Sequoia Capital’s 52-Page Deck on the Market Downturn

We do not believe that this is going to be another steep correction followed by an equally swift V-shaped recovery like we saw at the outset of the pandemic.

Sequoia Capital

Sequoia Capital is infamous for its memos and presentations it shares with its portfolio companies during macroeconomic crises (“R.I.P. Good Times” was for 2008; “Coronavirus: The Black Swan of 2020” was another).

Its latest warning, which was shared with 250 founders on May 16th, was called “Adapting to Endure.” In other words, don’t expect a recovery from the current market downturn to happen quickly.

Over the years, Sequoia, the venture firm behind Google, Apple and Airbnb, has developed a reputation as the tech industry’s POV Master, through memos and presentations that it shared with the leaders of its portfolio companies during past macroeconomic crises.

In 2008, that took the form of a 56-slide survival guide to the Great Recession, entitled “R.I.P. Good Times.” In early 2020, as the pandemic began upending the economy, Sequoia sent its founders a grim memo entitled, “Coronavirus: The Black Swan of 2020.”

Its latest warning to its portfolio companies takes the form of a 52-slide presentation where:

  • Sequoia describes the current combination of turbulent financial markets, inflation and geopolitical conflict as a “crucible moment” of uncertainty and change;
  • Sequoia told founders not to expect a speedy economic bounce-back akin to what followed the start of the pandemic because, it warned, the monetary and fiscal policy tools that propelled that recovery “have been exhausted.”
  • The firm suggested founders move fast to extend runway and to fully examine the business for excess costs. “Don’t view [cuts] as a negative, but as a way to conserve cash and run faster,” they wrote.

You can view the deck here and it is worth a skim to see what a top-tier Silicon Valley VC thinks about the current macro climate.

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.

The 12 Core Principles for Legal Operational Excellence

Management consultants whether McKinsey, BCG or Accenture have made an industry out of identifying best practices and applying to specific company challenges.

Although most in-house legal and compliance departments have remained immune from this for many decades, the tide has been turning for some years now with many legal departments building out higher-performing teams, operations, and services. Leveraging best practice insight – from across all sectors not just legal teams – has been a key ways to support this.

One of these tools is the ‘Core 12’ from the Corporate Legal Operations Consortium:

“While every company and team has its own unique needs, the guidance in these functional areas – known as the “Core 12” – applies to many environments and requirements towards operational excellence”.

The Core 12 can be seen below:

Essentially these are the operations, services or capabilities which define the legal function. CLOC provide more context below:

“Legal operations” (or legal ops) describes a set of business processes, activities, and the professionals who enable legal departments to serve their clients more effectively by applying business and technical practices to the delivery of legal services. Legal ops provides the strategic planning, financial management, project management, and technology expertise that enables legal professionals to focus on providing legal advice.

The Core 12 allows any legal department leader or 3rd party consultant to assess their current state of performance maturity, map it to the ideal state, and then decide and plan what are steps they wish to take to improve which makes sense for their specific context and constraints.

The last aspect is critical as the Head of Legal in a Series A-funded start-up will have completely different challenges, requirements and objectives to a Fortune 100 legal team.

When selecting one of the 12, you can deep-dive further into that area of competence. For example, with Technology, CLOC provide the following high-level (and non-exhaustive) detail to help understand what good generally looks like:

TECHNOLOGY: Innovate, automate, and solve problems with technology.

Current reality: Teams often rely on manual, time-consuming, and fragmented point solutions. They may lack an overall technology vision and are deploying costly applications that are underused and disconnected from the team’s workflow.

Desired state: Create a clear technology vision that spans all of the needs of your organization. Automate manual processes, digitize physical tasks, and improve speed and quality through the strategic deployment of technology solutions.

  • Create and implement a long-term technology roadmap
  • Incorporate connected tools for e-billing, matter management, contact management, IP management, e-signature, and more
  • Automate repetitive or time-consuming manual processes
  • Determine where to build and where to buy
  • Evaluate new vendors, suppliers, and solutions
  • Assess emerging technology capabilities and incorporate into your long-term strategic planning
  • Structure an effective partnership with your corporate IT team

Although the CLOC 12 isn’t of itself a useable tool as far as detailed diagnostic, business analysis or benchmarking is concerned, it does provide a helpful introduction for legal leaders looking to learn more about what good looks like in terms of legal operations and capabilities.

