Developing market-creating innovations in emerging markets

For over a decade I have been thinking about doing further study whether a masters, MBA, LLM or even a PhD. For various reasons I haven’t pressed the button on anything, although in 2019/20 I did get close.

I had just read a brilliant book called the “Prosperity Paradox” by Clayton Christensen which discusses why so many investments in economic development fail to generate sustainable prosperity, and how investing in market-creating innovations can create lasting change.

I was immediately hooked, although I was biased. I had focused my undergraduate business honours thesis on a former book by the same author called “The Innovators Dilemma”.

I found a few universities with suitable programmes and sent off applications. In the end I didn’t proceed with the offers but I thought it would be worthwhile to show the summary application and proposed research topic, approach and key areas to investigate. I still may look to explore this topic in the future albeit in a different way e.g. research, articles, consulting etc.

Proposed PhD Research title

“Developing Market-Creating Innovations That Drive Prosperity in Emerging Markets”

Background

The historic approach to improving outcomes and prosperity in emerging economies has typically focused around ‘poverty alleviation’ whereby private-sector companies and start-ups exploit existing markets at the top or ‘bottom of the pyramid’ (Prahalad 2004), or other initiatives which ‘push’ international aid, grants, loans, outsourcing, or incremental (‘sustaining’) improvements to existing offers for established customer bases. More recently, a number of leading management researchers led by Clayton Christensen (2019) argue that more successful approaches may lie in creating or ‘pulling in’ new market innovations that enable significant numbers of non-consumers to easily and affordably find a product or service to help them overcome daily struggles or solve an important problem. Pursuing this strategy (distinct from other types of innovation including ‘sustaining’ and ‘efficiency’ innovations), established firms and founders[1] typically see opportunity in the struggles of their respective frontier markets by targeting non-consumption in the broader market, creating not just products and services, but entire ecosystems, enabling infrastructure, networks and jobs to promote stability, prosperity and sustainable economic growth. Despite this opportunity, in 2016 alone, the OECD estimated that $143 billion was spent on official development approaches. Christensen (2019) however asks that what if this was instead channelled to support direct market-creation efforts in developing countries, even when those circumstances seemed unlikely? Some examples of market-creating innovations (MCI) are listed below:

  • M-PESA: A mobile money platform that enables the storage, transfer and saving of money without owning a bank account;
  • MicroEnsure: Affordable insurance for millions of people living on less than $3 a day;
  • Celtel: A pay-as-you-go mobile phone service that enables customers to purchase cell phone minutes from as little as 25 cents;
  • Galanz: An inexpensive microwave oven for the average Chinese citizen;
  • Tolaram: A tasty, inexpensive, easy-to-cook meal in Nigeria that can be prepared in less than three minutes;
  • Grupo Bimbo: Affordable, quality bread for Mexicans;
  • Ford Model T: An affordable car for the average American in the 1900s;

Topic

My PhD research will seek to build on these themes and the work of Christensen (2019) and others (Prahalad 2006; Auerswald 2012; Quadir 2014) to better understand the following key questions: How do established firms and start-ups successfully build market-creating innovations (“MCIs”) in emerging markets? Why are some firms successful, and others are not? The research will address gaps in understanding highlighted by Christensen (2019) in terms of further defining the process by which new markets are created, the characteristics that set market-creating innovators apart, and more details into the role of non-consumers (‘non-consumption economy’) in this process. In addition, my research will improve understanding of the relative importance of external factors which facilitate (or inhibit) success, including government, ecosystems, NGOs, investors, skilled labour, infrastructure, networks, and partners. The extent of benefits that MCIs deliver for society in terms of driving inclusive, sustainable and prosperous development across sectors including education, health, financial services, energy, and communications will also be analysed. Finally, the findings will deliver practical guidance, frameworks and insight for a wide range of international companies, entrepreneurs, governments, investors, thinktanks, and NGOs who pursue (or are looking to pursue) strategies and investments in emerging markets, or alternatively use the learnings to apply in more developed contexts

References

C.K. Prahalad, The Fortune at the Base of the Pyramid: Eradicating Poverty Through Profits (Upper Saddle River, NJ: Prentice Hall, 2006)

Philip Auerswald, The Coming Prosperity: How Entrepreneurs Are Transforming The Global Economy (Oxford University Press, 2012), 58

Iqbal Quadir, “Inclusive Prosperity in Low-Income Countries,” Innovations 9, no. 1-2 (2014): 65-66

Provide a statement of your research interests and intended research topics:

Research interests:

My research interests focus on how organisations innovate (across processes, practices, products, partnerships) in various contexts, including geographical (e.g. emerging or developed markets), new markets (e.g. non-consumption economy, consumer insight, go-to-market), operational (e.g. outsourcing, resource allocation, incentives, portfolio management, projects, change), offerings (e.g. new product development), technological (e.g. emerging technology), competitive (e.g. start-ups, business models), strategic (e.g. organic, M&A, JVs), human (e.g. leadership, culture, talent, skills), ecosystems (e.g. networks, partnerships, knowledge, public-sector), and sectoral (e.g. education, health, financial, energy).

I will use my many years of relevant professional experience working across most of the above topics (whether as an academic, lawyer, consultant, or founder) to ensure that the PhD research makes a substantial contribution to the academic research (see research questions), and provides practical insight for critical strategic and investment challenges for industry stakeholders (e.g. multi-national companies, investors, public sector, NGOs, etc).

Research topic:

My PhD research will seek to build on the themes of my research interests, and the work of Christensen and others to help answer the following question: How do established firms and start-ups successfully build market-creating innovations (“MCIs”) in emerging markets?

Core research questions include[2]:

  • What is the process by which these new markets are created?
  • What is the MCI development process within established and new (start-up) firms? For example, opportunity identification, development, investment, launch and scaling;
  • Why are some firms and efforts successful, and others are not?
  • What is the role non-consumers (‘non-consumption economy’) play in this process?
  • What are the qualities that set market-creating innovators and firms apart? For example, the ability to identify possibilities where there seem to be no customers;
  • What are the characteristics of the most successful (and unsuccessful) MCIs?  For example, business models, attributes, targeting non-consumption, value networks, ecosystems, partnering;
  • What are the most important internal and external conditions which facilitate or inhibit this process?
  • What commonalities exist across nations, sectors, firm size, age, or other variables?
  • What is the role of other key stakeholders in MCI development? For example, government, NGOs, investors, ecosystems, networks;
  • What are the key benefits for society, sectors (e.g. education) and stakeholders (e.g. government) from MCIs which deliver inclusive, sustainable and prosperous development?
  • What are the future implications for private and public sector organisations (e.g. companies, government, investors, NGOs etc) who wish to facilitate the future development of MCIs, or take the learnings into other developing (or developed) markets?

The below diagram describes the research focus areas and questions relevant to be asked:

Some anticipated research parameters may include a focus on:

  • Products/services and ventures which create new markets (“MCIs”) and benefits for large segments of the population, as opposed to product improvements (“sustaining innovations”) or efficiency gains (“efficiency innovations”).
  • Sectors that play key roles in prosperity development including education, health, financial services, communications, food and water, energy, and technology;
  • Data collection in a wide selection of geographies including BRIC nations, developing and developed nations (e.g. US), although the feasibility of this may prove problematic thereby requiring a more vertical approach (e.g. narrow to a few nations);
  • A time horizon of MCIs created post-2000 to capture more recent examples of MCI development;
  • An inter-disciplinary research approach given the wide-ranging research topic, building on academic researchers in fields including strategic management, strategic marketing, disruptive innovation, new product development, consumer insight, technology and operations management, innovation, organisational behaviour, leadership, emerging market strategy, international and economic development, and public policy;
  • Hybrid data collection strategy: whilst the research scope (e.g. companies, countries, sectors etc) and data collection strategy has yet to be defined, it is expected that a hybrid approach which mixes both qualitative and quantitative methods with primary and secondary research might be the most appropriate.  For example, face-to-face interviews, online surveys and case studies can help collect primary data to define firm MCI development processes. However, firm performance and development benefits (e.g. social, economic, and sectoral) will require quantitative analysis of public records and databases, as well as any additional internal data from private companies or government agencies.

[1] Examples of successful market-creating companies include Celtel (Africa), GrameenBank (Bangladesh), M-Pesa (Kenya), MicroEnsure (Africa), Jio (India) and Ford Motors (US) in the 1920s

[2] I have a range of sub-research questions but in the interests of brevity I have not included here.

Trends and issues of AI-enabled legal and compliance services

As AI continues to transform many industries[1], including the legal service industry, many experts are unanimous in predicting exponential growth in AI as a paramount technology to bring new tools and features to improve legal services and access to justice. Already, many aspects of the estimated $786B[2] market for legal services are being digitised, automated and AI-enabled whether discovery in litigation (e.g. RelativityAI), divorce (e.g. HelloDivorce), dispute resolution (e.g. DoNotPay) or contract management (e.g. IronClad).

As with many disruptive technologies, there are many experts who believe that AI will significantly disrupt (rather than extend) the legal market:

“AI will impact the availability of legal sector jobs, the business models of many law firms, and how in-house counsel leverage technology. According to Deloitte, about 100,000 legal sector jobs are likely to be automated in the next twenty years. Deloitte claims 39% of legal jobs can be automated; McKinsey estimates that 23% of a lawyer’s job could be automated. Some estimates suggest that adopting all legal technology (including AI) already available now would reduce lawyers’ hours by 13%”[3]

The real impact will be more nuanced over the long-term as whilst AI will eliminate certain tasks and some legal jobs, it will also augment and extend the way legal services are provided and consumed. In doing so, it will drive new ways of working and operating for both established and new entrant firms who will need to invest in new capabilities and skills to support the opening up new markets, new business models and new service innovations. In the past few decades, we have seen the impact of emerging and disruptive technologies on established players across many sectors, including banking (e.g. FinTechs), media and entertainment (e.g. music, movies, gambling), publishing (e.g. news), travel (e.g. Airbnb) and transportation (e.g. Uber). It is very likely traditional legal providers will be faced with the same disruptive challenges from AI and AI-enabled innovations bundling automation, analytics, and cloud with new business models including subscription, transaction or freemium.

Although AI and AI-enabled solutions present tremendous opportunities to support, disrupt or extend traditional legal services, they also present extremely difficult ethical questions for society, policy-makers and legal bodies (e.g. Law Society) to decide.

This is the focus of this article which sets out a summary of these issues, and is structured into two parts:

  1. Current and future use cases and trends of AI in legal and compliance services;
  2. Key issues for stakeholders including legal practitioners, society, organisations, AI vendors, and policy-makers.

A few notes:

  • This article is not designed to be exhaustive, comprehensive or academically detailed review and analysis of the existing AI and legal services literature. It is a blog post first and foremost (albeit a detailed one) on a topic of personal and professional interest to me, and should be read within this context;
  • Sources are referenced within the footnotes and acknowledged where possible, with any errors or omissions are my own.
  • Practical solutions and future research areas of focus is lightly touched on in the conclusion, however is not a focus for this article.

Part 1 – Current and future use cases of AI in legal and compliance services

Historically, AI in legal services has focused on automating tasks via software to achieve the same outcome as if a law practitioner had done the work. However, increasing innovation in AI and experimentation within the legal and broader ecosystem have allowed solutions to accelerate beyond this historical perspective.

The graphic below provides a helpful segmentation of four main use cases of how AI tools are being used in legal services[4]:

A wider view of use cases, which links to existing legal and business processes, is provided below:

  • e-discovery;
  • document and contract management
  • expertise automation;
  • legal research and insight
  • contract management
  • predictive analytics
  • dispute resolution
  • practice automation
  • transactions and deals
  • access to justice

Further context on a selection of these uses is summarised below (note, there is overlap between many of these areas):

  • E-Discovery – Over the past few years, the market for e-discovery services has accelerated beyond the historical litigation use case and into other enterprise processes and requirements (e.g. AML remediation, compliance, cybersecurity, document management). This has allowed for the development of more powerful and integrated business solutions enabled by the convergence of technologies including cloud, AI, automation, data and analytics. Players in the legal e-discovery space include Relativity, DISCO, and Everlaw.
  • Document and contract management The rapid adoption of cloud technologies have accelerated the ability of organisations across all sectors to invest in solutions to better solve, integrate and automate business processes challenges, such as document and contract lifecycle management. For contracts, they need to be initiated (e.g. templates, precedents), shared, stored, monitored (e.g. renewals) or searched and tracked for legal, regulatory or dispute reasons (e.g. AI legaltech start-ups like Kira, LawGeex, and eBrevia). In terms of drafting and collaboration, the power of Microsoft Word, Power Automate and G-Suite solutions has expanded along with a significant number of  AI-powered tools or sites (e.g. LegalZoom) that help lawyers (and businesses or consumers) to find, draft and share the right documents whether for commercial needs, transactions or litigation. New ‘alternative legal service’ entrants have combined these sorts of powerful solutions (and others in this list) with lower-cost labour models (with non-legal talent and/or lower-cost legal talent) to provide a more integrated offering for Fortune500 legal, risk and compliance teams (e.g. Ontra, Axiom, UnitedLex, Elevate, Integreon);
  • Expertise Automation –In the access to justice context, there are AI-powered services that automate contentious or bureaucratic situations for individuals such as utility bill disputes, small claims, immigration filing, or fighting traffic tickets (e.g. DoNotPay). Other examples include workflow automation software to enable consumers to draft a will (for a fixed fee or subscription) or chatbots in businesses to give employees access to answers to common questions in a specific area, such as employment law. It is forseeable that extending this at scale in a B2C context (using AI-voice assistants Siri or Alexa) with a trusted brand (e.g. Amazon Legal perhaps?) – and bundled into your Prime subscription alongside music, videos and same-day delivery – will be as easy as checking the weather or ordering an Uber.
  • Legal Research – New technologies (e.g. AI, automation, analytics, e-commerce) and business models (e.g. SaaS) have enabled the democratisation of legal knowledge beyond the historic use cases (e.g. find me an IT contract precedent or Canadian case law on limitation of liability). New solutions make it easy for clients and consumers (as well as lawyers) to find answers or solutions to legal or business challenges without interacting with a lawyer. In more recent times, legal publishing companies (e.g. LexisNexis, PLC, Westlaw) have leveraged legal sector relationships and huge databases of information including laws and regulations in multiple jurisdictions to build different AI-enabled solutions and business models for clients (or lawyers). These offerings promise fast, accurate (and therefore cost-effective) research with a variety of analytical and predictive capabilities. In the IP context, intellectual property lawyers can use AI-based software from companies like TrademarkNow and Anaqua to perform IP research, brand protection and risk assessment;
  • Legal and predictive analytics – This area aims to generate insights from unstructured, fragmented and other types of data sets to improve future decision-making.  A key use case are the tools that will analyse all the decisions in a domain (e.g. software patent litigation cases), input the specific issues in a case including factors (e.g. region, judge, parties etc) and provide a prediction of likely outcomes. This may significantly impact how the insurance and medical industry operate in terms of risk, pricing, and business models. For example, Intraspexion leverages deep learning to predict and warn users of their litigation risks, and predictive analytical company CourtQuant has partnered with two litigation financing companies to help evaluate litigation funding opportunities using AI. Another kind of analytics will review a given piece of legal research or legal submission to a court and help judges (or barristers) identify missing precedents In addition, there is a growing group of AI providers that provide what are essentially do-it-yourself tool kits to law firms and corporations to create their own analytics programs customized to their specific needs;
  • Transactions and deals – Although no two deals are the same, similar deals do require similar processes of pricing, project management, document due diligence and contract management. However, for various reasons, many firms will start each transaction with a blank sheet of paper (or sale and purchase agreement) or a sparsely populated one. However, AI-enabled document and contract automation solutions – and other M&A/transaction tools – are providing efficiencies during each stage of the process. In more advanced cases, data room vendors in partnership with law firms or end clients are using AI to analyse large amounts of data created by lawyers from previous deals. This data set is capable of acting as an enormous data bank for future deals where the AI has the ability to learn from these data sets in order to then:
    • Make clause recommendations to lawyers based on previous drafting and best practice.
    • Identify “market” standards for contentious clauses.
    • Spot patterns and make deal predictions.
    • Benchmark clauses and documents against given criteria.
    • Support pricing decisions based on key variables
  • Access to justice – Despite more lawyers in the market than ever before, the law has arguably never been more inaccessible. From a small consumer perspective, there are thousands of easy-to-use and free or low cost apps or online services which solve many simple or challenging aspects of life, whether buying properties, consulting with a doctor, making payments, finding on-demand transport, or booking household services. However, escalating costs and increasing complexity (both in terms of the law itself and the institutions that apply and enforce it) mean that justice is often out of reach for many, especially the most vulnerable members of society. With the accelerating convergence of various technologies and business models, it is starting to play a role in opening up the (i) provision of legal services to a greater segment of the population and (ii) replacing or augmenting the role of legal experts. From providing quick on-demand access to a lawyer via VC, accelerating time to key evidence, to bringing the courtroom to even the most remote corners of the world and digitizing many court processes, AI, augmented intelligence, and automation is dramatically improving the accessibility and affordability of legal representation. Examples include:
    • VC tools e.g. Zoom, FaceTime
    • Document and knowledge automation e.g. LegalZoom
    • ADR to ODR (online dispute resolution) e.g. eBay, Alibaba
    • Speed to evidence – Cloud-based, AI-powered technology e.g. DISCO

