Category: Disruptive Technologies

BBC’s Reith Lectures – Living with AI

Last Wednesday BBC R4 hosted the first of 4 weekly lectures hosted by Professor Stuart Russell, a world-renowned AI expert at UCLA. The talks (followed by Q&A) examine the impact of AI on our lives and discuss how we can retain power over machines more powerful than ourselves.

I think this area (e.g. AI commercialisation, AI governance, AI safety, AI ethics, AI regulation etc) is going to be one of the hot topics of the next decade alongside trends including climate change, fintech (crypto), AR/VR, quantum computing etc. Accordingly I couldn’t wait to hear Professor Russell speak.

The event blurb states the following:

The lectures will examine what Russell will argue is the most profound change in human history as the world becomes increasingly reliant on super-powerful AI. Examining the impact of AI on jobs, military conflict and human behaviour, Russell will argue that our current approach to AI is wrong and that if we continue down this path, we will have less and less control over AI at the same time as it has an increasing impact on our lives. How can we ensure machines do the right thing? The lectures will suggest a way forward based on a new model for AI, one based on machines that learn about and defer to human preferences.

As I write, I have heard 2 talks both of which have been absolutely fascinating (and quite honestly, scary. Especially regarding military applications of AI which is already here). I didn’t take notes however the BBC interviewed Professor Russell ahead of the talks. I have provided a summary of the Q&A below which is well worth a read:

How have you shaped the lectures?

The first drafts that I sent them were much too pointy-headed, much too focused on the intellectual roots of AI and the various definitions of rationality and how they emerged over history and things like that.

So I readjusted – and we have one lecture that introduces AI and the future prospects both good and bad.

And then, we talk about weapons and we talk about jobs.

And then, the fourth one will be: “OK, here’s how we avoid losing control over AI systems in the future.”

Do you have a formula, a definition, for what artificial intelligence is?

Yes, it’s machines that perceive and act and hopefully choose actions that will achieve their objectives.

All these other things that you read about, like deep learning and so on, they’re all just special cases of that.

But could a dishwasher not fit into that definition?

It’s a continuum.

Thermostats perceive and act and, in a sense, they have one little rule that says: “If the temperature is below this, turn on the heat.

“If the temperature is above this, turn off the heat.”

So that’s a trivial program and it’s a program that was completely written by a person, so there was no learning involved.

All the way up the other end – you have the self-driving cars, where the decision-making is much more complicated, where a lot of learning was involved in achieving that quality of decision-making.

But there’s no hard-and-fast line.

We can’t say anything below this doesn’t count as AI and anything above this does count.

And is it fair to say there have been great advances in the past decade in particular?

In object recognition, for example, which was one of the things we’ve been trying to do since the 1960s, we’ve gone from completely pathetic to superhuman, according to some measures.

And in machine translation, again we’ve gone from completely pathetic to really pretty good.

So what is the destination for AI?

If you look at what the founders of the field said their goal was, general-purpose AI, which means not a program that’s really good at playing Go or a program that’s really good at machine translation but something that can do pretty much anything a human could do and probably a lot more besides because machines have huge bandwidth and memory advantages over humans.

Just say we need a new school.

The robots would show up.

The robot trucks, the construction robots, the construction management software would know how to build it, knows how to get permits, knows how to talk to the school district and the principal to figure out the right design for the school and so on so forth – and a week later, you have a school.

And where are we in terms of that journey?

I’d say we’re a fair bit of the way.

Clearly, there are some major breakthroughs that still have to happen.

And I think the biggest one is around complex decision-making.

So if you think about the example of building a school – how do we start from the goal that we want a school, and then all the conversations happen, and then all the construction happens, how do humans do that?

Well, humans have an ability to think at multiple scales of abstraction.

So we might say: “OK, well the first thing we need to figure out is where we’re going to put it. And how big should it be?”

We don’t start thinking about should I move my left finger first or my right foot first, we focus on the high-level decisions that need to be made.

You’ve painted a picture showing AI has made quite a lot of progress – but not as much as it thinks. Are we at a point, though, of extreme danger?

I think so, yes.

There are two arguments as to why we should pay attention.

One is that even though our algorithms right now are nowhere close to general human capabilities, when you have billions of them running they can still have a very big effect on the world.

The other reason to worry is that it’s entirely plausible – and most experts think very likely – that we will have general-purpose AI within either our lifetimes or in the lifetimes of our children.