CLOC have a download guide with more information on the Core 12 which you can access here

Management of Portfolios (“MoP”)

Today I sat (and passed) the MoP Foundation Exam run by PeopleCert on behalf of AXELOS. I’ll do the final Practitioner exam next week. I bought the on-demand training via SPOCE, a UK training firm specialising in project management (“PM”) certifications such as PRINCE2, Agile, MSP etc.

Although I’ve had over 15 years experience with PM (including courses in PRINCE2, ITIL), it has been an extremely worthwhile exercise to build and consolidate knowledge on best practices around managing change portfolios.

For those not familiar with portfolio management, it helps organisations to make better decisions about implementing the right changes to their business as usual (BAU) activity via projects and programmes.

The Management of Portfolios (MoP®) guidance provides senior executives and practitioners responsible for planning and implementing change, with a set of principles, techniques and practices to introduce or re-energize portfolio management. MoP helps organizations answer the fundamental question: Are we sure this investment is right for us and how will it contribute to our strategic objectives?

In my experience – and supported by many studies and anecdotal evidence – most change initiatives tend to fail or not realise intended benefits. There are many reasons for this but certainly high-performing organisations invest in the right initiatives and implementing them properly.

In other words, such organisations do the right things, and realise all the benefits.

The Practitioner Exam next week will be significantly tougher than the Foundation. I better get back to studying.

8 Areas of Leadership Focus In Times Of Ongoing Disruption

In July last year I published a research and later and an eBook called REIGNITE! From Crisis To Opportunity In A COVID World. In light of a recent lockdown where I live (Guernsey) I thought it worth reflecting on what I wrote back then. To help I’ve pasted an infographic containing 8 areas where leaders should focus to rebuild their organisations.

Six months on and most (if not all) recommendations still remain, from prioritising digital investments, pushing ahead with smarter working policies, and leading with empathy. Whether or not organisations have implemented some or all of these is likely to be another story.

RIP Tony Hsieh

I first came across Tony Hsieh when I read his book Delivering Happiness soon after it was published in 2010. I remember immediately being captivated by his story as a scrappy but ultimately successful tech start-up founder, and then as an early investor and employee at ShoeSite (later Zappos).

There he focused on people and tested ‘radical’ management concepts such as:

Pay brand-new employees $2,000 to quit
Make customer service the responsibility of the entire company-not just a department
Focus on company culture as the #1 priority
Apply research from the science of happiness to running a business
Help employees grow-both personally and professionally
Seek to change the world
Oh, and make money too . . .

Aside from these techniques which helped propel Zappos into the hands of Amazon for $1B+ , the bigger impact for me was how ‘simply’ he was able to communicate in the pages of the book. There was a real ‘humanity’ with the way he wrote which was in stark contrast from most other best-selling leadership and business books of that era (e.g. Jack Welsh).

You got a real sense that the author really cared about using business as a means to do good, and make money for not just himself but colleagues and investors. I later learned that he deployed significant amounts of his wealth into various regeneration and gentrification projects around Las Vegas (according to various reports, some were successful, others not so much).

The world of entrepreneurship is certainly worse-off with Tony’s loss.

For more context on Tony’s life and the impact he had, this NY Times obituary is well worth a read.

RIP Tony.

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)

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

The Power of Language To Communicate Strategy & Change

I used this slide at a presentation yesterday.

For me its purpose was to contrast current/future states and link to best practices.

However one of the participants (Banking senior executive) said he loved how it simply showed how powerful ‘language’ can be to communicate a new strategy, initiative or change.

He said they have been stuck for years using the same old terminology from the ‘old’ column.

This was brilliant.

An unexpected but simple example showing the power of fresh #perspectives #diversityofthought #customerdevelopment #userfeedback

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

 

 

 

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. 

 

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)

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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

119 Worst Business Buzzwords for 2020

Yesterday I posted about a new BBC podcast looking at the history behind this buzzword: Disruptor.

I since came across a list of 119 of the worst business buzzwords in 2020 (thanks to TrustRadius).  Check them out below.