2. Key issues for the future of AI-power legal and compliance services  

There are many significant issues and challenges for the legal sector when adopting AI and AI-powered solutions. Whilst every use case of AI-deployment is unique, there are some overarching issues to be explored by key stakeholders including the legal profession, regulators, society, programmers, vendors and government.  

A sample of key questions include the following:

  • Will AI in the future make lawyers obsolete?
  • How does AI impact the duty of competence and related professional responsibilities?
  • How do lawyers, users and clients and stakeholders navigate the ‘black box’ challenge?
  • Do the users (e.g. lawyers, legal operations, individuals) and clients trust the data and the insights the systems generate?
  • How will liability be managed and apportioned in a balanced, fair and equitable way?
  • How do organisations identify, procure, implement and govern the ‘right’ AI-solution for their organisation?
  • Are individuals, lawyers or clients prepared to let data drive decision outcomes?
  • What is the role of ethics in developing AI systems?

Other important questions include:

  • How do AI users (e.g. lawyers), clients or regulators ‘audit’ an AI system?
  • How can AI systems be safeguarded from cybercriminals?
  • To what extent do AI-legal services need to be regulated and consumers be protected?
  • Have leaders in businesses identified the talent/skills needed to realise the business benefits (and manage risks) from AI?
  • To what extent is client consent to use data an issue in the development and scaling of AI systems?
  • Are lawyers, law students, or legal service professionals receiving relevant training to prepare for how they need to approach the use of AI in their jobs?
  • Are senior management and employees open to working with or alongside AI systems in their decisions and decision-making?

Below we further explore a selection of the above questions:

  • Obsolescence – When technology performs better than humans at certain tasks, job losses for those tasks are inevitable. However, the dynamic role of a lawyer — one that involves strategy, negotiation, empathy, creativity, judgement, and persuasion — can’t be replaced by one or several AI programs. As such, the impact of AI on lawyers in the profession may not be as dire as some like to predict. In his book Online Courts and the Future of Justice, author Richard Susskind discusses the ‘AI fallacy’ which is the mistaken impression that machines mimic the way humans work. For example, many current AI systems review data using machine learning, or algorithms, rather than cognitive processes. AI is adept at processing data, but it can’t think abstractly or apply common sense as humans can. Thus, AI in the legal sector enhances the work of lawyers, but it can’t replace them (see chart below[5]).
  • Professional Responsibility – Lawyers in all jurisdictions have specific professional responsibilities to consider and uphold in the delivery of legal and client services. Sample questions include:
    • Can a lawyer discharge professional duties of competence if they do not understand how the technology works?
    • Is a legal chatbot practicing law?
    • How does a lawyer provide adequate supervision where the lawyer does not understand how the work is being done or even ‘who’ is doing it?
    • How will a lawyer explain decisions made if they do not even know how those decisions were derived?

To better understand these complex questions, the below summaries some of the key professional duties and how they are being navigated by various jurisdictions:

Duty of Competence: The principal ethical obligation of lawyers when they are developing or assisting clients is the duty of competence. Over the past decade, many jurisdictions are specifically requiring lawyers to understand how (and why) new technologies such as AI, impact that duty (and related duties). This includes the requirement for lawyers to develop and maintain competence in ‘relevant technologies’. In 2012, in the US the American Bar Association (the “ABA”) explicitly included the obligation of “technological competence” as falling within the general duty of competence which exists within Rule 1.1 of its Model Rules of Professional Conduct (“Model Rules”)[6]. To date, 38 states have adopted some version of this revised comment to Rule 1.1. In Australia, most state solicitor and barrister regulators have incorporated this principle into their rules. In the future, jurisdictions may consider it unethical for lawyers or legal service professionals to avoid technologies that could benefit one’s clients. A key challenge is that there is no easy way to provide objective and independent analysis of the efficacy of any given AI solution, so that neither lawyers nor clients can easily determine which of several products or services actually achieve either the results they promise. In the long-term, it will very likely be one of the tasks of the future lawyer to assist clients in making those determinations and in selecting the most appropriate solution for a given problem. At a minimum, lawyers will need to be able to identify and access the expertise to make those judgments if they do not have it themselves.

Duty to Supervise – This supervisory duty assumes that lawyers are competent to select and oversee team members and the proper use of third parties (e.g. law firms) in the delivery of legal services[7]. However, the types of third parties used has expanded in recent times due to liberalisation of legal practice in some markets (e.g. UK due to the ABS laws allowing non-lawyers to operate legal services businesses). For example, alternative service providers, legal process outsourcers, tech vendors, and AI vendors have historically been outside of the remit of the solicitor or lawyer regulators (this is changing in various jurisdictions as discussed in below sections). By extension, to what extent is this more than just a matter of the duty to supervise what goes on with third parties, but how those third-parties provide services especially if technologies and tools are used? In such a case, potential liability issues arise if client outcomes are not successful: did the lawyer appropriately select the vendor, and did the lawyers properly manage the use of the solution?

The Duty to Communicate – In the US, lawyers also have an explicit duty to communicate to material matters to clients in connection with the lawyers’ services. This duty is set out in ABA Model Rue 1.4 and other jurisdictions have adopted similar rules[8]. Thus, not only must lawyers be competent in the use of AI, but they will need to understand its use sufficiently to explain to clients the question of the selection, use, and supervision of AI tools.

Black Box Challenge  

  • Transparency – A basic principle of justice is transparency – the requirement to explain and justify the reasons for a decision. As AI algorithms grow more advanced and rely on increasing volumes of structured and unstructured data sets, it becomes more difficult to make sense of their inner workings or how outcomes have been derived. For example, Michael Kearns and Aaron Roth report in Ethical Algorithm Design Should Guide Technology Regulation[9]:

“Nearly every week, a new report of algorithmic misbehaviour emerges. Recent examples include an algorithm for targeting medical interventions that systematically led to inferior outcomes for black patients, a resume-screening tool that explicitly discounted resumes containing the word “women” (as in “women’s chess club captain”), and a set of supposedly anonymized MRI scans that could be reverse-engineered to match to patient faces and names”.

Part of the problem is that many of these types of AI systems are ‘self-organising’ so they are inherently without external supervision or guidance. The ‘secrecy’ of AI vendors – especially those in a B2B and legal services context – regarding the inner workings of the AI algorithms and data sets doesn’t make the transparency and trust issue difficult for customers, regulators and other stakeholders. For lawyers, to what extent must they know the inner workings of that black box to ensure that she meets her ethical duties of competence and diligence? Without addressing this, these problems will likely continue as the legal sector increases its reliance on technology increases and injustices, in all likelihood, continue to arise. Over time, many organisations will need to have a robust and integrated AI business strategy designed at the board and management level to guide the wider organisation on these AI issues across areas including governance, policy, risk, HR and more. For example, during procurement of AI solutions, buyers, stakeholders and users (e.g. lawyers) must consider broader AI policies and mitigate these risk factors during vendor evaluation and procurement.

  • Algorithms – There are many concerns that AI algorithms are inherently limited in their accuracy, reliability and impartiality[10]. These limitations may be the direct result of biased data, but they may also stem from how the algorithms are created. For example, how software engineers choose a set of variables to include in an algorithm, deciding how to use variables, whether to maximize profit margins or maximize loan repayments, can lead to a biased algorithm. Programmers may also struggle to understand how an AI algorithm generates its outputs—the algorithm may be unpredictable, thus validating “correctness” or accuracy of those outputs when piloting a new AI system. This brings up the challenge of auditing algorithms:

“More systematic, ongoing, and legal ways of auditing algorithms are needed. . . . It should be based on what we have come to call ethical algorithm design, which begins with a precise understanding of what kinds of behaviours we want algorithms to avoid (so that we know what to audit for), and proceeds to design and deploy algorithms that avoid those behaviours (so that auditing does not simply become a game of whack-a-mole).”[11]

In terms of AI applications, most AI algorithms within legal services are currently able to perform only a very specific set of tasks based on data patterns and definitive answers. Conversely, it performs poorly when applied to the abstract or open-ended situations requiring judgment, such as the situations that lawyers often operate in[12]. In these circumstances, human expertise and intelligence are still critical to the development of AI solutions. Many are not sophisticated enough to understand and adapt to nuances, and to respond to expectations and layered meaning, and comprehend the practicalities of human experience. Thus, AI still a long way from the ‘obsolescence’ issue for lawyers raised above, and further research is necessary on programmers’ and product managers’ decision-making processes and methodologies when ideating, designing, coding, testing and training an AI algorithm[13]:

  • Data – Large volumes of data is a critical part of AI algorithm development as training material and input material. However, data sets may be of poor quality for a variety of reasons. For example, the data an AI system is ‘trained’ on may well include systemic ‘human’ bias, such as recruiters’ gender or racial discrimination of job candidates. In terms of data quality in law firms, most are slow at adopting new technologies and tend to be “document rich, and data poor” due, in large part, to legacy on-premise systems (or hybrid cloud) which do not integrate with each other. As more firms and enterprises transition to the cloud, this will accelerate the automation of business processes (e.g. contract management) with more advanced data and analytics capabilities to enable and facilitate AI system adoption (in theory, however there are many constraints within traditional law firm business and operating models which makes the adoption of AI-enabled solutions at scale unlikely). However, 3rd party vendors within the legal sector including e-discovery, data rooms, and legal process outsourcers – or new tech-powered entrants from outside of the legal sector – do not have such constraints and are able to innovate more effectively using AI, cloud, automation and analytics in these contexts (however other constants exist such as client consent and security). In the court context, public data such as judicial decisions and opinions are either not available or so varied in format as to be difficult to use effectively[14]. Beyond data quality issues, significant data privacy, client confidentiality and cybersecurity concerns exist which raises the need to define and implement standards (including safeguards) to build confidence in the use of algorithmic systems – and especially in legal contexts. As AI becomes more pervasive within law firms, legal departments, legal vendors (including managed services) and new entrants outside of legal, a foundation with strong guidelines for ethical use, transparency, privacy, cross-department sharing and more becomes even crucial[15].
  • Implementation – Within the legal sector, law firms and legal departments are laggards when it comes to adopting new technologies, transforming operations, and implementing change. With business models based on hours billed (e.g. law firms), this may not incentivize the efficiency improvements that AI systems can provide.  In addition:

“Effective deployment of AI requires a clearly defined use case and work process, strong technical expertise, extensive personnel and algorithm training, well-executed change management processes, an appetite for change and a willingness to work with the new technologies. Potential AI users should recognize that effectively deploying the technology may be harder than they would expect. Indeed, the greatest challenge may be simply getting potential users to understand and to trust the technology, not necessarily deploying it[16].

However, enterprises (e.g. Fortune500), start-ups, alternative service providers (e.g. UnitedLex) and new entrants from outside of legal do not suffer from these constraints, and are likely to be more successful – from a business model and innovation perspective – in adopting new AI-enabled solutions for use with clients (although AI-enabled providers must work to overcome client concerns as discussed above).   