I think if general-purpose AI is created in the current context of superpower rivalry – you know, whoever rules AI rules the world, that kind of mentality – then I think the outcomes could be the worst possible.

Your second lecture is about military use of AI and the dangers there. Why does that deserve a whole lecture?

Because I think it’s really important and really urgent.

And the reason it’s urgent is because the weapons that we have been talking about for the last six years or seven years are now starting to be manufactured and sold.

So in 2017, for example, we produced a movie called Slaughterbots about a small quadcopter about 3in [8cm] in diameter that carries an explosive charge and can kill people by getting close enough to them to blow up.

We showed this first at diplomatic meetings in Geneva and I remember the Russian ambassador basically sneering and sniffing and saying: “Well, you know, this is just science fiction, we don’t have to worry about these things for 25 or 30 years.”

I explained what my robotics colleagues had said, which is that no, they could put a weapon like this together in a few months with a few graduate students.

And in the following month, so three weeks later, the Turkish manufacturer STM [Savunma Teknolojileri Mühendislik ve Ticaret AŞ] actually announced the Kargu drone, which is basically a slightly larger version of the Slaughterbot.

What are you hoping for in terms of the reaction to these lectures – that people will come away scared, inspired, determined to see a path forward with this technology?

All of the above – I think a little bit of fear is appropriate, not fear when you get up tomorrow morning and think my laptop is going to murder me or something, but thinking about the future – I would say the same kind of fear we have about the climate or, rather, we should have about the climate.

I think some people just say: “Well, it looks like a nice day today,” and they don’t think about the longer timescale or the broader picture.

And I think a little bit of fear is necessary, because that’s what makes you act now rather than acting when it’s too late, which is, in fact, what we have done with the climate.

The Reith Lectures will be on BBC Radio 4, BBC World Service and BBC Sounds.

Legaltech Venture Investment

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

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

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

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

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

According to various start-up founders:

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

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

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

Here are a few observations on what is going on:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

In Chairman Cicilline’s wrap-up:

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

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

Behind The Buzzwords Podcast: Disruptors

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

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

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

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

4 Key Takeaways From The US Big Tech ‘Monopoly’ Hearings

The House Judiciary Committee’s Democratic chairman, Rhode Island Rep. David Cicilline, concluded today’s daylong hearing by hinting at what might lie ahead as lawmakers ponder federal regulations to hold the four companies — worth nearly a combined $5 trillion — to account.

In summary, Rep. David Cicilline, D-R.I., says Amazon, Facebook, Google and Apple operate like monopolies and need to be broken up or regulated.

“These companies as they exist today have monopoly power. Some need to be broken up. All need to be properly regulated and held accountable,” said Cicilline, adding that antitrust laws written a century ago need to be updated for the digital age.

“When these laws were written, the monopolists were men named Rockefeller and Carnegie,” he said. “Today the men are named Zuckerberg, Cook, Pichai and Bezos. Once again, their control of the marketplace allows them to do whatever it takes to crush independent business and expand their own power. This must end.”

This power has been obvious for many years (and accelerated in 2020 due to COVID) however the political will has never been there until now, and agreeing the exact nature of the ‘stick’ or remedies to sort out the issues is never an easy task.

According to NPR, 4 key takeaways from today include the following:

  1. Bezos “can’t guarantee” Amazon never used seller data to make its own products
  2. Hurting the competition emerges as Democrats’ primary charge against Big Tech
  3. Republicans sidetrack hearing to air complaints over anti-conservative bias
  4. Missing from view? Zuckerberg’s reaction (when Bezos described social media as a “nuance destruction machine”)

NPR do a great job filling out the details and you can read the full article here

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.

The full list of success tactics are below with the full article is here.

Out of 83 practices that were tested in the survey, the following are those that best explain the success of an organization’s digital transformation:

  1. Implement digital tools to make information more accessible across the organization.
  2. Engage initiative leaders (leaders of either digital or nondigital initiatives that are part of the transformation) to support the transformation.
  3. Modify standard operating procedures to include new digital technologies.
  4. Establish a clear change story (description of and case for the changes being made) for the digital transformation.
  5. Add one or more people who are familiar or very familiar with digital technologies to the top team.
  6. Leaders engaged in transformation-specific roles encourage employees to challenge old ways of working (processes and procedures).
  7. Senior managers encourage employees to challenge old ways of working (processes and procedures).
  8. Redefine individuals’ roles and responsibilities so they align with the transformation’s goals.
  9. Provide employees with opportunities to generate ideas of where digitization might support the business.
  10. Establish one or more practices related to new ways of working (such as continuous learning, open physical and virtual work environments, and role mobility).
  11. Engage employees in integrator roles (employees who translate and integrate new digital methods and processes into existing ways of working to help connect traditional and digital parts of the business) to support the transformation.
  12. Implement digital self-serve technology for employees’ and business partners’ use.
  13. Engage the leader of a program-management office or transformation office (full-time leader of the team or office dedicated to transformation-related activities) to support the transformation.
  14. Leaders in transformation-specific roles get more involved in developing the digital transformation’s initiatives than they were in past change efforts.
  15. Leaders in transformation-specific roles encourage their employees to experiment with new ideas (such as rapid prototyping and allowing employees to learn from their failures).
  16. Senior managers get more involved in digital initiatives than they were in past change efforts.
  17. Leaders in transformation-specific roles ensure collaboration between their units and others across the organization when employees are working on transformation initiatives.
  18. Senior managers ensure collaboration between their units and others across the organization.
  19. Engage technology-innovation managers (managers with specialized technical skills who lead work on digital innovations, such as development of new digital products or services) to support the transformation.
  20. Senior managers encourage their employees to experiment with new ideas.
  21. Senior managers foster a sense of urgency within their units for making the transformation’s changes.

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.

Watch this video here to read more about how leaders can overcome this challenge.

5. Constant Learning

In a constantly evolving landscape, it is critical for leaders to keep learning and evolving their thinking and tool-sets for strategic planning, crisis management, innovation, problem solving, and other business processes.

There are lots of sources out there (including those mentioned above), but below I provide a few great ways I do this (NB I am not formally affiliated with any of these organisations):

Strategy Upskilling:

Thought Leadership

Webinars

Podcasts:

Startups

  • Techcrunch
  • Crunchbase

Summary

There are a number ways to improve the thinking and planning of the approach to digital investment strategy. This not only improves the chances of benefit realisation and achievement of strategic goals, but in the current time of crisis, can set up the firm for long-term success.

Whilst there is no playbook for leaders, these initial set of resources can help organisations to refocus current thinking and initiatives during these extraordinary times.

In summary, the themes were:

  1. Start Small, Think Big
  2. Soft and Hard Facts Of Change
  3. Break Down The Barriers
  4. Systematic Approach
  5. Execution AND Innovation
  6. Constant Learning

 

What Digital Really Means

“Everyone wants to go digital. The first step is truly understanding what that means” – McKinsey

I was talking to a COO of an off-shore investment bank yesterday and he mentioned something which gave me the impression that his bank did not understand what ‘digital’ really meant. According to McKinsey:

For some executives, it’s about technology. For others, digital is a new way of engaging with customers. And for others still, it represents an entirely new way of doing business. None of these definitions is necessarily incorrect. But such diverse perspectives often trip up leadership teams because they reflect a lack of alignment and common vision about where the business needs to go. This often results in piecemeal initiatives or misguided efforts that lead to missed opportunities, sluggish performance, or false starts.

As COVID-19 continues to rapidly accelerates the shift to building more digital capabilities within organisations, it is a critical time to take a step back and reevaluate existing efforts in light of the new challenges ahead. This means properly understanding what digital means, assessment of existing efforts, aligning to future strategy, and identifying what capabilities are needed across leadership, culture, and execution.

Whilst extremely hard, now is the best time to refocus efforts toward accelerating digitisation as the case for such change is for some a matter of survival. Think about how many food and other retailers are rapidly shifting to e-commerce models requiring new skills, software, tools and mindsets.

You can read more on this from McKinsey here

 

Turbocharging Legal Industry Transformation

“COVID-19 will produce a thinning of the herd and a reimagined legal industry” – Mark Cohen

Last Thursday I watched a great online webinar run by LegalGeek entitled ‘An Uncertain Decade’. Legal sector experts Mark Cohen and Richard Susskind ran the sessions. Whilst I have read various thought leadership from each expert, it was the first time I had seen either speak. Not surprisingly, they both were very impressive in both domain expertise and thoughtfulness around their points of view.