The 119 Worst Business Buzzwords for 2020

  1. Synergy
  2. Think outside the box (and other variations, like “step out of the box,” an “out of the box” idea, etc.)
  3. Take it offline
  4. Circle back
  5. Low-hanging fruit
  6. At the end of the day
  7. Cloud, and cloud-based
  8. To not know what you don’t know
  9. Big Data
  10. Move the needle
  11. Leverage
  12. Agile
  13. Best Practice
  14. Digital transformation
  15. Deep dive
  16. Bandwidth
  17. Customer journey
  18. Moving forward–and its close cousin “going forward”
  19. Next level, up-level, level up
  20. Reach out
  21. Touch base
  22. Wheelhouse
  23. Disruptor
  24. Alignment / Aligned
  25. Right
  26. Bottom line
  27. Acronyms (FYI, ROI, KPI, etc.)
  28. Disruptive
  29. Value (as in value-add, driving value, value proposition, corporate values, or value drop)
  30. Ping
  31. Lean, and lean-in
  32. Paradigm (as in paradigm shift or breaking the paradigm)
  33. Partner–the verb (“Partner with us”) and the noun (“Business partner”)
  34. Ideate / Ideation
  35. Ask, used as a noun to mean “request”
  36. Learnings
  37. Holistic, especially in the phrase “Holistic approach”
  38. Culture (as in “company culture,” “corporate culture,” “startup culture,” or “creating a [inset adj. here] culture”)
  39. Thought leader / Thought leadership
  40. Content (whether “Content is king” or “snackable content”)
  41. Growth hacking (which is essentially just marketing)
  42. Buy-in
  43. Pain point
  44. Swimlane, or even just “lane,” particularly when someone is telling you to stay in yours.
  45. Best in class / Best of breed
  46. Game-changer
  47. Teamwork, team-building, and team-players
  48. Next-gen
  49. Hard stop
  50. ROI (“Return on investment”)
  51. IoT (“Internet of things”)
  52. Innovative
  53. Influencer
  54. Single pane of glass
  55. Customer-centric
  56. All hands on deck
  57. Net-net
  58. Put a pin in it
  59. Stakeholders
  60. Strategic
  61. Metrics
  62. Machine Learning
  63. Pivot
  64. On the same page
  65. Advertainment
  66. Collaboration
  67. Intelligence, whether it’s “artificial intelligence,” “business intelligence,” “emotional intelligence,” “market intelligence,” “competitive intelligence,” or otherwise.
  68. Automation
  69. Blockchain
  70. Intuitive
  71. Analytics
  72. Platform
  73. Open the kimono
  74. Unpack
  75. Giving 110%
  76. Tables of all sorts: table stakes, bringing something to the table, or tabling it for later
  77. Quick win
  78. Onboarding (and “get everyone on board”)
  79. Scrum
  80. Boil the ocean
  81. Story (in context of “storytelling,” “user stories,” or making a “long story short”)
  82. On your plate, or having a “full plate”
  83. 30,000 ft. view, 10,000 ft. view, and other escalations of a top-down view
  84. Core competency / Core capabilities
  85. Rockstar
  86. Loops: “looping back,” keeping someone “in the loop,” or the dreaded “feedback loop”
  87. Free, and even worse, freemium
  88. Blue sky
  89. Integration
  90. Engagement
  91. Actionable
  92. Efficiency
  93. Socialize
  94. Diversity
  95. Verticals
  96. Bio-break
  97. Bleeding edge
  98. Optimize
  99. Scalable
  100. Organic
  101. Omni-channel
  102. Empower
  103. Win-win
  104. Optics
  105. DevOps
  106. Data-driven
  107. In the weeds
  108. Double click (as in to “double-click” into something)
  109. On your radar
  110. Ducks in a row
  111. Drill down
  112. Space (as in “playing in” a particular “space”)
  113. Fast in various forms, such as “fast-paced,” “fail fast” or “cheap, fast, and good”
  114. Top of mind, mindfulness, and mindshare
  115. KPI (“Key performance indicator”)
  116. ASAP (“As soon as possible”)
  117. Giving back your time
  118. Per (“per se,” “per my last email,” etc.)
  119. FYI (“For your information”)

Humanocracy: Creating Organisations As Amazing As The People Inside Them

It is rare that you come across a business book that makes you scream “YEEEESSSS!” when you haven’t even read it yet. In fact, I don’t think that has ever happened to me before.