  • Liability – There are a number of issues to consider on the topic of liability. Key questions are set out below:
    • Who is responsible when things do go wrong? Although AI might be more efficient than a human lawyer at performing these tasks, if the AI system misses clauses, mis-references definitions, or provides incorrect outcome/price predictions caused by AI software, all parties risk claims depending on how the parties apportioned liability. The role of contract and insurance is key, however this assumes that law firms have the contractual means of passing liability (in terms of professional duties) onto third parties. In addition, when determining relative liability between the provider of the defective solution and the lawyer, should a court consider the steps the lawyer took to determine whether the solution was the appropriate one for use in the particular client’s matter?
    • Should AI developers be liable for damage caused by their product? In most other fields, product liability is an established principle. But if the product is performing in ways no-one could have predicted, is it still reasonable to assign blame to the developer? AI systems also often interact with other systems so assigning liability becomes difficult. AI solutions are also fundamentally reliant on the data they were trained on, so liability may exists with the data sources.  Equally, there are risks of AI systems that are vulnerable to hacking.
    • To what extent are, or will, lawyers be liable when and how they use, or fail to use, AI solutions to address client needs? One example explained above is whether a lawyer or law firm will be liable for malpractice if the judge in a matter accesses software that identifies guiding principles or precedents that the lawyer failed to find or use. It does not seem to be a stretch to believe that liability should attach if the consequence of the lawyer’s failure to use that kind of tool is a bad outcome for the client and the client suffers injury as a result.
  • Regulatory Issues – As discussed above, addressing the significant issues of bias and transparency in AI tools, and, in addition, advertising standards, will grow in importance as the use of AI itself grows. Whilst the wider landscape for regulating AI is fragmented across industry and political spheres, there are signs the UK, EU and US are starting to align.[17] Within the legal services sector, some jurisdictions (e.g. England, Wales, Australia and certain Canadian provinces) are in the process of adopting and implementing a broader regulatory framework. This approach enables the legal regulators to oversee all providers of legal services, not just traditional law firms and/or lawyers. However, in the interim the implications of this regulatory imbalance will become more pronounced as alternative legal service providers play an increasing role in providing clients with legal services, often without any direct involvement of lawyers. In the long run, a broader regulatory approach is going to be critically important in establishing appropriate standards for all providers of AI-based legal services.
  • Ethics – The ethics of AI and data uses remains a high concern and key topic for debate in terms of the moral implications or unintended consequences that result from the coming together of technology and humans. Even proponents of AI, such as Elon Musk’s OpenAI group, recognise the need to police AI that could be used for ‘nefarious’ means. A sample of current ethical challenges in this area include:
    • Big data, cloud and autonomous systems provoke questions around security, privacy, identify, and fundamental rights and freedoms;
    • AI and social media challenge us to define how we connect with each other, source news, facts and information, and understand truth in the world;
    • Global data centres, data sources and intelligent systems means there is limited control of the data outside our borders (although regimes including GDPR is addressing this);
    • Is society content with AI that kills? Military applications including lethal autonomous weapons are already here;
    • Facial recognition, sentiment analysis, and data mining algorithms could be used to discriminate against disfavoured groups, or invade people’s privacy, or enable oppressive regimes to more effectively target political dissidents;
    • It may be necessary to develop AI systems that disobey human orders, subject to some higher-order principles of safety and protection of life;

Over the years, the private and public sectors have attempted to provide various frameworks and standards to ensure ethical AI development. For example, the Aletheia Framework[18] (developed by Rolls-Royce in an open partnership with industry) is a recent, practical one-page toolkit that guides developers, executives and boards both prior to deploying an AI, and during its use. It asks system designs and relevant AI business managers to consider 32 facets of social impact, governance and trust and transparency and to provide evidence which can then be used to engage with approvers, stakeholders or auditors. A new module added in December 2021 is a tried and tested way to identify and help mitigate the risk of bias in training data and AIs. This complements the existing five-step continuous automated checking process, which, if comprehensively applied, tracks the decisions the AI is making to detect bias in service or malfunction and allow human intervention to control and correct it.

Within the practice of law, while AI offers cutting-edge advantages and benefits, it also raises complicated questions for lawyers around professional ethics. Lawyers must be aware of the ethical issues involved in using (and not using) AI, and they must have an awareness of how AI may be flawed or biased. In 2016, The House of Commons Science and Technology Committee (UK Parliament) recognised the issue:

“While it is too soon to set down sector-wide regulations for this nascent field, it is vital that careful scrutiny of the ethical, legal and societal dimensions of artificially intelligent systems begins now”.

In a 2016 article in the Georgetown Journal of Legal Ethics, the authors Remus and Levy were concerned that:

“…the core values of legal professionalism meant that it might not always be desirable, even if feasible, to replace humans with computers because of the different way they perform the task. This assertion raises questions about what the core values of the legal profession are and what they should or could be in the future. What is the core value of a solicitor beyond reserved activities? And should we define the limit of what being a solicitor or lawyer is?[19]

These are all extremely nuanced, complex and dynamic issues for lawyers, society, developers and regulators at large. How the law itself may need to change to deal with these issues will be a hot topic of debate in the coming years.

Conclusion

Over the next few years there can be little doubt that AI will begin to have a noticeable impact on the legal profession and consumers of legal services. Law firms, in-house legal departments and alternative legal services firms and vendors – plus new entrants outside of legal perhaps unencumbered by the constraints of established legal sector firms – have opportunities to explore and challenges to address, but it is clear that there will be significant change ahead. What is required of a future ‘lawyer’ (this term may mean something different in the future) or legal graduate today – let alone in 2025 or 2030 versus new lawyers of a few decades ago, will likely be transformed in many ways. There are also many difficult ethical questions for society to decide, for which the legal practice regulators (e.g. Law Society in England and Wales) may be in a unique position to grasp the opportunity of ‘innovating the profession’ and lead the debate. On the other hand, as the businesses of the future become more AI-enabled at their core (e.g. Netflix, Facebook, Google, Amazon etc), the risk that many legal services become commoditised or a ‘feature set’ within a broader business or service model is a real possibility in the near future.

At the same time, AI itself poses significant legal and ethical questions across all sorts of sectors and priority global challenges, from health, to climate change, to war, to cybersecurity. Further analysis on the legal and ethical implications of AI for society, legal practitioners, organisations, AI vendors, and policy-makers, plus what practical solutions can be employed to navigate the safe and ethical deployment of AI in the legal and other sectors, will be critical.


[1] AI could contribute up to $15.7 trillion1 to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption side effects.

[2] https://www.statista.com/statistics/605125/size-of-the-global-legal-services-market/

[3] https://jolt.law.harvard.edu/digest/a-primer-on-using-artificial-intelligence-in-the-legal-profession

[4] https://www.morganlewis.com/-/media/files/publication/presentation/webinar/2020/session-11_the-ethics-of-artificial-intelligence-for-the-legal-profession_18june20.pdf

[5] https://kirasystems.com/learn/can-ai-be-problematic-in-legal-sector/

[6] https://www.americanbar.org/groups/professional_responsibility/publications/professional_lawyer/27/1/the-future-law-firms-and-lawyers-the-age-artificial-intelligence

[7] Australian Solicitors Conduct Rules 2012, Rule 37 Supervision of Legal Services.

[8] https://lawcat.berkeley.edu/record/1164159?ln=en

[9] https://www.brookings.edu/research/ethical-algorithm-design-should-guide-technology-regulation/

[10] https://hbr.org/2019/05/addressing-the-biases-plaguing-algorithms

[11] https://www.brookings.edu/research/ethical-algorithm-design-should-guide-technology-regulation/

[12] https://hbr.org/2019/05/addressing-the-biases-plaguing-algorithms

[13] https://bostonreview.net/articles/annette-zimmermann-algorithmic-political/

[14] https://www.law.com/legaltechnews/2019/10/29/uninformed-or-underwhelming-most-lawyers-arent-seeing-ais-value/

[15] https://www.crowell.com/NewsEvents/Publications/Articles/A-Tangled-Web-How-the-Internet-of-Things-and-AI-Expose-Companies-to-Increased-Tort-Privacy-and-Cybersecurity-Litigation

[16] https://www.lexisnexis.co.uk/pdf/lawyers-and-robots.pdf

[17] https://www.brookings.edu/blog/techtank/2022/02/01/the-eu-and-u-s-are-starting-to-align-on-ai-regulation/

[18] https://www.rolls-royce.com/sustainability/ethics-and-compliance/the-aletheia-framework.aspx

[19]https://go.gale.com/ps/i.do?id=GALE%7CA514460996&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=10415548&p=AONE&sw=w&userGroupName=anon%7E138c97cd

Top ten traps which cause GC’s to fail around technology, automation and change

I recently came across a brilliant guide from Plexus, a legal software and services provider based in Australia. Although most GCs will rate rate ‘investing in technology and automation’ as their top priority, many initiatives will never get past the starting line.

There are many reasons for this and everyone’s context is different. It is certainly not for lack of intent, ambition, need, or interest.

According to Plexus, the biggest challenge functional leaders have is when they are required to rapidly work and operate in a cross-functional way. These skills are a new ‘core’ capability for a legal function or executive:

If you ask a GC how they select and sign up a new law firm to spend $100,000 - the answer is often as simple as a few emails and signed engagement letter. Ask them how they will spend half that amount on technology, and they will scratch their head… even though - because of the ‘sunk cost’ nature of professional services spend’ it is far more likely that it will not generate value

Plexus.co

I have summarised the top ten traps below:

You let risk aversion get the better of you.

You approach the project like a contract negotiation.

You frame the business case around ‘what legal needs’

You get hung up in ‘integrations’

You get too many people involved.

You try to go too big too early.

You delegate responsibility to others.

You allow other functions to drive the agenda.

You fall for the ‘tomorrow fallacy’.

You work with vendors with the wrong orientation.

I highly recommend reading the full version here which contains more detail on the above traps plus extremely practical ‘do this’ and ‘do not do this’ strategies and tactics.

Legaltech Venture Investment

This week Crunchbase produced some numbers covering Legal tech investments in 2021.

Legal tech companies have already seen more than $1 billion in venture capital investments so far this calendar year, according to Crunchbase data. That number smashes the $510 million invested last year and the all-time high of $989 million in 2019.

While dollars are higher, deal flow is a little behind previous years, with 85 funding rounds being announced so far in 2021, well behind the pace of 129 deals last year and 147 in 2019.

Some of the largest rounds in the sector this year include:

  • San Francisco-based Checkr, a platform that helps employers screen job seekers through initiating background checks, raised a $250 million Series E at a $4.6 billion valuation earlier this month;
  • San Francisco-based legal services provider Rocket Lawyer closed a $223 million venture round in April; and
  • Boston-based on-demand remote electronic notary service Notarize raised a $130 million Series D in March at a reported $760 million valuation.

According to various start-up founders:

“This mainly is a paper-based industry. However, COVID exposed inefficiencies and it forced people to look at everything you do and explore new ways.”- Patrick Kinsel, founder and CEO at Notarize

“There’s no doubt COVID provided huge tailwinds for legal tech growth,” said Jack Newton, co-founder and CEO at Vancouver-based legal tools platform Clio, which raised a $110 million Series E at a $1.6 billion valuation. “It was the forcing factor for firms that had put off their transformation.”

“Since the midpoint of last year, we’ve seen an acceleration of our business,” said Vishal Sunak, co-founder and CEO at Boston-based management tool developer LinkSquares, which used that increased interest to help raise a $40 million Series B in July.

Here are a few observations on what is going on:

  1. Impact of the Cloud: Just as in many industries, the cloud and other new tech had been slowly changing the legal world for more than a decade. However, after COVID caused offices to close and legal processes and documents to go virtual, adoption of those technologies skyrocketed. Investors started to eye technologies that took many firms “in-house” processes and moved them to the cloud—many involving documentations and filings as well as tools to help better communicate with clients.

2. Cloud-first generation: Many general counsels are now coming from a “cloud-first” generation and know the importance of things such as data insights that can help predict outcomes. Just as data and AI has changed marketing, sales and finance, the legal community is now catching on, and many don’t just want to be a cost centre

3. Increasing investor knowledge: The increasing market and scaling legaltech start-ups are causing VCs to take note. While many investors eyed the space in the past, more investors have knowledge about contracts and legal tech, and founders do not tend to have to explain the market

However, the market is still small albeit growing and no ‘goliaths’ exist in the space. With no large incumbents, how investors see returns remains a popular question.

This may chance if, for example, horizontal software companies like Microsoft or Salesforce could become interested in the space—as legal tech has data and analytics those types of companies find useful, Wedler said.

Some companies in the space also have found private equity a viable exit, with films like Providence Equity rolling up players such as HotDocs and Amicus Attorney several years ago.

However, perhaps more interesting to some startups is the legal tech space even saw an IPO this year, with Austin, Texas-based Disco going public on the New York Stock Exchange in July. The company’s market cap now sits at $2.8 billion.

One thing most seem certain about is that while the legal world’s tech revolution may have been brought on by a once-in-a-century event—there is no turning back.

How to Fail Fast and Pivot: Lessons from the Legal Ops Front Lines

This week I attended a virtual Summit hosted by CLOC (Corporate Legal Operations Consortium). One interesting session covered lessons learned from developing and implementing legaltech and operation changes within legal and compliance teams of large corporates and SMEs.

Panelists including range of lawyers, project managers and legalops experts from Netflix, Salesforce and GE and covered topics including:

*How to manage change and being comfortable with being uncomfortable

*Avoiding big bang deployments which are so risky now vs POC/MVP and more agile approaches to change

*Learning how to take some budget off the total and use it for experimenting and be prepared to fail.

The below is a blurb introducing the session:

“…On the path to success, failure is not only an option, it’s inevitable. Mistakes, missteps, and misunderstandings are opportunities to acquire new skills and knowledge that can contribute to your professional growth. The growing and evolving legal operations profession is filled with opportunities to evolve beyond errors. 

In this honest and impactful session, legal operations professionals will share a key moment of failure and how they learned and grew from it. After hearing from the panelists on their vulnerable moments of growth, we will spend time as a group sharing our own stories and offering our peers perspectives and possible solutions for overcoming some of their failures…”

Below I captured a few nuggets of gold from the panellists:

  • Give a purpose to failure; this helps to gain buy-in from users and clarify the bigger picture
  • Allow the community to own the new way to work rather than push to them
  • Leadership (e.g. town hall) to set the tone
  • Wider business context, and show why the change is important
  • Be transparent – there will be failure. Expect it. Tolerate it!
  • If leading the change, need to get to a stage of comfortable with being uncomfortable…but not too uncomfortable. Have to be mindful of current state of culture, empathise with users
  • Need to balance focus on the big picture using storytelling, sales skills etc as can’t control every details of the change
  • Experimental in communication, design thinking, courageous leadership, state of culture a huge consideration on how to balance approach
  • Big bang projects are so risky now vs POC/MVP and more agile approaches

Evaluating Your Business Idea With Better Customer Discovery Questions

As someone who is fascinated with start-ups and business ideas, I loved this post called “100 Questions You Can Ask In Customer Interviews”.

In it, the author compiles an inventory of questions you might need to better understand the problem you are trying to solve for the customer, how important is it for them in the context of their life, how they currently solve it (or not), and so on.

Having founded start-ups and advised many other founders, it still surprises me that many people do not take the time to do this work to the quality and depth required. Many do not even know about it or value its importance, which really baffles me. Obviously it is more ‘exciting’ to get on with it and ‘start building’, although this is fraught with serious risks.

In any case, the tool above is certainly a great way to have better conservations with potential customers and shape propositions accordingly.

A Stronger Science, Technology + Innovation Agenda: 6 Areas of Focus

“Science, technology and innovation (STI) are universally recognized as key drivers for economic growth, improving prosperity, and essential components for achieving the Sustainable Development Goals (SDGs)”  UN Conference on Trade and Development (2019)

A few months ago I wrote down some thoughts and questions after being inspired by political events where I live (Guernsey) and internationally (e.g. US). In both jurisdictions, the balance of power has dramatically shifted for different reasons but both against a backdrop of major crises including health (COVID), rising inequality, and skills gaps.

In essence, I was trying to think through answering 2 key questions for the new Government and ecosystem players (e.g.businesses, investors, educators etc): what are some key STI areas of focus, and what questions would I ask?