Here are some key takeaways (along with my thoughts):

  • Disruption: COVID-19 will dramatically turbocharge legal industry transformation which has been slowly accelerating since the 2008 Financial Crisis. This may not be that surprising to many outsiders, however many lawyers – including those in Generation X – still tend to be conservative when thinking about competition, new technologies, business models, and structural market changes. Transformation and disruptive models and services will continue to come from outside traditional law firms. Whilst Disruptive Innovation theories of Professor Clayton Christensen were not referenced, his work on how established firms often are disrupted by low-end entrants who move up-market over time, will provide insight as to why and how this is happening within the legal sector (click here for his articles from Harvard Business Review).
  • Innovation: Enterprise clients and consumers will continue to drive the shift away from bundled services toward a more productised, customer-centric mode of consumption at scale which leverage new technologies, business models, and regulatory changes. This has already been happening to some extent ‘around the edges’, and facilitated by ABS models in the UK (whereby retailers (e.g. Co-Op), real estate agents, insurers and other firms can compete head-on with traditional legal practices with their own legal services ventures). DoNotPay in the US was cited as a recent example of a start-up which has over 100 use cases of dispute resolution services (e.g. fight a parking ticket). A new and current use case in the US for them has been to make it easy, cheap and convenient to file unemployment and other worker claims.
  • Unbundling: The impending depression driven by COVID-19 and resultant cost pressures for clients will accelerate the shifting of lower value, high-volume work to more flexible, alternative providers (e.g. LPOs, ABS Licensed Firms, Big4, Axiom, UnitedLex etc) and digital platforms (e.g. DoNotPay). This will continue to enable these players to move further up-scale into higher-value, more complex work and jobs. This is how the Indian IT outsourcing firms managed to make significant in-roads against Accenture, IBM and others in the 2000s, and how Toyota managed to become a US car manufacturing leader with its low-cost model US market strategy. Over the coming years, the legal industry will continue to rapidly fragment beyond traditional structural boundaries to incorporate a much bigger share for alternative providers (which will grow rapidly at the expense of incumbents), but significant new markets will be created especially for those consumers (i.e. non-consumers) who historically have never able to access low-cost, convenient legal services;
  • Business Models: A next generation of technology-enabled service providers (e.g. FisherBroyles) will gain rapid scale over the next decade in the same way as FinTechs have within Retail Banking. Continued experimentation by established law firms (e.g. non-legal services diversification, in-sourcing IT, new product development etc) and further consolidation within and amongst traditional law firms and alternative services providers, vendors and legaltechs unable to re-capitalise or scale. Large traditional law firms with the foresight and capital to invest over the coming years will likely continue to struggle to properly allocate resources and organise these innovative models efficiently and effectively within the established firm.
  • Online Dispute Resolution: COVID-19 has provided an MVP to as legal systems and courts globally have had to re-think how to deliver this. According to Mark Cohen:

The inaccessibility, cost, formality, abstruse rules, and protracted processes of courts in their present guise is misaligned with life in the digital age. The urgency of modernization is unprecedented. Courts around the world have ground to a halt when demand for accessible, efficient, and widespread administration of justice is desperately needed.

  • Education: Law Schools have not really changed their content, formats or approach to skills in over 40 years. Combined with EdTech disruption, providers will be under significant pressure to change in line with industry and client demands. Traditional JD/LLB’s offered by mid-market schools in the short-term will see massive disruption and closures, whilst the degree as it stand may become a more commoditised requirement, augmented by other specialty courses run by others or industry. Clearly, now is the time for online law ‘degree’ or course models, assuming the solicitor/lawyer regulatory boards provide approval (if they haven’t already)
  • Training: Traditional insistence of a junior being trained up or supervised by a senior lawyer/partner will be turned on its head. Assuming a longer-term shift to more remote working for a large number of the workforce and demand for more multi-skilled lawyers (e.g. project management), training for juniors (and all staff) will need to be redesigned.

In a recent Forbes article here, Mark Cohen concludes the following:

The old guard will cling to the hope these are temporary changes. They will point to the recession precipitated by the 2008 global economic crisis and suggest the current one will take a similar course. This time  is different. Technology and new delivery models are far more advanced than they were in 2008. Consumers have a different mindset and a greater urgency to solve a growing list of complex challenges. The potential of technology and its ability to support new models, processes, and paradigms is already on display. The genie is out of law’s bottle, and it will not return.

Opportunities for Law (and other) Firms

Interestingly, there wasn’t too much discussion on this during the webinar. For me, Disruptive Innovation theory might provide some guidance for any progressive law firms who wish to take on the inevitable structural and business model disruptions described above. I’ll save this analysis for another post soon.