Just a few words in the blurb from author Gary Hamel did it for me:

“Our organisations are failing us. They’re sluggish, change-phobic, and emotionally arid. Human beings, by contrast, are adaptable, creative, and full of passion. This gap between individual and organisational capability is the unfortunate by-product of bureaucracy–the top-down, rule-choked management structure that undergirds virtually every organisation on the planet” – Gary Hamel, management guru and author of Humanocracy

humanocracy-cover-2x

This quote, COVID-19 and first-hand experience of these issues over the past 20 years provided the inspiration for me to want to better understand what is going on inside large and small organisations around the world across 15 dimensions including leadership, strategy, culture, processes, and technology.

This led to a multi-month project producing the REIGNITE! 2020 Report, numerous new tools and frameworks including the COVID Response Index (CRI) and REIGNITE! FLYWHEEL, a forthcoming ebook (wait list here), and new set of offerings at REIGNITE! Global. 

I doubt Gary Hamel realises what he has started and the impact he is going to have with this book. Actually, he probably does.

Humaocracy is out soon and on pre-order now. Obviously, I have signed up. Book review to follow in September I think.

#covidresponse #covidimpact #leadership #strategicresponse #organisationalbehaviour #organisationalchange

Google Home Working Until July 2021

After I saw the Google announcement in the NY Post I posted this comment on LinkedIn and Twitter earlier today:

“Big tech tend to be the test bed for new HR practices although many do not go mainstream. Even with the pandemic I still don’t think this will hit mass market either mainly due to powerful old school bureaucratic orgs, entrenched work practices, and many baby boomer leaders holding on for control”.

As a glass-half-full-guy I hope I am wrong here, but having worked in and consulted to many large and small organisations on almost all continents, I can’t see a majority of businesses following suit.

It will be fascinating to track what happens on this issue (and all other organisational behavioural) issues over time.

 

 

The CEO Gig Has Now Become 100x Tougher

COVID-19 has brought with it a pressurized operating environment the likes of which few of today’s CEOs have ever experienced—it has “unfrozen” many aspects of the CEO role.

I came across a new article from McKinsey today which I could have summarised in 7 words: The CEO Gig Has Now Become 100x Tougher.

It is worth a read but beware as if you are an aspiring leader it may put you off from your ambition to descend to the top job.  The article focuses on the need for leaders to make 4 major shifts:

  • Aspire 10x higher
  • Show up every day with humanity
  • Fully embrace stakeholder capitalism
  • Harness the power of P2P networks

I’ll have a wild guess and estimate that 1 in 10 leaders will make the full shift, 3 will intentionally try, and maybe 1-2 will have no choice but to try.

“When the pressure decreases, will CEOs go back to operating as they did before? Or will the role at the top be thoughtfully reconsidered and reconceived by those who occupy it? Clearly, not every CEO will choose to make permanent the four shifts we’ve discussed. The more that CEOs do, however, the more the moment has the potential to become a movement—one that could create higher-achieving, more purposeful, more humane, and better-connected leaders” – McKinsey

It will be very interesting to see what happens over time, and which way leaders go.

 

The Post-Crisis World of Work With Adam Grant

As people and businesses plan for pandemic recover and rebuilding, experts such as organisational psychologist Professor Adam Grant of Wharton are a great source of inspiration.

He gave a recent interview with Ross Chainey at European Business Magazine which provided a tonne of insight into the future of work in light of the ongoing crisis.

It was so good that I had to provide an edited transcript of the conversation below. Enjoy

First and foremost, this is a global health and economic crisis. But, for many millions of us, we’re battling a loss of normalcy in our daily lives. How well-prepared do you think we are to deal with a situation like this? Does it play to any of our natural strengths or is it more likely to expose our weaknesses?

It’s a little bit of both, like everything else. The challenging part is, as human beings, we don’t like uncertainty and unpredictability. There’s even some evidence that if you’re highly neurotic, you actually prefer experiencing pain over being in the dark about what you’re going to experience. That’s a part of the crisis that’s really a challenge.

On the flip side, we’re highly adaptable. Darwin wrote when he was building his theory of evolution that natural selection favours a sense of flexibility. It’s not always the strongest species that survives; it’s sometimes the most adaptable.

I think one of the ways we can cope with the uncertainty is: when you can’t imagine the future, you can actually rewind and think more about the past. You can recognize hardships that you’ve faced before. You can learn something from the lessons of your own resilience and then try to figure out “what did I do effectively before that might work for me today?”