I have since shared the memo with various stakeholders in the ecosystem, and now I thought it would make sense to post it publicly here. If you have any feedback, be sure to let me know

——-

Research, analysis and policy development opportunities and questions for the new Government and ecosystem players (e.g. businesses, investors, educators etc)

Business case for an STI economy: the importance of ‘science, technology and innovation’ for Guernsey’s future in driving economic growth and improved prosperity for all citizens 

  • Key STI trends, opportunities and challenges 
  • What is STI/digital, why important, global best practices
  • Why important for Gsy?
  • Defining and measuring Guernsey’s existing STI/digital economy 
  • Benefits and impacts to economy, society, prosperity and infrastructure 
  • Jobs, skills, human capital and education
  • Role of stakeholders e.g. education, govt, business, people etc
  • Building blocks, what is needed? E.g. 
    • Policy and regulatory frameworks
    • Institutional setting and governance
    • Entrepreneurial ecosystems and access to finance
    • Human capital
    • Technical/ICT & R&D infrastructure
  • Relevance of Sustainability, Green Finance, Solar/Wind, FinTech, RiskTech, RegTech, GovTech
  • Role of tax policy, skills, FDI, govt, business etc 
  • Strategic options for Guernsey 

Resources – A FRAMEWORK for Science, Technology and Innovation Policy Reviews: UN Conference on Trade and Development 

http://www.oecd.org/innovation/inno/

OECD (2020) A Common Framework for Measuring The Digital Economy 

ICT Infrastructure: Reshaping SURE Telecoms as a strategic asset to benefit the future of Guernsey and investigating the promise of new tech e.g. fibre, 5G etc

  • What is SURE’s current investment model, business strategy etc with regard to infrastructure, network performance and speeds, pricing and tariffs etc
  • How does it fit with Guernsey’s requirements, strategy and vision for the future? 
  • To what extent does the existing relationship with Sure/Cicra/others need to be reshaped?
  • What is the overall technology vision of Guernsey? E.g. the most digitally-enabled small island economy in the world? KPIs? 
  • What are the existing telco infrastructure challenges and market opportunities? E.g. connectivity, fibre, 5G etc
  • What are the key ICT indicators/KPIs for Guernsey?
  • How good or bad is the current network/asset performance? Where is the evidence? 
  • To what extent does Sure need to be incentivised to improve performance?
  • How will that benefit Guernsey? E.g. access, education, WFH, FDI, economic growth etc
  • What are the different levers to pull that can assist that?
  • What are the roles of the key stakeholders and to what extent does this need reshaping? E.g. Cicra, 
  • What are some example ownership models from around the world that should be considered?

Resource – 14 Key ICT Indicators

Smarter e-Government: Transforming public sector services to improve efficiency and effectiveness

  • Agilisys IT procurement: What was the promise vs reality, where is the accountability and island benefit (e.g. jobs, knowledge etc), what is the road ahead, and what needs to change 
    • What is the current status of the Agilysys IT procurement, what are the benefits (e.g. local jobs) vs costs, what is the roadmap
    • Current status and how successful has it been, why?
    • What was the scope of the original deal that was signed? How did that change over time? 
    • How much has been spent by the SOG?
    • What have been the benefits? E.g. local jobs, tax payer savings etc
    • How is the vendor managed, programme governed, quality assurance provided, risks/issues etc 
    • Strategic options and recommendations 
    • Role of new ways of working and thinking e.g. agile, design, lean
  • e-Gov/Future Digital Services
    • What is the latest vision and roadmap forward? Is it good enough?
    • In 2017 FDS was championed with a delayed and time-consuming procurement process which say Agilysys hired – what is the status?
    • What are the roadblocks, challenges vs opportunities 
      • E.g. SOG IT procurement decision-making and processes
    • What can we learn from other e-gov national leaders e.g. Estonia
    • What are the big opportunities/challenges?
    • What are the areas of focus?
    • What is required to move forward?
    • What are the costs/benefits?

Digital skills: how to re/upskill the population to be fit for the future 

  • What digital skills does Guernsey need? 
    • E.g. Data Analysis, Business Analysis, CS/Software Engineering, Product Development, Agile, PM, UX/UI, Google etc
  • What courses should be created?
    • For which groups e.g. school-leavers vs mid-level vs later stage 
  • How to deliver this?
  • Best practice models from similar jurisdictions 
  • Who to deliver this?
  • How much to deliver this?

Entrepreneurship and innovation ecosystems: what is the Innovation & Growth vision for Guernsey PLC? How to create a more efficient, attractive and collaborative system: 

  • What new tax policies, incentives and regulatory changes are needed to drive the captial/FDI and other behaviours? E.g. EIS
  • How to encourage businesses to invest in R&D?
  • How to encourage angels/HNWI/funds/businesses/VC etc reallocate investments into start-ups?
  • Build on my article here – https://andrewessa.com/2020/08/28/digital-ecosystems-tzars-puzzle-pieces-the-halo-effect/
  • What is the Innovation vision for Guernsey PLC
  • Baselining and measurement
    • What is Guernsey’s approach and how effective is it?
    • Strengths/weaknesses
    • Challenges/opportunities
    • Actors in the ecosystem
  • What is best practice in small or island communities and competing off-shore jurisdictions?
    • What have Jersey done? cost/benefit?
    • What can we learn from them and other nations?
    • What could we improve?
    • What needs to happen?
  • Ecosystem pillars: how effective are the current actors and what needs to change 
    • Tax, finance and incentives 
      • The role of tax policy, tax credits, R&D, and other incentives 
      • Access to capital, finance
    • Guernsey Innovation Fund
      • What has been invested in to date?
      • What type of investments and how much?
      • What mix of businesses e.g. local vs overseas, maturity etc
      • What returns, benefits to date?
      • Who is involved in the fund, what governance etc
      • What is success? 
      • How does it compare to other small community or island ‘sovereign’ investment funds?
      • What is ‘best practice’ in this space?
    • Human capital strategies – from cradle to grave 
      • Understanding the digital/skills crisis e.g. PwC report
      • Practical solutions to solve it 
      • Alignment with Guernsey PLC strategic vision 
      • Baselining, what new skills, how to up/reskill, what incentives for businesses and people 
      • Life-long learning 
      • More flexible access to skills and talent 
      • Immigration policies 
    • Digital Greenhouse
      • Current vs future state
      • Cost/benefit
      • Challenges/opportunities
      • Recommendations 
    • Governance 
      • Effectiveness of current system
      • What changes are needed
      • What models, what structure, what responsibilities etc e.g. Guernsey Innovation 
    • Corporate innovation
      • How to incentivise investments in skills and new ventures 
    • International cooperation
      • Role of collaboration including within the Bailiwick 
    • New business opportunities 
      • The role of new ‘market creation innovation’ (MCI) policies- see below
      • Relevance of Sustainability, Green Finance, Solar/Wind, FinTech, RiskTech, RegTech, GovTech
      • Regulatory innovation models e.g. sandboxes 

Resource – OECD Review of Innovation Policy – New Zealand (2007)

Other sample areas of ‘innovation policy’ to explore:

  • Environment: Sustainability, ESG and climate change  
    • What is best practice around the world in small island or communities 
    • What are some potential or viable new business opportunities
    • Assess current state of initiatives (e.g. Green Funds)
    • Evaluate new initiatives e.g. Wind, solar etc
  • International collaboration and trade
    • How important is it to be more market-focused and rethink and prioritise international partnerships/affairs? E.g. Jersey
    • A colleague and partner Chris Brock covers some of this topic in a recent report here
  • Regulatory, governance and risk innovation: to what extent do the various regulatory bodies and related private/public sector organisations (e.g. GFSC, Cicra, TISE, DPO etc) need to adopt a more balanced and innovative approach to regulation and new business? How to accelerate existing initiatives and opportunities? e.g. Green Finance
    • What is the nature of the current approach? 
    • How to balance bureaucracy/risk-adversity in the Guernsey ecosystem but at same time encourage innovation, FDI and new businesses?
    • What are best practice examples of innovative regulatory/risk models from competing or similar jurisdictions or around the world?
    • To what extent could this be useful in Guernsey?
    • How is the wider market evolving and how will this impact Guernsey?
    • What are the pros/cons and opportunities/threats?
    • What new business opportunities a more innovative approaches enable? E.g. FinTech, RegTec
    • What are practical recommendations forward and for which actors 
  • Role of market-creating innovations to drive prosperity AND economic growth (MCI): What is the opportunity for Guernsey to incubate market-creating innovations for local use and export? And how can Guernsey facilitate the development of MCIs across different sectors – e.g. FS, Infrastructure, Transport, Environment etc – for local use and export to improve income inequality and other social/economic benefits? 

Resources:

https://hbr.org/2019/01/cracking-frontier-markets

Understanding Value Proposition

Last week I posted here about my experience mentoring a start-up team from LSE’s Innovation Accelerator programme.

This week I have asked the team to get more ‘granular’ to better define, understand and analyse the problem they are focused on solving i.e. identify user pain-points, challenges, jobs to be done.

In the original Uber pitch deck the co-founders demonstrated a good understanding of the problem for the different stakeholders. Once this is done to a satisfactory level, you can then start to ‘test’ with customer research, experiments and MVPs.

To assist the team, below I provided some great videos from Strategyzer

The Value Proposition Canvas Explained
Value Proposition Canvas: Best Practices
The Basics Of Testing Business Ideas

Corporate Governance And Innovation: 10 Questions for Boards

To be successful, companies must be led by leaders – the CEO, top executives and board of directors – who are deeply and irrevocably committed to innovation as their path to success. Just making innovation one of many priorities or passive support for innovation are the best ways to ensure that their company will never become a great innovator – Bill George, former CEO and Chairman of Medtronic and Professor at Harvard Business School

A few weeks back I gave a talk focused strategic response, adaptability and innovation in a COVID world to an audience of NEDs mainly focused on off-shore financial services (FS) sector firms.

Given how highly regulated and risk-adverse many off-shore FS firms are, unsurprisingly questions were focused on the challenges of balancing risk vs innovation, how to make change happen at board level, and how to navigate director duties.

It got me thinking….

What are the ways for boards to show their real, concrete commitment to innovation and technology, and its governance?

As I discussed in my talk, all global business and technology trends point in the same direction: there is a need for more proactive and far-sighted management of innovation. Innovation for business reinforcement and growth – and for transformation in particular – are, of course, the prime responsibility of top management. Innovation governance – a holistic approach to steering, promoting and sustaining innovation activities within a firm – is thus becoming a critical management imperative.

Boards of directors also need to be more than just observers of this renewed management interest in innovation, because so much is at stake in an increasingly pervasive digital and COVID world. In a growing number of industries and companies, innovation will determine future success or failure.

Of course, boards do not need to interfere with company leaders in the day-to-day management of innovation, but they should include a strong innovation element in their traditional corporate governance missions. For example:

  • Strategy review;
  • Auditing;
  • Performance review;
  • Risk prevention and, last but not least;
  • CEO nomination.  

It is therefore a healthy practice for boards to regularly reflect on the following questions:

  • To what extent is innovation, broadly defined, an agenda item in our board meetings?
  • What role, if any, should our board play vis-à-vis management regarding innovation?

To facilitate their self-assessment, boards should answer a number of practical questions that represent good practice in the governance of innovation. According to various innovation governance experts, including Professor Jean-Phillipe Deschamps at IMD Business School and author of Innovation Governance: How Top Management Organises and Mobilises for Innovation (2014), below are ten good-practice questions and perspectives to incorporate into any board evaluation:

1) Have we set an innovation agenda in many, if not most, of our meetings?

Board meetings are always crowded with all kinds of statutory corporate governance questions, without talking about the need to handle unexpected events and crises. So, unless innovation issues are inserted into the board agenda, they won’t be covered. It is a good practice to include innovation as a regular and open agenda item in at least a couple of board meetings per year. It should also be a key item in the annual strategy retreat that many boards set up with the top management team. Many of the following questions will provide a focus for this open innovation agenda item.

2) Do we regularly review “make-or-break” innovation projects?

In some industries, like pharmaceuticals, automotive, energy and aerospace, company boards regularly review the big, often risky innovation projects that are expected to provide future growth. They also do so because of funding issues – some of these projects may require extraordinary and long-term investments that need board approval. But in other industries, boards may be only superficially aware of the new products or services under preparation. Arguably, there may be several projects that are still small in terms of investments but could become “game-changers,” and it would be wise for the board to review them regularly in the presence of R&D leaders and innovators.

3) Do we regularly review and discuss the company’s innovation strategy?

Boards are generally aware of – and discuss – the company’s business strategy, particularly when it involves important investments, mergers and acquisitions and critical geopolitical moves. But what about the company’s innovation strategy (if it exists and is explicit, which is not always the case)? There are indeed important decisions that might concern the board in a company’s innovation choices because of their risk level and impact. Think of the adoption of innovative new business models, the creation of totally new product categories, or the conclusion of important strategic alliances and partnerships for the development, introduction and distribution of new products. Management’s adoption of a clear ‘typology’ of innovation in its board communication would definitely facilitate such reviews and discussions.

4) Do we regularly review and discuss the company’s innovation risk?

Boards usually devote a significant amount of time to risk assessment and reduction. But their focus tends to be on financial, environmental, regulatory and geopolitical risk. Innovation risk may be underestimated, except in the case of large projects involving huge investments and new technologies. But internal innovation risk is not limited to new project and technology uncertainties. It can be linked to the loss of critical staff, for example. Innovation risk can also be purely external. Will competitors introduce a new disruptive technology that will make our products and processes obsolete? Will new entrants invade our market space through different, more effective business models? Will our customers expect new solutions that we have not thought about? Assessing innovation risk is critical to avoid what Ravi Arora calls “pre-science errors” – underestimating the speed and extent of market or technology changes – and, even worse, “obstinacy errors” – sticking to one’s solution too long after markets or technologies have changed. It is the duty of the board to prevent such errors.

5) Do we set specific innovation goals for management?

Boards often exert strong pressure on management by setting performance goals. But most of these goals tend to focus on financial performance: top and bottom line growth, earnings per share, capital utilization ratios, etc. Some companies add other goals to focus management’s attention on worthwhile new objectives, such as globalization or sustainability. But what about innovation if it increasingly becomes a growth driver? A number of highly innovative companies have indeed included innovation goals in the CEO’s balanced scorecard. One of the most commonly found is the percentage of sales achieved through new products, typically products introduced in the past few years. But there are many other innovation goals to incite conservative management teams to take more risk – for example, the percentage of R&D spent on high risk/high impact projects. Innovation goals are interesting because they actually determine much of the company’s long-term financial performance. It is therefore good practice to discuss these goals with the management team and retain the most meaningful ones.

6) Do we review innovation management issues with the CEO?

Most sustained innovation programs raise many issues. Some of them are managerial – how to keep innovators motivated and reward them? Others are organizational – how to decentralize R&D to tap the brains of our international staff? Many deal with intellectual property – how do we practice open innovation while maintaining our IP position? Others deal with strategic alliances and partnerships – how do we share the efforts and risks of new ventures with our partners? And there are many more issues. The question boards should ask is: Are we aware of the most acute issues that management faces as it steers the company’s innovation program? The board’s mission is of course not to interfere and become too deeply involved in these innovation issues. However, its mission is to keep informed and help the CEO and top management team reflect on their options. This is why it is essential to keep a short open agenda item – “innovation issues” – in board meetings with a specific innovation agenda. 

7) Do we expect management to conduct innovation audits?