 

14 Sources of Disruption

As the COVID-19 pandemic continues to cause significant or catastrophic disruption to many organisations, it is almost crazy to think that COVID-19 represents one source of disruption. Obviously it is a major shock and is inter-related with other forces (e.g. economic). However, from a crisis response perspective and the need to re-set short and longer-term strategic plans, it is important for leaders to always look at the bigger picture.

Why? According to Amy Webb, founder of  The Future Today Institute:

If leaders think that they are aware of the forces that might disrupt their company, their lens’ may be far too narrow…

To support such analysis, I use a tool called The Strategic Forces Framework (SFFF) which Amy Webb discusses in detail here. 

MAG-webb-essay-s1

Clearly, the SFFF builds on long-standing (and less comprehensive) frameworks including PESTLE. Many forces will seem obvious, but others less so.  

Amy Webb provides context on using the tool:

The SFFF helps clients identify external uncertainties which broadly affect business, markets, and society across positive, neutral, or negative dimensions. In over a decade of strategy consulting and research, I have observed that all major or ‘disruptive changes’ are the result of one or more of the 11 forces. 

For leaders and executives, the critical skill is being able to look for areas of convergence, inflections, and contradictions, with emerging patterns especially important because they signal ‘transformation’ of some kind. People must connect the dots back to their industries and companies, and position teams to take incremental – or transformative – actions as required.

Whilst many of the 11 sources of disruption might seem obvious or onerous at first, taking a broader viewpoint provides perspective as the tool can help identify critical growth opportunities (e.g. market-creating innovations) or areas of potential disruption (e.g. new business models). For example, an established regional farming equipment firm tracking eco-friendly infrastructure trends could be a first mover into new or emerging markets, while a traditional electronics retailer (with online operations) monitoring 5G, IoT and AI plus segments of non-consumption, could be better positioned to compete against the big e-commerce platforms.

Whilst Amy uses 11 forces, I add 3 more to make 14. See below for details but I believe that Legal, Industry, and Business Models deserve their own line of enquiry. You only have to think about the music-industry in the early 2000s to understand why that matters.

Sources of macro change encompass the following:

  1. Prosperity: the distribution of income and wealth across a society; asset concentration; and the gap between the top and bottom of the pyramid in within an economy.
  2. Education: access to and quality of primary, secondary, and postsecondary education; workforce training; trade apprenticeships; certification programs; the ways in which people are learning and the tools they’re using
  3. Infrastructure: physical, organizational, and digital structures needed for society to operate (bridges, power grids, roads, Wi-Fi towers, closed-circuit security cameras); the ways in which the infrastructure of one city, state, or country might affect another’s.
  4. Government: local, state, national, and international governing bodies, their planning cycles, their elections, and the regulatory decisions they make.
  5. Geopolitics: the relationships between the leaders, militaries, and governments of different countries; the risk faced by investors, companies, and elected leaders in response to regulatory, economic, or military actions.
  6. Economy: Standard macroeconomic and microeconomic factors, including interest rates, inflation, exchange rates, taxation
  7. Public Health: changes occurring in the health and behaviour of a community’s population in response to lifestyles, disease, government regulation, warfare or conflict, and religious beliefs.
  8. Social: Life-style, trends, ethics, norms, religions, diversity and inclusion, culture, religion, demographics, population rates and density, human migration, and other dynamics are leading to shifts in communities, markets (including non-consumption) and societal needs
  9. Environment: changes to the natural world or specific geographic areas, including extreme weather events, climate fluctuations, rising sea levels, drought, high or low temperatures, and more. Agricultural production is included in this category.
  10. Communications: all of the ways in which we send and receive information and learn about the world, including social networks, news organizations, digital platforms, video streaming services, gaming and e-sports systems, 5G, and the boundless other ways in which we connect with each other.
  11. Technology: not as an isolated source of macro change, but as the connective tissue linking business, government, and society. We always look for emerging tech developments as well as tech signals within the other sources of change.
  12. Legal: Privacy, health and safety, labour, consumer rights, product safety 
  13. Industry: Suppliers, buyers, non-buyers (e.g. non-consumption), competitors (current and new), substitutes, distribution channels, partners, ecosystems and value-networks 
  14. Business Models: The incredible pace of technological change continues to open up more ways to make money and go-to-market. Combined with the tremendous disruptive impact business model innovation can have on traditional firms and industries, I believe it is critical to include it as a separate category for investigation e.g. Software-as-a-service, Direct-to-consumer, Pay-as-you-go

How best to use the SFF?