I still hear a lot of people complaining about FOMO – the fear of missing out – even though there’s nothing really going on. Has COVID killed FOMO or exacerbated it?

I prefer to think about this less in terms of FOMO and more in terms of what’s often called JOMO, which is the joy of missing out. I actually made a list of all the things I’m thrilled that I don’t have to do, and that includes changing out of sweatpants [and] having to commute.

This is a practice that’s pretty useful for people. We have a lot of evidence that marking moments of joy can actually create those moments of joy because we’re more likely to notice them. We’re more likely to savour and share them. Being able to capture a few things that are really joyful about getting to stay home seems like a productive step.

We’re all separated from our teams. How can we maintain a sense of belonging while isolated at home?

I don’t know that it’s easy. In one company, they did a virtual tour of their home offices. That gave them the chance to talk about some of the mementos that they keep nearby. They were showing off pictures that their kids drew for them. And it was a great moment of personal connection in a way that never would have happened if everyone was in the office.

I’m not suggesting that’s the perfect fit for everyone, but it seemed like a small step that can make a meaningful difference in feeling like I learned something new about my colleagues, [that] I see them more as human beings as opposed to just achievement robots.

Every team has its introverts and extroverts. Do you think this crisis has levelled the playing field between them?

I wouldn’t go that far. I think the reality of the current situation is we’re still catering to extroversion. We’re now sitting on video calls all day, as opposed to saying: “You know what, maybe we should have fewer meetings”.

We’ve known for a while that that introverts’ voices tend to get overlooked in a group setting. This would be a good time to experiment with moving towards some more independent individual work, which we know is the best approach if you want to generate lots of good ideas in groups.

One of the simple practices I would recommend to make sure that introverts don’t get drowned out is to shift from brainstorming to brain-writing. So brain-writing is a process where you [ask] all the people in a team to come up with ideas independently, then submit them. Then you review them. That leverages individual strengths around coming up with original ideas and allows the group to do what it does best, which is to begin to evaluate and refine. That’s probably one of the most effective ways to make sure that introverts are heard.

Through this crisis, managing expectations has become even harder. All of a sudden, we’re workers, we’re teachers, we’re providers, we’re cleaners. Should we try and keep up? Is this good for our sanity?

This is a time when leaders need to be flexible and compassionate. This is not an experiment that any of us opted into, but as long as we’re stuck with it, as a leader, it’s an opportunity to say: “If I impose less control over people’s schedules and plans, that’s going to teach me whether I can trust them or not”.

We’ve known from a couple of decades of research on management and monitoring that when people are monitored too closely, that signals distrust and they respond by saying, “I don’t really feel obligated to act in a way that you might consider trustworthy”. Whereas when you allow [people] to make some choices, they start to feel a greater sense of loyalty and they reciprocate the trust that they’re shown. Given that we don’t have a lot of options anyway to control people, this is the ideal time to do a little bit less of it.

Is this a particularly challenging time for managers, and what advice would you have for them?

I think this is a great time for leaders to be more hands-off when it comes to scheduling and planning. Where leaders may need to be a little bit more hands-on is in figuring out how their people are doing on a day-to-day basis. This is one place where leaders have an opportunity to learn.

Imagine if you’re a manager, how awkward it would be in year two to sit down and say: “I’d love to find out what you’re finding interesting in this job; what aspects of your work you find meaningful; and are there changes we can make that would make your job a little bit more exciting?”

This is a moment when leaders can take a step back and say: “I haven’t always learned as much about my employees’ values, interests, strengths, motivations as I should have, and what better time than now”.

How does work/life balance work in a crisis like this?

Work/life balance has been a myth for a long time. If you care about your family, and you care about your job, and you also want to prioritize health and friendships and hobbies, the idea that you might have even a day where all those things are in perfect harmony to me is hysterically funny, if not just wrong.

What I always strive for is balance in a week, where I might have two days where I’m pretty focused on my work and I don’t get as much time with my family as I want, but then I’ll have two more days where I’m in family mode and work takes a backseat. That’s probably the most realistic way to manage this crisis – to say [that] instead of work/life balance, we ought to think about work/life rhythm.

You’ve written a lot about givers, takers and matchers. Does this period of self-isolation when working remotely magnify or reduce these qualities?