Many companies embarking on a major innovation boosting program rightfully start with an internal audit and, sometimes, a benchmarking exercise against best-in-class competitors. Where are we deficient in terms of strategy, process, resources and tools? Do we have the right type of people in R&D and marketing, and do we tap their creativity effectively? Do we cover all types of innovation, i.e. not just new technologies, products and processes? Are our projects well resourced and adequately managed? Are they under control? How good is our innovation climate? These audits are extremely effective for highlighting priority improvement areas, and it is therefore good practice for the board to suggest that management undertake such audits and keep them updated. These audits will provide the board with a rich perspective on the company’s innovation performance issues.

8) Do we expect management to report on innovation performance?

This question is directly related to the questions on innovation goals (5) and innovation audits (7). Once innovation goals have been set and an audit conducted, it will be natural for the board to follow up and assess innovation performance. To avoid having to delve into too many details, innovation performance reviews should be carried out once or twice a year on the basis of a reasonably limited number of innovation performance indicators. Good practice calls for these indicators to cover several categories. A couple of them should be lagging indicators, i.e. measuring the current result of past efforts – the percentage of sales achieved through new products being one of them. A couple of others should be leading indicators, measuring the level of efforts done today to ensure future innovation performance – for example, the percentage of the R&D budget devoted to high risk/high impact projects mentioned above. One or two others should be in the category of in-process indicators – the most usual measure being the percentage of projects managed on schedule and on budget. Finally, it is always interesting to include a learning indicator to measure the reactivity of management and its ability to progress on key issues.

9) Do we know and occasionally meet our main corporate innovators?

Nothing conveys a company’s strong innovation orientation better than a visit by the entire board to the labs and offices where innovation takes place, both locally and abroad. Such visits, which are often carried out by innovative companies, have a dual advantage. They enable board directors to be aware of the real-world issues that the company’s innovators face, and they provide them with a good understanding of the risks and rewards of innovation. They also motivate the frontline innovators, who often lack exposure to top management.

10) Do we take innovation into account when appointing new leaders?

This last question is probably the most important. The nomination of a new CEO is undoubtedly one of the board’s most visible and powerful contributions to the company. It can herald a new and positive era for the company if the capabilities of the CEO match the company’s strategic imperatives. But it can sometimes lead to damaging regressive moves if the values of the new CEO are innovation-unfriendly. Management author Robert Tomasko notes that CEOs often fall into one of two broad categories: fixers and growers. The former are particularly appreciated by boards when the company needs to be restructured and better controlled. But fixers often place other values and priorities ahead of innovation. Growers are more interested in innovation because of its transformational and growth characteristics. This does not mean that boards should always prefer growers over fixers. There are times when companies require drastic performance improvement programs and an iron-handed CEO is needed. The board should, however, reflect on the impact the new CEO will have on the company’s innovation culture and performance. This is why it is so important to look at the composition of the entire management team. How many growers does it include and in what position? Will these senior leaders be able to counteract excessive innovation-unfriendly moves by the new fixer CEO?    

If you are interested in this topic, I suggest starting with Professor Jean-Phillipe Deschamps book Innovation Governance: How Top Management Organises and Mobilises for Innovation (2014)

Pandemic Pivots by Small Businesses

The COVID-19 crisis caused many businesses to make crunch decisions such as rapidly pivot offerings or building out new products/services. Often we hear stories of how big companies (e.g. Uber pivoting away from ride-sharing to food delivery) have done this (or not as the case may be), but rarely do we hear of pivots by small or local businesses.

In the course of research for my REIGNITE! 2020 Report which analysed strategic responses of 439 international organisations (large and small) around the world between March-June 2020, I came across many inspirational stories of incredible small business pivots.

In a recent speech to the NED Forum (slides here), I described the story of one particular business who had managed to turn crisis into opportunity.

To tell the story of a brilliant pandemic pivot by a small business, I’ve pasted the excerpt from the talk below:

Let me tell you a quick story about ABC Learning Company, based here in Gsy. Obviously that is not their real name but I came across them in some research I did during Q2 and lockdown. 

In the research which later became the REIGNITE 2020 Report – which I’ll introduce shortly – there was so much devastation across sectors including travel, hospitality, retail, construction, manufacturing, and so on. 

In fact 50% of the 439 leaders surveyed were in total despair, in terms of closures, restructuring, uncertainty and so on. 

However…there was a glimmer of hope!

About 10% of businesses were doing extraordinary things. They were using the crisis as an opportunity to reset, rethink, and reinvent. They were pivoting, quickly using technology to launch new offerings, testing new business models, and at the same time becoming more efficient, productive and reducing costs.

In terms of ABC Learning, it was a typical lifestyle business providing high school tutors, owned by one person with 5 tutors on the payroll. No online presence, web-site or anything. Business stopped overnight with lockdown, but by rethinking things quickly and using simple online and digital tools – google spreadsheets for CRM and bookings, zoom for delivery of live sessions, stripe for online or over the phone payments, the owner was not only able to quickly survive but doubled revenue during lockdown, hired 10 more tutors on contracts, and created a scalable solution which allowed for recorded training on-demand on popular topics. So better CX, more revenue and profits.

So what is interesting here is the combination of human psychology and business strategy during a crisis: so how did the leader reinvent whilst everyone was retreating, what can we learn, and how can we emulate this for our own contexts

This is what underpins today’s talk and certainly the REIGNITE 2020 Report which I’ll introduce shortly.


How To Create Winning Strategies That Reignite Human Potential, Adaptability and Creativity

Yesterday I gave a presentation to a NED Forum event sponsored by Investec. It covers a topic that I think is one of the most important issues for CEOs and Boards today who continue to grapple with the challenges of COVID.

The 3 key objectives for the presentation were to:

  1. Better understand what are some of the key and complex forces at play in organisations due to COVID
  2. How organisations can be more adaptable and resilient to future disruptive change
  3. And how to do this with more humanity using some best practices of a growing new breed of organisations out there

You can view the presentation here or below including the REIGNITE! 2020 Report:

The REIGNITE! 2020 Report

For those interested on more detail, below I have pasted in snippets of the talk including the Introduction.

Enjoy!

——

Hello and welcome everyone. Thank you to The NED Forum and Investec for the opportunity to speak here today. My name is Andrew Essa, and today I’m going to cover a topic that I think is one of the most important, if not THE most important, issues for CEOs and Boards today.

And that is:

Not just about turning this COVID crisis into an opportunity

Not just about where CEOs should focus, or where to invest

And not just about what winning strategies to implement to outmanouevure the competition

But more about HOW to do all of this in a way that is also more humane, more trusting and less bureaucratic, and in a way that can unleash the potential and creativity of people to have more impact and more fulfilling work lives

So we will aim to do 3 things here today:

  1. Better understand what are some of the key and complex forces at play in organisations
  2. How organisations can be more adaptable and resilient to future disruptive change
  3. And how to do this with more humanity using some best practices of a growing new breed of organisations out there

Slide 2 – Gary Hamel quote

  • So to bring this quote which I love and also my ‘fascination’ with this topic – I’ll tell you a quick story about ABC Learning Company, based here in Gsy. 
  • Obviously that is not their real name but I came across them in some research I did during Q2 and lockdown. 
  • In the research which later became the REIGNITE 2020 Report – which I’ll introduce shortly – there was so much devastation across sectors including travel, hospitality, retail, construction, manufacturing, and so on. 
  • In fact 50% of the 439 leaders surveyed were in total despair, in terms of closures, restructuring, uncertainty and so on. 
  • However…there was a glimmer of hope!
  • About 10% of businesses were doing extraordinary things. They were using the crisis as an opportunity to reset, rethink, and reinvent. They were pivoting, quickly using technology to launch new offerings, testing new business models, and at the same time becoming more efficient, productive and reducing costs.
  • In terms of ABC Learning, it was a typical lifestyle business providing high school tutors, owned by one person with 5 tutors on the payroll. No online presence, web-site or anything. Business stopped overnight with lockdown, but by rethinking things quickly and using simple online and digital tools – google spreadsheets for CRM and bookings, zoom for delivery of live sessions, stripe for online or over the phone payments, the owner was not only able to quickly survive but doubled revenue during lockdown, hired 10 more tutors on contracts, and created a scalable solution which allowed for recorded training on-demand on popular topics. So better CX, more revenue and profits.
  • So what is interesting here is the combination of human psychology and business strategy during a crisis: so how did the leader reinvent whilst everyone was retreating, what can we learn, and how can we emulate this for our own contexts
  • This is what underpins today’s talk and certainly the REIGNITE 2020 Report which I’ll introduce shortly.

Slide 5 – The Modern Org is Under Attack

  • So the modern organisation is clearly under attack from so many angles. 
  • The pace of change now is exponential and only will increase as further technological convergence happens through digital, AI, automation, analytics and so on
  • Today’s orgs look and feel very similar to how they have always been – command-control, top-down consistency, coordination and standardisation- which is the classic bureaucracy 
  • In US 1983-2019 the bureaucratic workforce – managers and overhead – has doubled in that time-frame VS growth of 50% in all other job categories
  • At same time productivity per OECD has gone down since them
  • Mental health, burnout, anxiety, stress, bullying, politics, discrimiation, harassment etc has skyrocketed 
  • Do we know anyone who is a leader, manager or worker and genuinely feels inspired, trusted, valued and engaged by their organisation every day??
  • We can’t afford it anymore!
  • So the question becomes, is it possible to build organisations that are big and fast, disciplined and empowering, responsive to market shifts yet resilient, efficient and entrepreneurial, and bold and prudent?
  • Many examples of new breeds of organisations successfully operating with 1/2 of bureaucratic load of traditional org
  • Case study – Buurtzorg (page xi)
    • Dutch firm Birdszaard home-health employers 16,000 nurses and home-carers with 2 line managers with a span of control of 1-8000!
    • They do this with dividing into small teams, give them the data they need to be self-managing, connect with a social platform to collaborate to solve problems and collaborate and share best practices, hold deeply accountable with P&Ls
    • Gives all the advantages of bureaucracy with control, consistency and coordination with no drag or overhead

On Digital Business:

  • Speed and scale: Digital and cloud has enabled adaptability at speed and scale;
    • The crisis has shown that rapid change at speed and scale is possible using digital and cloud in the short-term.
  • Increased adoption: Increased adoption of back-end cloud and front-end productivity tools, from e-signature to VC to MS365 to Dropbox etc
  • Effectiveness and benefits: Focus now on what is working, what isn’t, benefits realisation, productivity, efficiency, training, 
  • Complexity: So much going on…..managing capacity, cybersec, managing the complexity of the new IT estate, ensuring greater resource allocation with 2021 budgets, investments and leadership commitment to that 
  • Scaling and Transformation: The best firms – probably not many – are:
    •  firmly putting digital at the centre of corporate strategy
    • looking whether to build vs buy
    • aligning leaders on digital acumen so every CXO is a Chief Digital Officer for their function
    •  looking at wider opportunities for upskilling and digital adoption across the firm – so beyond infrastructure into more advanced worker productivity tools – automation, AI, analytics, superior Customer Experiences, New Business Models and Products/Services, Ecosystem Collaborations/Ventures
    • As well as more strategically, how to better organise and transform to become a digital business
  • Caution! Digital laggards will get left behind due to external forces and competitive intensity

On Trust + Safety:

  • So this is such a critical, complex and often overlooked dimension, mainly as it requires leaders to be empathetic and emotionally intelligent, and unfortunately many aren’t  
  • The BIG opportunity is that for the firms who get these complex dynamics right, will differentiate themselves from a talent retention and hiring perspective and become the new employers/brands of choice 2021+
  • But first we need to look at the state of play before COVID
  • In a nut-shell, there is very little trust, just need to look at amount of oversight, rules, policies, rule-choked processes and employees get this and know they aren’t trusted and even that their managers don’t think they are very capable
  • UK amount of discretion people have in jobs has been going down in last 20years
  • Only 1 out of 5 believe their opinions matter at work
  • Only 1 in 10 have the freedom to experiment with new solutions and methods
  • Most people can buy a car or house but same people in organisations can’t order a better £150 work chair without going through crazy internal hoops and hurdles
  • The way organisations are organised it is a caste system of managers and employees of thinkers/doers which causes disengagement of people from their work
  • Gallup surveys show only 20% of those highly engaged in their work – this is ALARMING so something needs to change
  • So against that backdrop you introduce a health and economic crisis of proportions never seen before, which impacts the human psyche in many different ways, and for most orgs you have a widening trust gap
  • Key impacts:
    • The “psychological contract” between employer/employee has also shifted for many
    • Traditional work assumptions have been challenged, firms must now not assume ‘old’ practices were the right ones
    • Acceleration of complex issues around safety, mental health, inclusivity, belonging, empathy, EQ, culture and behaviour, power dynamics, and expectations on leadership styles

An Interview With Gary Hamel

I recently listened to the Eat.Sleep.Work. Repeat podcast where Bruce Daisley interviewed Gary Hamel about his new book Humanocarcy. I posted about my excitement to recieve the pre-order of it here, and am really enjoying working my way through it.

If you are a leader, manager or worker in ANY job, this book (or notes below) is a must-read.

Whilst I rarely (well, never) take notes of the podcasts I listen to, after the first 5min it was clear I needed to capture the content. There was just so much unbelievable value Gary Hamel was providing.

And so the below represents my rough notes of that interview (which includes the below quote – so simple, yet so powerful):

Cannot assume that low-skill jobs means low-skill capabilities! – Gary Hamel

Enjoy!

What is the impact of COVID on the world of work?

  • Remote work and flexibility is possible, that will continue
  • Power moves to the periphery. Front-line people have had to use their ingenuity along with more freedom and autonomy so these people will not want to go back to traditional roles
  • Institutional and political resilience has come up short. Organisations are poorly suited to fast-moving, demanding problems and challenges beyond COVID such as racial injustice, income inequality, environmental change, automation impacts will need everyone to turn on everyone’s creativity

What is going on with the state of trust?

  • Yes very little trust, just need to look at amount of oversight, rules, policies, rule-choked processes and employees get this and know they aren’t trusted and even that their managers don’t think they are very capable
  • UK amount of discretion people have in jobs has been going down in last 20years
  • Only 1 out of 5 believe their opinions matter at work
  • Only 1 in 10 have the freedom to experiment with new solutions and methods
  • Most people can offered to buy a car or house but same people in organisations can’t order a better £150 work chair without going through crazy internal hoops and hurdles
  • The way organisations are organised it is a caste system of managers and employees of thinkers/doers which causes disengagement of people from their work
  • Gallup surveys show only 20% of those highly engaged in their work – this is ALARMING so something needs to change

What is the impact of bureaucracy?