Most companies we encounter use the Strategic Forces Framework to help make sense of initial or deep uncertainty, optimise existing planning processes, or reinvent how that is typically performed. Some use it at the start of a strategic project at corporate levels, while others use it as a guiding principle throughout their functional or departmental work streams, processes, and planning. The key is to make a connection between each source of change and the organisation with questions such as: 

  • Who is funding new developments and experimentation in this source of change? 
  • Which populations will be directly or indirectly affected by shifts in this area? 
  • Could any changes in this source lead to future regulatory actions? 
  • How might a shift in this area lead to shifts in other sectors? 
  • Who would benefit if an advancement in this source of change winds up causing harm?

Here are some good examples of use in business as usual (BAU) provided by Amy Webb:

I have seen the most success in teams who use the macro change tool not just for a specific deliverable but to encourage ongoing signal scanning. One UK-based multinational professional services firm took the idea to an amazing extreme:

    • It built cross-functional cohorts made up of senior leaders and managers from every part of the organization all around the world.
    • Each cohort had 10 people, and each person is assigned one of the sources of macro change, along with a few more specific technology topics and topics related to their individual jobs. 
    • Cohort members are responsible for keeping up on their assigned coverage areas. A few times a month, each cohort has a 60-minute strategic conversation to share knowledge and talk about the implications of the weak signals they’re uncovering. 

Not only is this a great way to develop and build internal muscles for signal tracking, it has fostered better communication throughout the entire organization.

Whilst this process might go against the established culture of your organization, embracing uncertainty is the best way to confront external forces outside of your control. Seeking out weak signals by intentionally looking through the lenses of macro change is the best possible way to make sure your organization stays ahead of the next wave of disruption. Better yet, it’s how your team could find itself on the edge of that wave, leading your entire industry into the future.

Crisis Leadership

Just about every business large and small across the world has been in crisis mode for some time dealing with the catastrophic consequences of the Corona Virus pandemic. Almost daily now there are announcements from companies shedding employees or going into administration. One interesting trend however are those CEOs who are pledging not to lay-off workers. For example, on March 26th in Techcrunch Marc Benioff (Salesforce CEO) announced a 90 day pledge.

This has got me thinking lately at a more macro-level: who are those business leaders who have successfully led companies through crises?

  1. Netflix CEO Reed Hastings in pivoting and transforming the business when confronted by an emerging disruptive technology, business models, and established well-funded competition;
  2. Steve Jobs in the late 1990s when he returned to the company he founded (and was ousted from);
  3. Richard Branson in the 1990s at Virgin Atlantic during the ‘dirty tricks war’ with British Airways;
  4. Bob Iger as CEO of Disney when, whilst he was opening Shanghai Disney, a toddler was killed by an alligator at Disney World Florida;
  5. Jørgen Vig Knudstorp as the new CEO of Lego Group in 2004 and embarking on a transformational turnaround;
  6. Angela Ahrendts as the new CEO of Burberry and transforming its brand and performance from ‘chavvy’ to high-end luxury;
  7. Amex CEO Kenneth Chenault following the September 11, 2001 terrorist attacks;
  8. CEO Howard Schultz in 1997 when a robbery killed 3 employees at a US store;
  9. Toyota CEO Jim Lentz during a 2.3 million car recall in the US

The way these leaders responded to their various crises – whether caused by macro-factors (e.g. terrorism, recession, disruptive technologies) or internal (e.g. mismanagement) – were certainly ‘make or break’ situations. In other words, without strong leadership and executing on relevant crisis management principles, the outcomes could have been catastrophic and/or bankrupted their respective companies.

Such leaders deployed various business strategies and tactics but professionally exhibited courage, decisiveness, emotional intelligence, transparency,  ownership, clear communication, and many other characteristics. It will be interesting to see how many current organisations and brands respond in a way that also gives them the best chance to survive short-term, as well as in a post-Corona world.

 

Zooming

I came across an article this week here which asked whether Corona Virus (CV) could present a tipping point for virtual events. This reminded me of a pre-CV experience at the end of 2019. I attended a virtual conference hosted by marketing guru Seth Godin.

Afterward I was amazed at how far VC technology has come in being able to easily manage large numbers of people in an interesting and organised way which adds-value to both sides. He ran it using Zoom, had over 300 attendees from 50 countries, used self-managed break-out rooms over the course of the 2hrs, and created interactivity (which game them market research) with Q&A into the chat boxes.