Giving, taking and matching are just different styles of interaction that we bring to the workplace. Givers are people who by default want to know, “what can I do for you?” Takers are the opposite. They’re interested in figuring out “what can you do for me?” And then matchers hover in the middle of that spectrum and say, “I don’t want to be too selfish or too generous, and so I’ll do something for you if you do something for me”.

The takers may feel like they have a little bit more licence to shirk, maybe to steal credit for other people’s ideas. I think though, we’ve seen an incredible outpouring of generosity in this crisis. The givers really see this as a situation where they need to step up. They feel a sense of responsibility to try to help. My guess is that matching gets weeded out a little bit. I don’t think that most people operate like matchers because it’s their core value. I think people match because they’re afraid of the risks of over-correcting on either side. In these situations, people probably gravitate more toward fundamentally, am I more of a selfish or generous person?

One of the big frustrations for givers in a situation like this is they don’t always know where they can help. A couple of years ago, I cofounded a knowledge-sharing platform called Givitas, to make it easy for people to seek and give help in five minutes a day or less. I would love to see more of those kinds of efforts to make sure that we can make people’s needs and requests visible, so that the people who have the motivation and the ability to contribute are able to direct their energy in the way it’s needed.

You said recently that interruptions are part of our new reality. Many people are struggling with distractions and procrastination. Are there ways to make ourselves more resilient to this?

I don’t know that that resilience is possible when it comes to interruptions, because the problem is less that they’re a source of hardship; it’s more that they’re distracting and it’s hard to get back into the task. Probably one of the best things we can do is try to find a sense of self-compassion.

Psychologists like Kristin Neff say, “think of the kindness that you would show to a friend who was in a situation like yours. What happens if you apply that same kindness to yourself?” When we get interrupted, instead of getting frustrated, I can say, “okay, this is a really difficult time right now”.

Interruptions are part of the human condition. They are an intensified part of the human condition during a pandemic. I know I’m not the only one facing these. Let me just see if I can get through today without losing control. If I don’t succeed today, I’ll try again tomorrow. When we don’t beat ourselves up like that, it’s a lot easier to move forward as opposed to wallowing in the challenges we’ve faced in the past.

Is there anything positive that may come out of this crisis?

We’re going to see a lot of employers embrace more flexibility around working from home and having virtual teams. They’re going to find out that it wasn’t as impossible as they thought it was, and there are some productivity gains that come from not having to commute, and getting to work where you want.

On an individual level, unfortunately, there are some people who are going to face post-traumatic stress. The encouraging news psychologically is over half of people report a different response to trauma, which is post-traumatic growth. Post-traumatic growth is the sense that, I wish this didn’t happen but, given that it happened, I feel like I am better in some way. It might be a heightened sense of personal strength; it could be a deeper sense of gratitude; it could be finding new meaning, or investing more in relationships.

Being so eager to get back to normal, having gone through this long crisis, how do we make sure that we learn from this experience?

Learning from an experience like this comes from reflection. As people come out of this crisis and start coming back to work, the first thing that I would do is have a discussion about what everyone learned from the experiments they ran. Some of those experiments were by force, others were by choice, but we’ve all had to test out different routines and the way we work.

I’d want to hear what everyone tested out, what worked and what didn’t, and then keep evolving what we thought were our best practices in light of that. That would be something that you continue doing. Last I checked, experiments are the best way to learn.

Presumably there’ll be some powerful insights for you to learn from this whole experience?

There are going to be some incredible natural experiments that are already being run. They’re going to be analyzed, and we’re going to be able to see what’s the effect of having to work from home on productivity at a scale that’s never been tested before. We’re also going to learn something about what happens to people’s creativity and connection when they can’t interact face-to-face with their colleagues.

There’s a whole group of organizational psychologists, as well as sociologists and management professors, who are going to spend the next five, 10 years studying the effects of this pandemic in different places. In a way, another form of post-traumatic growth is we gain new insights about how to work together effectively from a distance that we wouldn’t have had access to otherwise. And I wish we didn’t have access to it. I’d rather not go through this crisis. But given that we’re stuck with it, we might as well try to learn from it.

6 Ways To Make Digital Investments More Successful

Recently I posted here about how organisations can go back to basics and understand what digital really means. In the context of today’s rapid acceleration of digital and IT investments to support remote or new ways of working – from cloud to SaaS tools to desktop VC solutions – this is critical to understand.

Another key fact to consider is that some of the most successful companies ever were started during or just after times of crisis (e.g. GE, GM, IBM, Disney, Facebook).