  • A 1/3 of wage bill goes to managers, supervisors and administrators
  • A 1/3 of all hours/activities in organisations goes to bureaucratic tasks
  • In US 1983-2019 the bureaucratic class has grown by 200% (doubled) in that time-frame VS growth of 50% in all other job categories
  • It’s not about more regulation but the proliferation of new functions
  • At same time productivity per OECD has gone down since them
  • We can’t afford it anymore!
  • Many examples of post-bureaucratic vanguard of firms operating with 1/2 of bureaucratic load of traditional org
  • Dutch firm Birdszaard home-health employers 16,000 nurses and home-carers with 2 line managers with a span of control of 1-8000!
  • They do this with dividing into small teams, give them the data they need to be self-managing, connect with a social platform to collaborate to solve problems and collaborate and share best practices, hold deeply accountable with P&Ls
  • Gives all the advantages of bureaucracy with control, consistency and coordination with no drag or overhead
  • Can cut the bureaucratic drag by 50% would produce 10T gain in economic output across OECD (in UK £900B) and would double productivity growth rate over next 10 years
  • No other proposals on the table eg improving education, more incentives for capital investment
  • Economic reason, competitive reasons, social reasons as ethically the reason to do this

How do we get there?

  • Foundation for building a post-bureaucratic organisation is everyone thinking and acting like an entrepreneur, owner
  • Pre-Industrial era most owners/employees 4-5 people, all customer-focused and knew each other
  • As organisations scaled in line with Industrial revolution that was lost and no longer have the information to be self-organisation
  • Firms that do it e.g. Haier, Nucor ensure the front-line people have the information, skills, incentives, and freedom to think/act like owners
  • Still have to have coordination and tie the org together, instead of top-down it can be via collaboration
  • Some organisations have ESSP but that’s not what an owner – autonomy, right to make key decisions, right of participation in the financial upside of the business

Have we over-valued consistency and scale?

  • Bureaucracy invented to enable control and efficiency at scale with a top-down model
  • Replicability required to do things properly at scale
  • But that makes it very hard to change 
  • Control is important in most industries! 
  • But what else is important and what other ways to achieve it?
  • Orgs at heart are built to maximise control
  • Today we need orgs to maximise contribution with free to experiment, free to respond quickly to customer needs, free to solve local problems, not waiting for permission 
  • In bureaucratic model everything comes top-down which makes it hard to change fast
  • By the time an issue is big enough to attract CEO’s attention, often too late by then
  • E.g. Intel CXOs only would go after $1B Opportunities – but how do you know what is this at this scale? Only way is if someone else is already doing it i.e. not original, innovative. Nothing starts out as a $1B opportunity VS Amazon which experiments with all sorts of opportunities at different levels VS waiting for someone at the top to say ‘this is a strategic priority’ which will rarely happen

Experimentation is part of the new Org DNA

  • Pace which anything evolves is limited by the amount of experimentation that takes place e.g. humans today
  • Worrying that vast majority of employees say it’s virtually impossible for front-line employee to get a small amount of time and budget to try something new
  • More than ⅔ of employees say new ideas are greeted by hostility or skepticism 
  • E.g. central collaboration platform at a global tech retailer to share ideas and issues and real-time and treat the stores/orgs as a laboratory
  • Bezos says his goal is to build the world’s biggest lab, best place to create break-out success or fail with ideas vs if know it will succeed as have data it will likely be incremental innovation 
  • Intel hires goes through ‘Design To Delight’ programme teaching ‘design thinking, rapid prototyping, agile, experimentation’ 

Is the moment now a great opportunity to experiment?

  • We’ve had the tools/tech to enable remote working for over a decade 
  • Whilst tech becomes more available, also enables orgs to exert more control! Due to analytics. 
  • But data is not context and is historical 
  • We can assign every worker a detailed rulebook on what they need to do and somehow it aggregates into extraordinary performance. But does not reflect reality 
  • Battle of forces pushing decentralisation and autonomy and remotely, enabling lateral communications VS vertical challenging managers top-down
  • Same complexity to drive decentralisation is also pushing to exert control especially with the old guard 
  • One of the ways to ‘soothe’ a leader is to go to bed at night is that there is a policy to guide everything! I.e. squeeze the complexity of the chaos and world by creating appearance of uniformity and control but reality is far from it

The paradox of forces at play:

  • Consistency does matter – when I got to Apple store we expect certain things
  • But we do need this and creativity on the front-line with ability to tweak and change to make the real-time trade-offs
  • E.g. Nucor – unleashed the everyday genius of workers 
  • Tension between adaptability vs consistency 
  • Even if irreconcilable the eco value from scale is not what it used to be VS demand now for customised, personal experiences 
  • It will be a long slog
  • Over 70% say the prime way to get ahead is to be a good bureaucrat! i.e. horde resources, politics, climb ladder, attain positional power
  • But requires political challenge to redistribute power which no-one will like to do that 
  • System is working for anyone – workers, managers, leaders 
  • It all grows to accumulate power! We have to change that game 
  • Power needs to be fluid in orgs
  • If adding value people or a mentor or inspiring people will follow

What;’s happening in politics?

  • There’s a belief that the system is not working for them – income inequality, low wage jobs, equity
  • Workers treated like commodities, resources VS opportunity to use all competencies, skills, grow etc
  • Cannot assume that low-skill jobs means low-skill capabilities!
  • Stop talking about low-skilled jobs!
  • US Bureau of Stats – 70% low-skilled jobs are designed so people cannot use their originality 
  • Economically indefensible that we haven’t done more to given front-line people the opportunity to grow and use ingenuity

Can all orgs make this change away from bureaucracy? 

  • If you are a smaller business, what are the principles to hold scared as you grow the org
  • Founding principle – humanity vs bureaucracy 
  • From the start highly alert to the signs of bureaucracy to stay vibrant 

US Airlines example

  • Needed to kick-off some people to allow crew on
  • Staff did not have authority to offer correct incentives
  • Passenger carried off and became worst PR disasters ever
  • The CEO said workers did not have the procedures, guidelines, rules to use their own judgement! But it was the existence of too many rules that did not allow the local staff to use their own judgement 
  • Manual at UA is 60 pages VS manual at Southwest Air 5 pages

Haier Case Study

  • Hair Chinese domestic appliances
  • They wanted to build a network company
  • They divided 80k organisation into 4k micro-enterprises
  • All businesses had rights and flexibility akin to start-ups with significant incentives
  • Tied together with internal contracts for services e.g. HR or can go outside
  • Everyone’s performance – including internal contracts – is tied together on the success of the product in the market so everyone is aligned
  • Make it easy to start new businesses, if new idea post it online internally and others can join, Haeir can give you access to their VC network and they will co-invest and you can leverage the Haier network
  • Haier to make the journey redeployed 12k middle-managers to the micro-enterprises (or left), today three is 1 level between front-line and CEO, most firms have 8 levels

 

 

 

Digital Ecosystems, Tzars, Puzzle Pieces, & The Halo Effect

This week I have had numerous informal discussions with different business leaders about the digital potential of Guernsey in the context of a COVID world. It got me thinking.

What are the key ingredients of an efficient digital and innovation ecosystem? What are the key pillars? If I was Digital Tzar for a day, what would I focus on?

I immediately thought back to my own entrepreneurial journey starting in 2011 in Shoreditch (London) when I left Accenture Consulting & co-founded The Social Experiences Club, one of the first European experiences and activities marketplaces. Along the way and following an exit I have advised, mentored, coached and consulted to many other entrepreneurs, VCs and corporates on everything from new venture development to business models to fundraising to hiring and firing.

Below I have provided a list of some key ‘ingredients’ to an efficient innovation and digital ecosystem. They are like pieces of a puzzle. There can’t be one without the other. Whilst there are wider factors required for success (e.g. smart, collaborative and decisive government), these are not the focus here.

Key Ingredients Of An Efficient Digital and Innovation Ecosystem:

  • Innovation-I think the focus on ‘digital’ is too narrow. Perhaps the better conversation is around how to foster new ways of thinking, working and investing (in technologies, skills, institutions etc), and how to provide the right infrastructure for anyone or any organisation to be able to build new solutions and deliver benefit, value and prosperity for consumers/citizens.
  • Commitment + Vision As with anything in business or life, a strong vision and commitment to that vision is required to create impact and make change happen. For the public-sector, having a strong technology and innovation policy is critical, and was the foundation of Estonia’s e-Government transformation  Even with such intent and will execution will be hard enough, but without this and appropriate support, resources and political capital, nothing will change.
  • IT InfrastructureThe pandemic has shown how strategic this asset class is to the future prosperity of nations – and will continue to be – which may require regulators to rethink approaches to regulation and competition. Without reliable and quality connectivity and access for all people at a fair price today or in the near future (e.g. 5G, fibre etc), economic and social growth could suffer and could lead to catastrophic long-term consequences. On regulation, balancing the strategic interests of nations and the telecom providers (who all have very different corporate strategies, business models and operating structures) is no doubt a difficult but critical balancing act, especially in light of COVID’s acceleration of digital services, access and inequality issues, and continued and future investments in next generation infrastructure (e.g. 5G). 
  • Centralised Governance A centralised market-focused unit as the knowledge and resource ‘hub’ responsible for digital activity can provide benefits for an emerging innovation ecosystem, especially where aspects of the infrastructure might be lacking. London had TechCity, although it was arguably overshadowed by the power of the entrenched historic networks of the wider ecosystem in terms of universities, commerce, government, and investment community. 
  • IncentivesSmart technology and innovation tax policies is critical to facilitate a more efficient and attractive market to build the wider entrepreneurship and corporate innovation ecosystem.

Support for business R&D can help to foster innovation and boost productivity. Investment in new technologies can also be supported through more generous depreciation deductions or immediate expensing – OECD Report (2018) – Tax Policies for Inclusive Growth in a Changing World

Incentives (whether EIS, SEIS, tax-breaks or otherwise) can encourage and unlock local (and overseas) private and corporate capital flows into start-ups/scale-ups. In 2011 when I was raising funds for a start-up in London in 2011, everywhere we went investors, accountants and lawyers would immediately ask the same question: are you EIS compliant? Clearly the years following the 2009/09 Financial Crisis was a massive boon for innovation with a huge supply of entrepreneurs choosing new paths and supported by an abundance of capital. 

Since its inception in 1993 the Enterprise Investment Scheme (EIS) has enabled UK companies to raise over £16 billion in investments. Of the 3,470 companies benefitting from the EIS Scheme in 2015/16 alone, 1,645 companies were raising funds for the first time, between them generating £997 million of investment – Thomas Jenner LLP 

On the supply-side, facilitating a more efficient is needed to generate an increasing supply of entrepreneurs able to access capital (plus ‘smart’ capital) especially at early stages. For companies, encouraging the development of in-house IP via R&D tax credits (or similar) (UK HMRC policy is here) could also have downstream benefits such as up skilling (depending on the policy), and can be aligned with any national Digital Vision.

  • e-Government For smaller nations, it is especially critical to invest in citizen-facing automation (e.g. paper-less) and improved customer experience opportunities across social security, ID, e-voting, e-health, data, e-signatures, and EdTech. Often government is the largest employer in smaller communities hence these investments can have outsized impacts and benefits. It also ‘opens’ the government up to being more accessible, transparent, and helpful in working with and facilitating the wider ecosystem.
  • Ecosystem – One of the key reasons why London has been able to become a global leader in innovation (especially FinTech) has been due to the infrastructure and network effects facilitated by a number of key factors. In particular, within a 1hour train ride you have leading universities (e.g. Oxbridge, LSE, UCL, Imperial etc), commerce, and government. It creates enormous opportunities for creativity and collaboration to flourish, share knowledge, and build relationships with every piece of the start-up puzzle, from enterprise clients, to talent, to regulators and so on. As a start-up co-founder in Shoreditch in 2011, you could easily do nothing but network and attend amazing events, meet ups, hackathons, talks, pitch competitions etc  every night. Whilst not every city or small community can replicate that, the principles and practices are there to be examined and implemented within whatever your specific context is.

“We are witnessing a rapid changing of the guard for global investment in innovation centers. The US and Europe have traditionally been viewed as dominant forces in innovation and technology but Asia could soon surpass the US for number of innovation centers built and operated. Moreover it is clear that funding alone is not enough — the success or failure of any innovation center hinges on how effectively it taps into the surrounding ecosystem, and the role it plays in driving a broader corporate innovation strategy – Eric Turkington, Director at Fahrenheit 212, part of the Capgemini Group

  • Talent/Skills – Education is critical for the future of innovation in a society. At K-12, schools need to be offering introductory (and advanced) knowledge-based and/or practical courses on digital topics whether entrepreneurship, digital marketing, Excel/Google Spreadsheets, coding, design thinking, or analytics. This creates opportunities for ‘start-up clubs’ and business idea/pitch competitions aligned with industry, which can provide pathways for hiring and investors. Businesses should also prioritise up skilling which includes investing in softer skills (e.g. communication, creativity, collaboration, empathy).

“Twenty years from now, if you are a coder, you might be out of a job,” Cuban predicted. “Because it’s just math and so, whatever we’re defining the A.I. to do, someone’s got to know the topic. If you’re doing an A.I. to emulate Shakespeare, somebody better know Shakespeare”. – Mark Cuban

In addition, it is critical to learn new ways of working and thinking (e.g. agile, lean, design), and how to significantly improve inclusivity and diversity initiatives for existing talent (and future hires). At the higher education level, it is no surprise that some of the best known ecosystems (from Hollywood to Silicon Valley) have top-tier universities in close proximity. A centralised knowledge, teaching and research centre for technology and related skills and excellence must be a high-priority for any region without this. Also, making it easier or more flexible to hire overseas talent and plug skill-gaps in high-priority areas – whether software, analytics, UX or engineering – should also be considered, especially as this removes the friction for individuals or companies to pursue innovation.

  • Specialism It certainly helps to be known and famous for a certain speciality. London has done well to intentionally (or accidentally) carve out a ‘brand’ around FinTech which leverages the reputation, expertise and talent in that sector, although it is still active in many other sectors. This helps with the halo effect to build an ecosystem around that which then flows out into other areas. 
  • ExamplesThe halo effect above also extends to when there has been one or more successful start-ups and entrepreneurs who have moved though the start-up stages i.e. idea to exit. In a similar way that we celebrate sports stars and use them as aspirational icons for children and others, this can be used to inspire the next generation of entrepreneurs. If the right examples exist, we need to profile them and start holding them up examples of what can be possible (and using them as mentors).
  • Intellectual Property – Historically patents have been used a measure of R&D and innovation – and hence subject to tax breaks – but since 2000s software development has become a critical focus. Incentivising corporate investment into building out in-house IP vs using an overseas agency/service provider may provide local benefits and stimulate the local digital skills ecosystem.
  • Pathways Programmes for potential entrepreneurs whether at school or higher-education or post-university to educate prospective entrepreneurs. To be effective it requires all of these initiatives to be in place or in-flight
  • Collaboration – A critical digital ‘soft-skill’, without a collaborative approach and mindset amongst key participants – coupled with the strongest of commitments from smart government – attempts to develop and execute on a digital vision will struggle. This needs to be baked into any refreshed governance supported by strong top-down commitment.
  • Experimentation – Modern start-up development relies on many small experiments: start with a small hypothesis, test, learn, iterate, build, repeat. Government therefore needs to be more comfortable with this way of working to ensure progress is made versus spending years analysing and/or smothering creativity with bureaucratic processes which ultimately delivers nothing or very little. In the midst of an ongoing pandemic, unprecedented government spending, and a reduction in tax revenues, the Government must work differently and smarter in order to be more accountable to taxpayers and deliver benefit, value and sustainable progress for citizens.