Whilst it wasn’t perfect, it was impressive. I would certainly attend more of these, and reconsider in-person ones. Until this time, I had only ever used VC tech for standard corporate meeting use cases with just a few people. Now, I am recommending my parents to set up Zoom as an alternative for traditional B2C options (Skype, FaceTime).  Although that may change if the firm can’t get a handle on Zoom-bombing.

Despite some negative scaling side-effects and challenges, Zoom’s stock has post-IPO gone through the roof (actually, through the atmosphere). This gives them a massive window to place new bets and scale-up new products, value-added services, and M&A.

It is not often a newly public firm gets to invest for the long-term, but now is the certainly the time to accelerate investments into becoming a key player within the enterprise (and B2C?) ecosystem. Vertical, horizontal and hybrid platform solutions across many sectors and use cases will likely emerge as it has with IoT. It will be interesting to see how it plays out, how Zoom responds, and how long until its market capitalisation falls back down to earth.

Thank you, Clayton

In early January 2003 I embarked on a year-long academic research project at Queensland University Of Technology where I was studying and teaching. The work culminated in a 50,000 word thesis centred around applying Clayton Christensen’s theories on disruptive innovation to the Australian music industry. I was fascinated in trying to understand the competitive responses of key players in the Australian music industry as they battled a disruptive innovation – digital music distribution. At the time, the entire industry – from major record labels to retailers such as HMV – was in a state of chaos meaning it presented a fascinating ‘live’ research case study. 

As part of the literature review, I had come across Clayton Christensen’s academic work and books in a comprehensive strategy and innovation theory review alongside management luminaries in Michael Porter. His work didn’t feature too widely in peer-reviewed journals as his seminal work (The Innovator’s Dilemma) had only recently been published (late 90s). However I distinctly remember that I was immediately captivated by how insightful and unique his work was in such a complicated area i.e. understanding why established companies often fail when confronted with emerging technologies. I felt that this represented a step-change from the traditional (i.e. manufacturing-driven) strategic management literature, but also drew relationships (and challenges) with research from various fields, including management, economics, finance, strategy, leadership, innovation, & organisational behaviour.  As I sought to better understand what was happening, why, and the implications in the rapidly evolving music industry, I felt that his frameworks, models and case studies of other industries were highly relatable to analysing the challenge I faced.

Clayton was the reason why I subsequently pursued career paths loosely aligned with his work. I became a technology lecturer teaching university students in the early 2000s on the new field of e-Commerce law. I became a technology lawyer advising governments on emerging online gambling regulatory models. I became a technology management consultant helping global telcos with strategy, transformation, & operating models. I launched a start-up to gain the ‘innovators’ perspective on launching & scaling disruptive technologies (NB the start-up was too early and later failed, and as such was far from being disruptive). I even launched my own version of Clayton’s Innosight consulting firm called ROCKET + COMMERCE which helps CXOs to navigate and take advantage of new and emerging technologies (e.g. Digital, Internet Of Things, Digital, SaaS etc). 

I had planned to make contact with Clayton and share my thesis in 2003/04, but I didn’t. I had planned to experience his teachings in Boston, but I never applied. I had once planned to convince Innosight to hire me, but I never pursued them. Upon hearing about Clayton’s recent passing, I immediately thought about these potential ‘missed’ opportunities to meet, engage, and express gratitude to someone who has had so much influence from afar. Whilst I now won’t ever have that opportunity, perhaps there are other ways. A crazy idea might be to build upon his work, like I aimed to do back in 2003. To do that properly may mean a radical career U-turn back to my academic roots. An easy idea would be to express gratitude to those who have helped me along the life journey so far, even if just a little. I don’t think I have thoughtfully done this, so right now would be a good time to start. To help provide additional inspiration, I’ve just ordered Clayton’s book from some years ago – How Will You Measure Your Life? (I didn’t realise he had written it). I’m sure it will have great ideas. And I wouldn’t be surprised if it also has a profound impact like his earlier works did on how I might spend the next 10-20 years. Watch this space (NB: I’ll provide a direct update to this post in 5 years on Jan 26 2025. Promise). 

RIP Clayton

Smart Contracts: The Big Questions

It feels as though people have been talking smart contracts for a long time. Like most new innovations, it will take a specific use case (i.e. business challenge important enough to justify adoption) to kick it out of the domain of academics & legal conferences, and into commerce & industry. Perhaps this has already happened. If it has, be sure to give me a shout.

