Thursday, 23 November 2017

A new epoch in knowledge and decision-making

There comes a time when significant shifts in our world demand that we look again at the models we have lived with for years. For example, it's broadly accepted that the Holocene epoch (marked by the end of the last ice age) has now given way to the Anthropocene epoch  (marked by humanities physical impact on Earth). I don't claim equivalence, but suggest that our knowledge framework also needs a seismic overhaul.

We've modelled the Knowledge and Innovation Network on sound research and practice that takes into account, and differentiates between, explicit/codified knowledge, tacit know-how and networked knowledge. Each 'generation' or mode is equally important, but requires very different approaches to stewardship and leverage.

None of these three modes take into account the enormous impact of Artificial Intelligence and machine learning on decision-making. These are not just technological developments but are impacting trust, 'expertise' and are pervasive. As my colleague Steve Dale puts it:
  • Data and technology democratisation is about creating an environment where every person can use data to make better decisions. But are we all competent enough to trust the decisions being made by algorithms we can't see or understand?
  • The world of data-driven intelligence is evolving. Big data is now moving from the sole care of data scientists and becoming accessible to employees throughout organisations. The mystique surrounding data analytics is falling away, with sophisticated data visualisation tools designed to let non-technically-minded people understand metrics. Information that supports “good” business or policy decisions is just a click away.
  • Algorithms are replacing intuition in terms of establishing “truth”. Algorithmic prediction, which is essentially the use of the available bodies of data in order to predict the future, is replacing expertise inference.
I suggested to my KIN colleagues that we add a fourth column called 'Augmented Knowledge'. A healthy debate followed. In order to settle things, the proposed new framework is shown below. As well as the new fourth column, other proposed changes are shown in bold. What do you think?


The debate will continue at the KIN Winter Workshop on 6th December 'Data driven Decision Making', being chaired by Steve Dale.

Monday, 23 October 2017

Decision making needs both AI and a healthy dose of gut-feel

The case for AI 
The KIN Autumn Workshop on 6th December is on 'Data-driven decision making'. As Steve Dale, the workshop facilitator says...

"The world of data-driven intelligence is evolving. Big data is now moving from the sole care of data scientists and becoming accessible to employees throughout organisations. The mystique surrounding data analytics is falling away, with sophisticated data visualisation tools designed to let non-technically-minded people understand metrics. Information that supports “good” business or policy decisions is just a click away".

The implication is that decisions that are based upon empirical data through data are evidentially better. In fairness, Steve does point out that reliance on back-box algorithmic data must always be used with caution (although in many cases, it is impossible to validate or even understand how algorithms come up with results). As we have seen in a previous KIN workshop on 'Evidence-based decision making', AI algorithms and analytics may simply reflect innate biases, making them appear superficially 'trustworthy'.

If these caveats can be taken in to account, AI and machine learning is certainly going to make us smarter and our decisions more evidence-based. That's a good thing, no?

The case for Intuition
At KIN we are always looking for alternative perspectives that sometimes challenge orthodoxy or 'trends'. Julian Birkinshaw, our keynote speaker for the KIN Spring 2018 workshop 'Reimagining the Innovative Organisation' will certainly do that. In his new book 'Fast Forward', Julian proposes that over-reliance on IT, big-data and advanced analytics actually reduces competitive advantage.

"At corporate level, we end up with analysis paralysis, endless debate, and a bias toward rational, scientific evidence at the expense of intuition or gut feel."

There is a need for current management models to take into account the agility provided by ubiquitous data and upstart disintermediators. Similarly, managers' skills honed to support meritocracy will need to change to reflect adhocracy. These must draw on intuition as much as evidence if organisations are to constantly innovate.

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On balance of course, rapid decisions, based on sound data-driven evidence that influences experiential judgment are an ideal. The reality is that time-critical decisions, an inability to understand the source of algorithmic outputs, engrained biases and shouty bosses all conspire to make decisions less perfect. 

It will be fascinating to explore the balance of Intuition and Data-driven decisions over the course of the KIN Winter and KIN Spring workshops. In the meantime, if you are want to balance an AI dominated view, I recommend reading 'Fast/Forward'.










Thursday, 5 October 2017

The Impact of Automation & AI In The Workplace

Warwick Business School’s Knowledge & Innovation Network (KIN) and Norton Rose Fulbright (NRF) will be facilitating a breakfast briefing during Workplace Week (13-17th November) on the topic of 'Automation & AI in the workplace'.

Workplace automation is becoming more widespread, and today’s AI-enabled, information-rich tools are increasingly able to handle jobs that in the past have been exclusively done by people (including tax returns, language translations, accounting, even some types of surgery) – automation is destined to have profound implications for the future world of work.

McKinsey recently reported that 30 percent of activities for 60 percent of occupations are now technically automatable. We will look at some of the evidence that supports this claim; how this is likely to change the workplace environment; the jobs, roles and skills that are being (or will be) affected, and whether these changes are heralding new opportunities or fuelling a dystopian future.  It will be a lively discussion!