 

 

BigTech Power, Regulation, And The Early Days Of The Internet

I recently came across a Guardian article looking at the winners and losers from last month’s US Congressional hearings into the power, practices and conduct of various ‘Big Tech’ companies. It got me thinking.

BigTech’s power and urgent need for regulation reminds me of a hot topic back in the early days of the Internet being….the urgent need for regulation.

In Australia during the early 2000s, the approach of business and government to the emerging Internet and associated applications tended to be driven by fear and uncertainty (“let’s sue them, shut them down, and take control of the IP” – major records labels in the music industry) as traditional legal and regulatory frameworks struggled to adapt to the new paradigm and business models began to creak.

Between 2000-2004, I was entrenched in these issues as I wrote and delivered a brand new undergraduate and post-graduate course at Queensland University of Technology called ‘e-Commerce law’.

At the same time, I was in private practice advising Australia’s biggest casino, media and other operators on how to navigate the emerging world of online gaming and meet the increasing demand of Australian consumers (who love to gamble).

Most topics in the course and in practice grappled with the issue of how do the traditional legal frameworks apply to this new technology and applications, from payments and money, copyright (e.g. music file-sharing), privacy (e.g. data protection), and reputation (e.g. defamation).

In 2004, I analysed the Governments prohibition of online casinos in my first academic article published in QUT’s law journal, titled The Prohibition of Online Casinos in Australia: Is It Working?’.

I’ve pasted the introduction here as in the context of the BigTech Congressional Hearings, a few points are still interesting:

Preliminary online research of consumer gaming activity was utilised to develop an assumption that [after 2 years of prohibition] prohibition is not working. A key reason for this is the futility of prohibition given the unique nature of Internet technology. This article will also critique Government motives for prohibition, as arguably, the best approach to deal with interactive gaming was not implemented. The relevant question for public policy appears to be not whether online gambling can be controlled, but the extent to which it can be controlled.

Obviously, 16 years on you can apply this principle to the other areas which BigTech have completely dominated including social media, search, video, browsing, advertising, e-commerce, web services, app stores, personal data, and so on. In the early 2000s, it was a nascent and emerging industry and overall regulation policy needed to be ‘light-touch’ (although exceptions existed especially where consumer harm risk was high, such as gambling, payments).

As converging technologies penetrated (Internet, broadband, OS software, mobile, apps, cloud etc), limited regulation has allowed a handful of companies control the majority of our online data, purchases, browsing habits etc. This will only accelerate given the impact of COVID on our behaviour, and soon that will extend in the last frontier of growth for such firms including health, education, government services, and so on.

Whilst regulation (and disposals or break-up) is clearly required for many different reasons (competition, national security, business and consumer harm etc), it is unclear what will play out given the power of these firms, how politicised the issues have become, and the nature of US anti-trust enforcement and law which historically focused on pricing practices and consumer harm.

In Chairman Cicilline’s wrap-up:

This hearing has made one fact clear to me. These companies as they exist today have monopoly power. Some need to be broken up. All need to be properly regulated and held accountable … their control of the marketplace allows them to do whatever it takes to crush independent business and expand their own power. This must end.

Something needs to be done. But we will have to see what happens after the Nov elections.

4 Major Post-COVID Megatrends

This week I came across a great report and visual from market intelligence firm Luxinnovation. It focused in on the major megatrends that will impact the economic recovery: digitalisation, sustainability, resilience and new business strategies (see below):

The study “Post COVID-19 Market Trends” is based on information from three sources:

  • National recovery strategies that have already been published by European countries, as well as the European Commission’s recovery plan and position papers issued by international organisations such as the OECD and the World Economic Forum
  • Technology and innovation market studies taking into account the impact of the COVID-19 crisis
  • Articles published by specialised press on topics related to current market trends in the post COVID-19 period

As the report aligns with recent research I conducted into strategic responses of a range of organisations across the world (REIGNITE! 2020 Report), I’ve summarised the key points below as highlighted by Sara Bouchon, Head of Market Intelligence at Luxinnovation.

On digital:

  • Even though the crisis brought some parts of the economy to a near standstill during the lockdown, it has strongly accelerated some trends, such as digitalisation
  • A large proportion of the workforce had to switch to remote working with almost no advance notice, for example, and many shops had to very rapidly start selling their products online
  • Digitalisation also turned out to be a success factor for some industrial companies with a high level of automation, which allowed them to continue producing even when the staff could not be present on site. This will speed up the development of the factories of the future that are based on Industry 4.0 principles

On resilience:

  • The huge impact of the current health crisis has raised people’s awareness of the potential consequences of a future climate-related crisis.
  • Many governments have recognised the need for a sustainable recovery and the opportunity to “build back better”, to use the words of the OECD
  • Recovery plans will include dimensions such as achieving the transition to renewable energy, shifting to a circular economy and rethinking food value chains to make them more local and environmentally friendly. There is also a will to invest in sustainable infrastructure
  • The ability to absorb and adapt to external shocks is vital, for countries as well as for companies and individuals. This crisis has highlighted vulnerabilities in the way our society functions of which we were not aware. It is essential that we work on lessons learnt and define what we can do to become more resilient.
  • A main focus in obviously on the healthcare system that is some places has been pushed to the very limits of its capacities. Other key issues include the building of regional supply chains, the development of new skills that help the labour force be flexible and agile, and ways to stimulate an inclusive democracy

On business strategies:

  • While businesses are now dealing with the severe short-term impacts of the crisis, many of them will have to reconsider their strategies in the post-crisis period, taking into account the “new normal” situation.
  • Some companies that adapted their production in order to respond to the urgent needs for disinfectants, face masks and visors, for example, are considering whether to stay in those markets or not.
  • Others, who changed their business model to offer online shopping or home deliveries, ask themselves the same questions
  • COVID-19 has been a strong driver of new forms of business innovation
  • New partnerships have been formed that would not have happened otherwise, and we can see much more of open innovation. This, in turn, challenges the current regulations of intellectual property as many innovations stem from cooperations involving several organisations
  • The health crisis has created new consumption and working habits, new needs to ensure that sanitary measures are being respected in offices, shops and other public areas, and new demands for entertainment in a context where large gatherings and face-to-face contacts are difficult. These are some of the areas in which we expect to see a lot of innovation in the near future.”

If you are interested in more context on the future implications of COVID, check out my recent report called REIGNITE! 2020 Report

Building Resilient Growth

The creators of Blue Ocean Strategy recently a wrote Harvard Business Review article called “How to Achieve Resilient Growth Throughout the Business Cycle

In it they address this fundamental question: How do you build growth and resilience, irrespective of the stage of the business cycle?

Below I summarise some of the key insight from the article:

Strategize like a market-creator

The authors Chan Kim and Renee Mauborgne argue that based on their 30 years of research, they have identified two types of strategy:

1.     Market-competing strategy, which focuses on beating rivals in existing markets, and

2.     Market-creating strategy, which focuses on generating new markets.

While both types of strategy have their role to play, companies pursuing market-creating strategies are not only better positioned to unlock a growth edge when economic conditions are favorable. They are also able to generate resilient growth during unfavorable economic conditions.

Red ocean and blue ocean strategies are not a binary choice. You need both. But while you’re already focusing on market-competing strategies, ask yourself how much of your focus is going to market-creating moves that generate the resilient growth.

red-ocean-vs-blue-ocean-strategy

How to build resilient growth

There are four actions companies take to best manage growth through market cycles:

1.     Focus on building a healthy, balanced portfolio of market-competing and market-creating strategic moves.

Both are important. While market-competing moves generate today’s cash, market-creating moves ensure tomorrow’s growth.

2.     Don’t wait for growth to slow to make market-creation a strategic priority.

Prepare in advance. You’ll be buffered by your market-creating move in a downturn cycle only when your market-creating move is already launched or set to launch. Don’t wait. Act now.

3.     Ensure your market-creating efforts are a core component of your strategy.

It shouldn’t be siloed into a function, effectively a side show. If you want to achieve market-creation you need to make it a priority.

4.     Remember, technology itself doesn’t create markets.

What creates new markets is the use of technology and whether it provides a leap in value to the buyer. Ask yourself: Is it linked to value innovation or not?

In a nutshell, the principles focus on both (i) leaders being aware and fully committing to exploring opportunities beyond the short-term and (ii) organisations being organised – or ‘building the muscles’ – through culture, systems, processes and talent to embed the focus on exploring and exploiting market-creating growth opportunities.

The late Professor Clayton Christensen and co-authors applied these theories to the prosperity and income inequality challenges the world faces and continues to face today with the book The Prosperity Paradox

This book and Blue Ocean Strategy is a must-read for anyone wanting to learn more about market-creating innovations. 

 

OneTrust: How A Privacy-Law-Compliance Tech Start-Up Became America’s Fastest Growing Company

Today I came across an incredible story of OneTrust, a privacy-law-compliance start-up based in Atlanta.

OneTrust landed at No. 1 on this year’s Inc. 5000, with more than $70 million in 2019 revenue and a staggering 48,337.2 percent three-year growth rate. It is among the global leaders in privacy-law-compliance technology with a suite of digital tools that gives companies a clearer view of all the user data they accumulate.

This enables them to comply with privacy laws, like the European Union’s General Data Protection Regulation (GDPR) which gives consumers greater control of how com­panies can use their data.

Whilst Enterprise B2B SaaS and analytics isn’t the most sexiest space, in many cases, firms that play there can be the fastest-growing, most scaleable and profitable (and do good things at the same time). 

In an age of Big Tech monopolies, increasingly intelligent AI and API-powered platform business models, growing regulatory oversight and appetite, and increasing consumer-awareness, OneTrust and others are clearly riding a tidal wave. 

Read the full story here 

 

 

Digital Playbook: How And Where to Focus to Maximise Opportunities In a COVID World

In summary, this article provides:

  • An 8-point playbook of strategies which leaders can use to focus time and resources to build digital capabilities and navigate business change
  • A useful framework to compare or evaluate existing digital investment and innovation initiatives to improve quality and impact
  • A useful article to share or use for internal discussions with non-digitally native executives, Board members and cross-functional teams
  • A set of practical strategies to guide implementation following on from the key insight and findings in the REIGNITE 2020 Report authored by Andrew Essa
  • A playbook to evaluate your digital progress and help plan for the future. Get in touch with any questions, comments or help to implement these perspectives here andrew@rocketandcommerce.com or at ROCKET + COMMERCE

The 8 strategies include:

  1. Understand current digital usage, productivity, value and benefits
  2. Diagnose and benchmark digital performance and opportunities
  3. Scale digital capacity for increasing demand but manage complexity
  4. Review and upgrade cybersecurity measures
  5. Move from ‘good’ to ‘great’ across 4 key areas
  6. Prioritise resource reallocation to digital initiatives (with a crisis mindset)
  7. Improve the digital acumen of the Board (and workforce)
  8. Organise to build digital capabilities

8 Strategies For Leaders to Navigate Digital Acceleration

Although some organisations are thriving on the back of tailwinds in this environment, many more are struggling. In many cases, the difference between the former and the latter is an organisation’s ability to rapidly adapt and chart a sustainable and differentiated path forward, especially through maximising Digital opportunities across areas including Customer Experience, Growth Strategy, Workforce Productivity, and Organisational Adaptability (I posted recently here about the 3 Big Digital Opportunities for Organisations)

Below are 8 playbook strategies for leaders to now consider:

#1 Understand productivity, value and benefits 

For most organisations, the critical first step has been to safeguard employees by enabling them to work remotely using the full suit of available tools (see below). 

hub---digital-workplace

As this continues alongside partial or even full reintegrations, firms should continuously engage or ‘pulse check’ with workers, customers and key stakeholders. It is critical to evaluate what is working well (e.g. feedback, analytics, usage), what is missing (e.g. cybersecurity, training, IT hardware), lessons learned, and where low-hanging fruit is for further digitisation opportunities and benefits (e.g. customer service and experience).

main-qimg-1e639c31c8722a6fa494676916d1199f

A challenge to overcome is that most firms typically fail to realise the full value from their technology investments for a variety of reasons (e.g. budgets, skills, governance, change, training etc). What tends to happen is some efficiency and cost reduction, but limited revenue generation, improved customer experiences and new products/services. The firms who out-perform their peers are the ones who prioritise and maximise the full potential of digital and are laser-focused on benefits realisation across the organisation. 

“The crisis has sped up the utilisation of tools such as Microsoft Teams for meetings, e-signature software and other tech which will assist both with internal and external customers moving forward. Typically face to face meetings or travel has been a big part of how we’ve conducted business particularly in my role in the past – Client Director, Private Investment Bank (interviewed in the REIGNITE! 2020 Report)

#2 Diagnose digital performance and opportunities 

For some SMEs, the current state of digital maturity involves a combination of accelerated back-end cloud, front-end software tools (e.g. MS 365), and new ways of working. Other larger, established firms however continue to have core (or hybrid) infrastructure set-ups based on outdated tools, processes, and assumptions combined poor digital acumen at leadership level and limited workforce training or up skilling.

This makes it increasingly difficult to adapt to new challenges (e.g. remote work, new services, cybersecurity), manage complexity, and properly reap the benefits of digital technologies. In some cases, the lack of agility will drag down the business which might be fighting to to rescue declining margins, compete, or even survive.

The challenge for leaders is to build on the momentum of change (‘it can be done!’) and increased adoption by leveraging the potential of digital across the entire organisation (not merely in pockets) for improved efficiency, productivity, customer experiences and new products/services.

To get started, leaders need to know what they are dealing with today.  If strategic planning around digital opportunities are to be robust and there is leadership intent to focus time and resources on the digital agenda, data and insight about the current digital state of the organisation will be needed.

Diagnostic surveys tools and assessments can help to evaluate an organisation’s digital and analytics maturity to discover digital growth, operational  improvement and worker productivity opportunities now, with recommendations on where to focus efforts for longer-term growth, change or productivity. 

At ROCKET + COMMERCE our Digital Performance Index (DPI) focuses on areas including Strategy, Customers, Analytics, Technology, Operations, Marketing, Offerings, People, Culture, and Automation. This data-driven, diagnostic approach helps CxOs and functional leadership teams to shape, refresh and align around a common vision and strategy across key digital and innovation dimensions.

We also critically incorporate human-centric approaches (see below) to our diagnostic tools which also provides people-focused data of digital change on users, customers, experiences, productivity, collaboration, skills, behaviours, trust, safety, belonging, health and well-being. 

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Read these brief case studies on how  at ROCKET + COMMERCE we have helped organisations do this and find new ways to go-to-market, become more customer-centric, launch new ventures, or pilot new up skilling programmes

This exercise also allows leaders to identify gaps between current capabilities and those of digital leaders (or the desired future state of the organisation), and plan a prioritised road map of tactical improvements or new strategic initiatives. This data-driven, diagnostic approach can also help CxOs and functional leadership teams align around a common vision and strategy across key digital dimensions. 