Yesterday,  I came across an interesting analysis of smart contracts from Charles Kerrigan, a lawyer at big law firm CMS. It was compiled by Richard Troman of the blog Artificial Lawyer’s (must read for the legal techies out there). Mr Kerrigan was giving a speech as part of a panel giving evidence to the UK’s All Party Parliamentary Group on Blockchain at the end of last year. Whilst the speech is detailed, it provides an interesting deep dive into some of the pervasive questions out there on smart contracts. As Richard Troman’s points out:

…as the prospect of their use in day to day legal work draws ever closer, what should we be focusing on? How should we approach this subject and what really will be the key issues we need to grapple with before this quintessentially legal technology becomes mainstream?

The full extract is posted on Artificial Lawyer’s blog here. If you have any thoughts, or know of any live smart contract use cases in industry, be sure to let me know.

The Hype Cycle

I came across an article today which talked about why IoT has fallen short of expectations (check it out here). In summary, the key themes were:

  • Optimism of prediction
  • Niche consumer value
  • Privacy concerns
  • Inconsistent standards across hardware/software
  • Costs and limitations
  • Slow promise of the smart home use case

Reading this reminded me of what tends to happen with the adoption of most disruptive (or new) technologies, whether the Internet, AR/VR, AI, blockchain, or cryptocurrency. It is best represented by the Hype Cycle for Emerging Technologies who shows the rise-fall-rise of how markets tend to adopt innovations.

Below I’ve pasted in a Hype Cycle dedicated to IoT:

The key takeaway from the above charts is time. People always overestimate how quickly the mass market will adopt new innovations. There’s an entire body of work dedicated to explaining the reasons and not for this post. But it’s just not easy to get technology to a cost/performance level that works beyond the early adopters. A lot of things have to go right. And that includes one of the biggest things beyond technology: changing human behaviour.

 

1 Trillion Connected Devices

In a previous post I talked about how SoftBank recently announced that by 2035 1 Trillion devices would be connected. Whether or not that happens is not the point, as it’s about the ambition & not necessarily the result. But for that to happen, what needs to occur?

1. Market adoption by consumers and businesses of new products/services that help them solve most of their important daily problems & challenges;

2. Significant improvement in connectivity, cloud, data analytics & management, AI & other IoT solution & related technologies to help enterprises and the ecosystem handle all the real-time data being generated by the devices at such a significant scale;

3. Digital transformation of established enterprise & government to rapidly adapt to the new paradigm and compete with IoT focussed startups;

4. Deep ecosystem & cluster development with value-chain players working together & aligned in R&D and GTM within specific industry sectors or use cases.

5. Significant lowering of device manufacturing costs to enable business model innovations to drive market adoption, such as subscriptions, service models and so on.

There may be others but this is just a sample of my initial thoughts right now. If you have any others be sure to let me know

The Big 5

This post won’t be about what you might see on an African safari. Instead, today I’m thinking about where we are now, and where we are going in relation to the full potential of five disruptive technologies that get the most attention: AI, IoT, Blockchain, AR/VR, & Big Data.

Each technology is still in their infancy but fast maturing and gathering steam. We saw with cryptocurrencies in 2018 as a key use case for Blockchain which drove significant consumer & business adoption & later, government intervention

As I look ahead, the most interesting thing for me two-fold: (i) the timeframe(s) for the intersection of these technologies from a market adoption and technology maturity perspective, and (ii) the subsequent implications for established firms, and opportunities for new ones. If we think back to the late 2000s (over a decade since consumer internet introduction), it wasn’t until the launch of next generation mobile phones (via smartphones, tablets) that dramatically accelerated internet adoption driven largely by e-commerce. This opened up entirely new ecosystems (Apple, Google, Facebook, Uber, Amazon) whilst destroying others (Nokia, Motorola, Sears) in the process. For B2B/C, this enabled a new lawyer of applications & services for consumers & businesses alike, such as local discovery (e.g. restaurants), on-demand services (e.g. taxis, TV), & mobile (e.g. Amazon, eBay, banking). All designed to make life easier & better.

In 2018, such continued technology disruption – driven by the intersection of mobility & the internet – is only getting started (think retail, financial services, real estate etc). If we layer on top one or more the Big 5 technologies, it will be like pouring kerosene over an already burning fire. I can’t wait to see how it all plays out.

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