For leaders who can seize the ‘re-set’ opportunity this crisis provides – and start to engage with more long-term, future-focused, and exploratory strategic planning with digital at the core – this presents a potentially game-changing moment.

This presents a critical question: how should firm’s approach and organise to make digital or innovation investments and transformations successful?

Whilst there is no playbook, below I pull together a number of perspectives from some of the world’s leading management thinkers and practitioners on strategy, digital, innovation and change.

The Challenge

Digital transformation is extremely complex and requires new ways of approaching strategy. Starting big, spending a lot, and assuming you have all the information is likely to produce a full-on attack from corporate antibodies—everything from risk aversion and resentment of your project to simple resistance to change.

  1. Start Small, Think Big

Professor Rita McGrath calls this ongoing learning approach to strategy: discovery-driven planning (DDP). It was developed in the 1990s as a product innovation methodology, and it was later incorporated into the popular “lean start-up” tool kit for launching businesses in an environment of high uncertainty. At its center is a low-cost process for quickly testing assumptions about what works, obtaining new information, and minimizing risks. According to Rita:

By starting small, spending a little on an ongoing portfolio of experiments, and learning a lot, you can win early supporters and early adopters. By then moving quickly and demonstrating clear impact on financial performance indicators, you can build a case for and learn your way into a digital strategy. You can also use your digitization projects to begin an organizational transformation. As people become more comfortable with the horizontal communications and activities that digital technologies enable, they will also embrace new ways of working.

2. Soft and Hard Facts About Change

Managing change is tough, but part of the problem is that there is little agreement on what factors most influence transformation initiatives. Ask five executives to name the one factor critical for the success of these programs, and you’ll probably get five different answers.

In recent years, many change management gurus have focused on soft issues, such as culture, leadership, and motivation. Such elements are important for success, but managing these aspects alone isn’t sufficient to implement transformation projects.

According to consultants from BCG in an Harvard Business Review article entitled The Hard Side Of Change Management:

What’s missing, we believe, is a focus on the not-so-fashionable aspects of change management: the hard factors. These factors bear three distinct characteristics. First, companies are able to measure them in direct or indirect ways. Second, companies can easily communicate their importance, both within and outside organizations. Third, and perhaps most important, businesses are capable of influencing those elements quickly. Some of the hard factors that affect a transformation initiative are the time necessary to complete it, the number of people required to execute it, and the financial results that intended actions are expected to achieve. Our research shows that change projects fail to get off the ground when companies neglect the hard factors. That doesn’t mean that executives can ignore the soft elements; that would be a grave mistake. However, if companies don’t pay attention to the hard issues first, transformation programs will break down before the soft elements come into play.

3. Breaking Down the Barriers

According to a 2019 article from the partners from Innosight, a critical reason for businesses failing to get the impact they want is because they’ve failed to address a huge underlying obstacle: the day-to-day routines and rituals that stifle innovation.

Shifting+the+Culture+Iceberg

Innosight Partner Scott Anthony talks further about this below:

4. A Systematic Approach

A study by McKinsey here of leaders post-transformation has shown there are 21 best practices for organisation’s to implement to improve the chances of success.

These characteristics fall into five categories: leadership, capability building, empowering workers, upgrading tools, and communication. Specifically:

  • having the right, digital-savvy leaders in place
  • building capabilities for the workforce of the future
  • empowering people to work in new ways
  • giving day-to-day tools a digital upgrade
  • communicating frequently via traditional and digital methods

One interesting best practice was that firm’s who deploy multiple forms of technologies, tools and methods tended to have a great success rate with transformation (see below).

This might seem counterintuitive, given that a broader suite of technologies could result in more complex execution of transformation initiatives and, therefore, more opportunities to fail. But the organizations with successful transformations are likelier than others to use more sophisticated technologies, such as artificial intelligence, the Internet of Things, and advanced neural machine-learning techniques.

4. Execute AND Innovate

For any followers of the work of the late Professor Clayton Christensen on Disruptive Innovation (view his HBR collection of popular articles here), this is a fundamental challenge for almost every established firm which often becomes a matter of survival during industry, business model, technology or other shifts.

According to Alex Osterwalder:

This continues to be one of the biggest challenges we see companies face: to create two parallel cultures of world-class execution and world class innovation that collaborate harmoniously.

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