The breakfast briefing is scheduled for Wednesday 15th November, from 8.30am to 10am, and is being hosted by Norton Rose Fulbright (NRF) at their futuristic offices at 3 More London Riverside London, SE1 2AQ. As part of the session, NRF will share valuable insight to a global productive search solution they have recently implemented within their own workplace in order to maximise efficiency.  Guests will also be invited to join a private tour of NRF’s impressive workplace, including their spectacular roof-top garden.

This event is one of many taking place during Workplace Week, which aims to raise funds for the BBC's Children In Need charity. Ticket price is £32, all of which goes to Children In Need . KIN and NRF are providing their services at zero cost.
More details and ticket purchase is available from the Workplace Week website.

Places are limited, so if the topic, breakfast, panoramic views of London from NRF's iconic rooftop garden and the opportunity to contribute to a worthwhile cause appeal to you, book your tickets now!

Friday, 29 September 2017

Failure is an Option


The TED Radio Hour features TED presenters and explores their ideas further. This week, in 'Failure is an Option' the host Guy Raz introduces stories that perfectly illustrate the power and importance of embracing failure in order to innovate and change.

Google innovation supremo, the wonderfully named Astro Teller, explains why Google X give bonuses and promotions to those who fail. Yes, you read that right. In the world of the Google 'Moonshot Factory' this makes perfect sense. And it evidently works.
A few notable bits of advice from Teller:

  • 'Run at the hardest parts of the problem first...These are the things most likely to derail your project'.
  • 'There is a difference between learning and failing. Real failure is the point at which you know you are working on is the wrong thing. Stopping at that point, you are shame-free'.
  • 'We have a learning loop of one week'.
  • 'We bonus everyone in a team that chooses to stop their project. This unlocks the potential in every idea'.

Secondly, my favourite 'Undercover Economist' Tim Harford, challenges us to embrace Trial and Error. He gives a brilliant reasoning, using the example of soap powder manufacturing, as to why we should never even try to get solutions to complex problems right first time. His impassioned plea to teachers to stop impressing the need for schoolkids to get 100% is very powerful.

Casey Gerald was brought up in a strict Southern Baptist community in the US. His story of how his beliefs were shattered when the Messiah failed to turn up at the turn of the millennium is very funny and thought provoking. It was however the start of a long journey through which Casey realised that finding out things don't work as expected should be embraced.




Monday, 21 August 2017

'Mapping Innovation' by Greg Satell - a very readable 'Playbook for navigating a disruptive age'

I've just read Greg Satell's new book 'Mapping Innovation'. It must be good because I took it on holiday to finish reading it! I'm a fan of his blog Digital Tonto, which I also recommend.

The book's title doesn't do it justice as it is full of innovation anecdotes, quotes, case-studies and practical advice. I was delighted to see that Satell talks extensively about diversity (in all its senses) in relation to innovation practice. In fact one chapter is entitled 'Innovation is Combination'. n order to innovate in the digital age organisations need to shift emphasis from knowledge workers to relationship workers'. 

Like almost every consultant, Satell frames his hypotheses using a 2x2 matrix. The Y axis is 'Problem Definition' . He emphasises the importance of a thorough understanding of the problem by quoting Einstein "If I had 20 days to solve a problem, I would spend 19 days defining it". The other axis is 'Domain Definition'; this is harder to define, but is primarily whether the organisation has the skills and capability to address the problem.
 
The examples of disruptive and breakthrough innovation reference the usual digital suspects including Google and Apple, but also draw on many from healthcare, finance and transportation. The Opensource movement and its implications for all sorts of contemporary collaborative models (eg Innocentive) that have followed is particularly interesting. I would have liked to have more examples of breakthrough innovation in organisational management, but maybe that's because there haven't been that many. Satell does describe AirBNB and Uber's disruptive business models, but even these are predicated on already well-established technology.

The most impactful take-away in 'Mapping Innovation' is the importance of Basic Research. In his 1945 report to President Truman, Vannevar Bush argued for what became the US Office of Scientific Research and Development (OSRD):

'Basic research leads to new knowledge. It provides scientific capital. It creates the fund from which the practical applications of new knowledge must be drawn'.

In the book we learn that both Google and Apple leaned heavily on the outputs from government-funded basic science that can be traced directly back to OSRD . Only giants such as IBM have the resources to carry out their own speculative research. Satell conspicuously avoids the elephant in the room by not addressing Trump and other western government's attacks on basic science funding and the implications for future downstream innovation. I am not sure whether he is deliberately avoiding taking a political stance, but if the author's premise is right about the importance of the bottom left quadrant of his matrix, innovation and economies will suffer in the long-term.

Meanwhile, individuals and organisations will focus on the other 3 quadrants and can learn a lot from this 'Playbook for navigating a disruptive age'.