DMM_Model_Overview_2020

#3 Scale digital capacity for increasing demand but manage complexity 

Many IT teams are now grappling with providing sufficient capacity to serve the increased (and varying) volumes of traffic flowing through digital channels. One respondent to the survey (a provider of web-based collaboration tools), experienced a surge in demand from all of the newly remote workers and had to rapidly build out new infrastructure capacity to ensure availability.

This transition to digital channels will likely continue beyond the current health crisis as customers and organisations adopt fundamentally different ways of working. Recent research from Gartner indicates that about 41% of employees are likely to work remotely for some of the time post-pandemic. 

RemoteWorkStatisticsSource: Blackfog

The accelerated capacity build-out in H1 2020 has taken many forms beyond physical infrastructure deployment. In many cases, it has pushed organisations to adopt different architectural solutions for expansion, such as cloud bursting and augmenting on-premises deployments with virtual appliances and software-based deployments in the public cloud.

According to Mike Pelliccia, head of worldwide financial services technology solutions at Amazon Web Services (AWS), on-premises infrastructure no longer meets the business needs of today:

On-premises data infrastructures do not scale to meet variable and increasing volumes of data. Multiple disconnected data silos with inconsistent formats obscure data lineage and prevent a consolidated view of activity. Rigid data schemas prevent access to source data and limit the use of advanced analytics and machine learning. The high costs of legacy data warehouses also limit access to historical data.

The cloud helps organisations to harness the value of their data and aggregate it at speed and scale so that they can achieve their business goals. Traditional data solutions cannot keep up with the volumes and variety of data that is being collected today by financial players.

Pelliccia adds that a cloud-based data lake allows organisations – from banks to SMEs – to store all data in one central repository where it can be more readily available for the application of other technologies such as machine learning, “to support security and compliance priorities, realise cost efficiencies, perform forecasts, execute risk assessments, improve understanding of customer behaviour, and drive innovation.”

This enables organisations to maintain a holistic view of their business, while identifying risks and opportunities. For instance, analyses can help to detect fraud, surface market trends and mine for deeper customer insights to deliver tailored products and personalised experiences.

#4 Review and upgrade cybersecurity measures

Whilst many organisations will have robust cybersecurity processes and culture, for many others this will represent a new capability and massive learning curve. What was good just a few months or weeks ago may not be adequate today.

The urgency and impact of the shift away from office working will mean most organisations may have introduced new levels and types of cybersecurity risk not previously seen before at this scale (see below for leading causes of cyber risks).

bakerhostetler-causes-graph

Source: PropertyCasualty360

While allowing the workforce to be flexible is only a small part of digital transformation, it carries with it the need to ensure that new hardware (laptops, home printers, smartphones) and services have been, and continue to be, implemented securely (e.g. full disk encryption, enabling strong multi-factor authentication, and using VPN      technology).  

 #5 Move from ‘good’ to ‘great’ across 4 key areas 

Once solutions to immediate workforce and business priorities are in-flight, organisations should accelerate the exploring of different ways to use digital to work and operate, deliver innovative customer experiences, and create value in the new normal. For example, restaurants enabling entirely new in-home dining experiences, telemedicine becoming more of a norm, and different ways to shop with ubiquitous curb-side pick-up.

According to McKinsey, whilst many B2B companies have a general sense of what they need to do to become more digitally-enabled, it is the best B2B leaders who move beyond “accepted wisdom” to focus on being ‘great’ at 3 main differentiators of digital success:

  • Customer Insights
  • Process Improvement
  • Capability Building

To this list, I add a critical 4th dimension: Business Models 

The below provides further explanation:

Customer insights

  • Good: Focus on understanding their customer preferences and demographics.
  • Great: Ability to quickly translate into the most relevant value-creation strategies. Pick one or two high-value customer segments, then map decision journeys front-to-back to understand how customers buy, what channels they use, what turns them on—and off. More than 90 percent of B2B buyers use a mobile device at least once during the decision process, yet fewer than 10 percent of the B2B companies in the survey indicated that they have a compelling mobile strategy.

Process improvement

  • Good: Relentlessly improve existing processes.
  • Great: Use agile development techniques, automation, and design thinking to reengineer or reinvent supporting processes. Effective pre-sales activities—the steps that lead to qualifying, bidding on, winning, and renewing a deal—can help B2B companies achieve consistent win rates of 40 to 50 percent in new business and 80 to 90 percent in renewals. Incorporating agile techniques forces product development, marketing, sales, and IT to come together and use digital design practices, such as launching minimally viable products (MVP). That can ramp up the cultural changes needed as well.

Capability building

  • Good: Build important capabilities for digital initiatives
  • Great: Identify and augment the capabilities critical to achieving scale. B2B leaders create an organisational structure that supports their digital transformation. That involves identifying which skills need to be reallocated, what data and analytics resources are needed, and which customer opportunities require capabilities that need to be built, hired, or acquired. Systematic performance tracking needs to be in place to keep the efforts on track and make sure they having the desired impact (only one in five B2B companies systematically tracks digital performance indicators).

Business Models

  • Good: Optimise existing business model by digitising their traditional products, interfaces and distribution channels. 
  • Great: Take advantage of platform models and thinking leveraging network effects, intelligent AI-powered solutions, developer/API enablement and ecosystems, and customer-centric orchestration. As every sector digitises – accelerated by the COVID crisis – the imperative to incorporate new digital business models becomes more urgent. This underpins the ‘great’ executors. 

According to digital platforms expert Simon Torrence:

Platform thinking is about taking advantage of flexible software and digital  infrastructure to leverage, at scale, other economic actors (complementary third parties and/or developers) to create new value for customers and markets.Rather than trying to design and build everything yourself – which is the default for most companies today – platform thinking encourages you to act as a coordinator or enabling intermediary between the needs of your customers, your own expertise and the expertise of others.

Simon goes on to say that:

Incumbent leaders admire and fear the big tech giants, and would love to emulate or incorporate some of their ‘secret sauce’ into their own businesses, but don’t know how. They have been happy to invest large sums to digitise their existing business model and fund experiments, pilots and CVC investments in new areas, but have found it difficult to fully embrace the types of digital business models that work best in a hyper-connected world and to take bold steps in re-allocating meaningful levels of capital and resources towards them.

In summary, a commitment to “great” is really what allows companies to reap the rewards from digital and build digital and supporting capabilities. Without it, organisations will find their improvements provide only modest benefits that cannot be scaled.

#6 Prioritise resource reallocation to digital initiatives (with a crisis mindset)

As outlined above, the COVID crisis will accelerate the gap between digital laggards and transforming leaders requiring firms to now evaluate investments, baseline ‘digital maturity’, and in the short-term, secure a stronger, repositioned role for digital investments in 2021. 

In fact, in 2019 McKinsey believed a ‘crisis mindset’ was required. And that was before COVID….

1-920x1024

This is likely to require an urgent reallocation of resources. Although most senior executives understand the importance of strategically shifting resources (according to McKinsey research, 83 percent identify it as the top management lever for spurring growth— more important than operational excellence or M&A), only a third of companies surveyed reallocate a measly 1 percent of their capital from year to year; the average is 8 percent. 

This is a huge missed opportunity because the value-creation gap between dynamic and drowsy reallocators can be staggering. A company that actively reallocates delivers, on average, a 10 percent return to shareholders, versus 6 percent for a sluggish reallocator. Within 20 years, the dynamic reallocator will be worth twice as much as its less agile counterpart—a divide likely to increase as accelerating COVID impacts, digital disruptions, and growing geopolitical uncertainty boost the importance of nimble reallocation. 

The disconnect tends to be because managers struggle to figure out (and agree) where they should reallocate, how much they should reallocate, and how to execute successful reallocation. Additionally, disappointment with earlier reallocation efforts can push the issue off top management’s agenda.

Although these challenges can be overcome, feedback and data from employees, customers, and the maturity benchmarking should help to align senior management commitment to prioritising the short-term digital investment requirements, and at the same time laying the foundation for more detailed discussions and analysis for longer-term strategic planning. 

#7 Improve the digital acumen of the Board (and workforce)

 A UK government report published in 2016 found that the digital skills gap is costing the UK economy £63 billion a year in lost GDP. Similarly, a report from Amrop, a global executive search firm, reveals that just 5% of board members in non-tech organisations have digital competencies, and that the figure has barely moved in the last two years.

In the new COVID world requiring adaptability and digital adoption at a scale never seen before, boards must get to work in reassessing competencies, adopting new ways of working (e.g. continuous strategic planning, collaborating internally and with the wider ecosystem), and being open to hiring diverse backgrounds if needed. 

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In addition, since many new digital directors may have atypical perspectives (e.g. deep technical vs product vs strategy vs HR), companies must make sure that they have strong on-boarding processes in place, to capture and maximise the impact of their new board members.

A critical first step is to ensure a consistent understanding of what digital and innovation means amongst leaders and boards, what are the best practices of leading tech and non-tech organisations, and what are the big opportunities for digital (and threats) in a COVID world. As part of this, improving the board’s understanding of the external environment and how it is shifting, and how the big trends and signals might impact the immediate and longer-term future. 

In many cases, firms will need outside help across recruitment (e.g. diversity), training and education (e.g. research and insight, best practices, benchmarking), advisory, and briefings from experts, entrepreneurs, academics, and other ecosystem players. 

Once the above happens (which in theory can happen quickly with committed leadership), this should provide the intent and focus to refresh strategic plans and budgets, and then roll-out or accelerate digital and innovation upskilling throughout the wider workforce as a strategic priority.  

#8 Organise to build digital capabilities  

Put simply, digital capability can be defined as doing everything it takes to develop an organisation and workforce able to:

  • Maximise the potential of technology, data and talent to address business challenges; and
  • Ability to respond quickly to continual shifts in consumer behaviour and external environment in a fast-changing connected world.

According to recent study by Deloitte involving interviews with industry leaders, achieving this is not easy as the survey had a multi-faceted response. However, organisations that have successfully adapted to this new environment typically make delighting the customer their #1 priority, set bold goals to achieve factors of 10x impact, and challenge the status quo by looking for new ideas to solve.

3 core critical success factors to building digital capabilities:

Leadership:

In these times of significant change, leaders must understand, collaborate, and champion the exciting potential of technology from the very top of the organisation.

However, understanding the full suite of digital opportunities (e.g. API-based BaaS platforms) are often new and alien to leaders of incumbent firms. Teams and advisers need to help them to understand how digital can work, and the options in terms of where to play and how to win. This is critical to getting commitment to re-allocating sufficient capital and resources from other initiatives to support this market opportunity in a meaningful way.

Organisational Structure and Operating Models:

Organisations need to embed and build the right structures and models that allows them to drive digital change and execute in an agile way.  This requires clarity on the firm’s approach to digital strategy (e.g. build vs buy vs partner) as the implementation approaches to build digital capabilities will differ.

For example, many established firms will embark on dual-transformation or innovation portfolio approaches by

(i) executing process improvement and cultural change in the main firm (see ‘A’ below)

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(ii) creating separate legal entities, JVs and alliances to tackle new markets, exploit new business models, sometimes at the risk of cannibalising the main business (see ‘B’ above or ‘Exploit’ below)

82247d19-8db0-4050-8831-d4ec50b39f43.__CR0,0,300,300_PT0_SX300_V1___ (1)

03-Chart-ExploreExploitContinuum

Source: Strategyzer

PingAn has pursued the above approaches to become one of the best-performing transformer of the past decade (and become a much sough-after MBA case study subject). It typically kick-starts new ventures with partners as part of the ‘explore’ portfolio which is one of the most effective approaches to reducing risk and increasing chances of success.

Typically these are best managed away from the core in an ‘explore’ portfolio of businesses within a new organisational structure and P&L. 

Talent, Skills, Culture and Data:

Maximising digital opportunities require radically different skills, technologies, ways of working, and metrics. Organisations need to empower people to be creative, test and learn and challenge existing ways of working. They also need to cultivate diversity and a lifelong learning mindset, recognising that many will resist change. This was highlighted in PwC’s recent Skills Report.

In addition, whilst the focus of the ‘future workforce’ tends to focus on the technical and ‘hard’ skills (e.g. engineering, analytics, coding etc) it is the soft skills and humanities expertise which will gain increasing importance.

Screen Shot 2020-08-21 at 10.56.33

According to billionaire tech entrepreneur Mark Cuban:

“Twenty years from now, if you are a coder, you might be out of a job,” Cuban predicted. “Because it’s just math and so, whatever we’re defining the A.I. to do, someone’s got to know the topic. If you’re doing an A.I. to emulate Shakespeare, somebody better know Shakespeare.” Cuban acknowledged the importance of coding as a short-term opportunity. Long-term, however, the Shark Tank investor pointed out that A.I. is only as good as the data it’s given–meaning the highest-skilled workers in the future will be the ones who can identify “what is right and what is wrong and where biases are.”

Already today design thinking and human-centred design is a new differentiator in digital which complement technical mobile, cloud, AI, and other more technical digital skills.

“Creativity, collaboration, communication skills: Those things are super important and are going to be the difference between make or break” – Mark Cuban

In terms of data (the new ‘oil’) organisations need to capture, track, protect, analyse and maximise the business value of their data, as along with people, this is the most valuable asset.

Some further tactics might include:

  • Senior executive and board training, commitment and refreshed digital strategies 
  • Centralising digital business expertise (e.g. Centre of Excellence) using hub-and-spoke engagement model 
  • Hiring a Chief Digital Officer and team/function
  • New talent and up skilling (e.g. analytics, user experience)
  • Hiring external, flexible talent e.g. freelancers
  • Cross-functional governance
  • New incentives and behaviours
  • Collaborating with wider industry and ecosystem partners
  • Training will be integral which will also enable every C-level executive to be their own ‘Chief Digital and Innovation Officer’ for their functions.

Accenture summarise this using an 8 step ‘playbook’ below:

Accenture-Change-Leader-Digital-Economy-ThumbnailWhat’s next?

To better understand these issues further or explore our range of digital business advisory offerings, get in touch here andrew@rocketandcommerce.com or at ROCKET + COMMERCE

Behind The Buzzwords Podcast: Disruptors

The business world is famous for jargon and phrases that become so overused they soon become meaningless. ‘Disruptors’ is one of these words, and is explained from different perspectives in this great podcast episode from BBC called Behind The Buzzwords.

I came across the term ‘disruptive technologies’ in the early 2000s after reading The Innovator’s Dilemma by the late Professional Clayton Christensen. I ended up using some of his theories to help me with major research project analysing what was going on with the record labels and retailers in the Australian music-industry as online P2P file-sharing emerged and began to ‘disrupt’ the physical music business model. 

Interestingly, the perception of ‘disruption’ was subjective. For the small indie labels and artists, digital music was a new opportunity to reach new audiences. For the major labels, it was perceived negatively as a threat, especially as no legal services existed. It was the same with music retailers. 

This podcast explores these fascinating issues further in the context of 20 years on. It is well worth a listen. 

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