Book review: 'Fast/Forward, make your company fit for the future' by Julian Birkinshaw (keynote speaker at KIN Workshop Spring 2018)

There's been some push-back recently regarding the benefits of the digital revolution. Julian Birkinshaw's book Fast/Forward suggests that organisations that embrace 'adhocracy', make smart intuitive decisions and act decisively will be the best prepared for uncertainty. Whilst it would seem that this almost defines small, agile firms, the book is full of examples of large corporations that have done this successfully.

The core principles of Fast/Forward are built around what he calls 'The four paradoxes of progress'. 

1. Creative destruction. A heretical idea challenges orthodoxy (Darwin or IKEA), disbelief of the establishment (Nokia), followed by the innovator becomes the establishment (Microsoft).

2. The more we know the less we understand. 'Whilst the human race is becoming collectively more knowledgeable every year, each of us (as individuals) is becoming relatively more ignorant'. 'Relatively' is the key word here due to the exponential increase in digital information available, compared to the linear rate of learning by us as individuals. Birkinshaw makes the case that team and networking can to some degree mitigate this paradox.

3. Connectivity and unpredictability.  Competing on computational power has become a race to the bottom when it comes to solving complexity. 'There is a risk that the combination of new technology and old questions means that you end up with answers that are exactly wrong, rather than roughly right'. This is where the book makes the case for more agile management, particularly experimentation and learning.

4. Knowing and believing. Ironically, the torrent of data pouring into our lives may mean that we may inadvertently be making decisions by 'appeals to our emotions, our intuitive beliefs and our hidden values'. Fast/Forward suggests that this is no bad thing and may be a way of business leaders differentiating themselves. The example cited is Apple, where product design was as much about beliefs and emotions as it was about hard-headed business.

The concept of 'Adhocracy' is not new. Alvin Tofler explored the idea of flexibility in dealing with uncertainty in his 1973 book Future Shock. Birkinshaw updates the concept for the big data and machine learning age. He also neatly contrasts it with meritocracy and bureaucracy. 

I was glad to see that rather than dismissing bureaucracy as an outmoded concept, he considers the merits of each and proposes a 'Trinity in Reality' model. 

The main call-to-action for me is in the chapter 'Linking Strategy Back to Purpose'. 'Leaders need to make a stronger emotional connection to those around them, rather than allowing sterile, data-driven decision making to dominate their actions, reactions and responses'. Birkinshaw suggests that organisations should put 'pro-social' goals first, for example hire for attitude and train for skill (most organisations do the reverse). There are many examples cited of large organisations that clearly instil a sense of moral purpose (Tata, Arla, SouthWest Airlines) whilst innovating to break orthodox organisational models. 

With all the excitement (and fear) around AI, big data and machine learning, it is easy to lose sight of vital business principles and values. The first half of Fast/Forward can be seen as a useful playbook for leaders wanting guidance on how to meld a technology revolution, give a clear sense of purpose for their organisations in an increasingly complex world and to embrace disruption.

Julian Birkinshaw is keynote speaker at the KIN Spring 2018 members' workshop 'Reimagining the Innovative Organisation'. This will take place at The Shard in London on 22nd March 2018.

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Fast/Forward 

Authors: Julian Birkinshaw, Jonas Ridderstrale

Published 2017 

Stanford Business Books 

ISBN 9780804799539

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.

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'.

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 (13-17^th 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 15^th 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!

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.

'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'. 

'Will video make text and writing obsolete?'

Here's an irony...
I've been doing research in preparation for the Autumn Knowledge and Innovation Network workshop 'Now You're Talking - the language of workplace communication'. 

I came across this recent blog post 'Will video make text and writing obsolete?' 

The irony that the posting uses text rather than video will not be lost on you. Josh Bernhoff raises some interesting observations about of mixed-media communication and which are the most effective tools. We will be exploring these and others at the workshop on 20th & 21st September.

The intersection of Design Thinking and Knowledge

An ex-colleague from the World Bank, Arno Boersma, has written a useful article about how Design Thinking can be applied to knowledge sharing.

http://journal.km4dev.org/index.php/km4dj/article/viewFile/293/413

I agree that trying to convince workers and managers that 'KM' is a worthwhile endeavour is counter to the principles of Design Thinking and futile. Design Thinking ensures that we don't develop 'solutions' without fully understanding what the problem is and why it's a problem. Greg Satell's post on this is a great read http://www.digitaltonto.com/2017/dont-look-for-a-great-idea-look-for-a-good-problem/ I've been convinced for a long time that part of the problem is vocabulary. Rather than invent a new acronym 'KDT', we should promote design thinking skills and techniques as part of existing learning and development processes. Similarly, Systems Thinking; whereby problem solving is addressed holistically.

Design Thinking - not the panacea for innovation?

'What should I title this post?' That is how I used to start writing blog posts. 

Of course if I were to apply design thinking to this problem, the question should be 'what would the reader want to do having read about this topic?' The title would be the last thing, not the first. Since completing a Stanford MOOC on Design Thinking, I've been impressed with the approach. The process is sometimes summarized as: define, research, ideate, prototype, choose, implement, and learn. 

If you are not familiar with Design Thinking, this description from Digital Tonto, will give you a good idea.

'What makes design thinking so effective is its relentless focus on the needs of the end user. Instead of starting with a set of features, it begins by asking what the final experience should be and then works to define a solution. Designers develop products through a series of prototypes and continuously improve and refine them through testing.

So, for example, instead of developing a mobile phone by asking, “what should the keypad look like? A design thinking engineer would start by asking “What does the user want to do with the phone?” In a similar way, a design thinker wouldn’t start designing a doctor’s office by asking where the waiting room should go, but by asking, “what is the purpose of the waiting room?”

As Apple has demonstrated, design thinking can be tremendously helpful when you’re working with mature technologies that are well understood. Unfortunately, they’re not much help when you’re venturing into the unknown to, say, find a new cure for cancer or develop a new approach to artificial intelligence, which may be why Apple has gotten bogged down lately'.

This extract is from Greg Satell's article 'Here's Why Your Innovation Strategy Will Fail'. 

Satell suggests, illustrated with case studies, that a wider variety of 'paths' to innovation are needed. However, many organisations have a single approach, perhaps vested in Research and Development. 

Unsurprisingly, Apple features strongly in the article. It's interesting to consider how Apple set out to disrupt existing technologies and service providers, before considering what product innovations might serve that purpose. As we all know, the iPod, iPhone and iPad resulted. Great examples of design thinking. The big question for Apple is that it's 10 years since their last truly groundbreaking product innovation. It's highly likely that their autonomous vehicle, by the time it's available, won't be the only player and they may already be playing catch-up.

This revealing article on The Verge uses the history of the iPhone development as a lesson in how this disruption was planned by Apple. What innovation path are they using to maintain their preeminence?

Post Script: Another path to innovation I was reminded of is Systems Thinking; an extension of Design Thinking that attempts to take account of the increasingly interconnected and complex world. See https://www.fastcodesign.com/90112320/design-thinking-needs-to-think-bigger

Source: Mapping Innovation by Greg Satchell

Doing Conference Speaking Not Badly - David D'Souza

David D'Souza is without doubt, the most interesting, relaxed and compelling speaker I have heard.
I say heard rather than seen, as on both occasions, he has held the audience's attention for an hour without slides or notes. This is how he does it.

In typically modest style, David calls his post

'Doing Conference Speaking Not Badly'

Recess for workers?

My Knowledge and Innovation Network colleague Steve Dale recently highlighted an excellent article by Greg Satell entitled We need to educate kids for the future, not the past. Here's how...'

The importance of 'recess' (or break time) during the day is as important at work as at school. We are seeing the same erosion of time to socialise with work colleagues as teachers who have to cram timetables to 'get through' the curriculum (my daughter is a teacher). At work, this results in missing opportunities to co-develop ideas, widen personal networks and build relationships. The designers and architects of new-build offices do recognise the importance of social workspace, but this is often not reflected in our work-day calendar. I recall talking to a very senior individual at BP some years ago, who scheduled his entire Friday morning every week, just to informally go and talk to people. Unfortunately few of us can get our PA to ensure our diaries are kept clear like that.

When planning KIN events, especially our quarterly workshops, we carefully design-in the social aspects. The dinner the evening before (a bbq in the summer), an open bar, a fun activity designed to get people connected and an informal, relaxing environment. The significant break times scheduled during the day for networking are inviolate.

Greg's ideas for changing the school system make so much sense. I fear that, like the difficulty of clearing our work diaries to add a 'recess', the demands of educational testing and teaching to outmoded curricula, will meet much resistance.

The depreciating value of human knowledge

Automation is just one facet on the broader spectrum of AI and machine intelligence. Yes, it's going to affect us all (it already is with the increasing emergence of intelligent agents and bots), but I think there is a far deeper issue here that - at least for the majority of people who haven't become immersed in the "AI" meme - is going largely unnoticed. That is, the very nature of human knowledge and how we understand the world. Machines are now doing things that - quite simply - we don't understand, and probably never will. 

I think most of us are familiar with the DIKW model (over-simplification if ever there was), but if you ascribe to this relationship between data, information, knowledge and wisdom, I think the top layers - knowledge and wisdom - are getting compressed by our growing dependencies on the bottom two layers - data and information. What will the DIKW model look like in 20 years time? I'm thinking a barely perceptible "K" and "W" layers!

If you think this is a rather outrageous prediction, I recommend reading this article from David Weinberger, who looks at how machines are rapidly outstripping our puny human abilities to understand them. And it seems we're quite happy with this situation, since being fairly lazy by nature, we're more than happy to let them make complex decisions for us. We just need to feed them the data - and there's plenty of that about! 

This quote from the piece probably best sums it up:

"As long as our computer models instantiated our own ideas, we could preserve the illusion that the world works the way our knowledge —and our models — do. Once computers started to make their own models, and those models surpassed our mental capacity, we lost that comforting assumption. Our machines have made obvious our epistemological limitations, and by providing a corrective, have revealed a truth about the universe. 

The world didn’t happen to be designed, by God or by coincidence, to be knowable by human brains. The nature of the world is closer to the way our network of computers and sensors represent it than how the human mind perceives it. Now that machines are acting independently, we are losing the illusion that the world just happens to be simple enough for us wee creatures to comprehend

We thought knowledge was about finding the order hidden in the chaos. We thought it was about simplifying the world. It looks like we were wrong. Knowing the world may require giving up on understanding it."

Should we be worried? I think so - do you?

Steve Dale

Hail to the Chief - creating faux senior roles is no alternative to a grounded strategy

I've been advising a client that is devising a new knowledge strategy.

Here's a snippet of a recent phone conversation...

Client: 'We're thinking of appointing a Chief Knowledge Officer. We need to show that the strategy has some real clout behind it'.

Me: 'So will this Chief Knowledge Officer have a seat on the main board? If not, how many levels down will the role be positioned?' (The board has only 3 members, CEO, Finance/HR and Operations directors)

Client: 'No, it will be at senior manager level' (that's 3 levels down from the board)

Me: 'I think you should wait to see what the knowledge strategy requires, before creating roles. I'm going to send you an article from a recent Harvard Business Review. Let's have another conversation when you've read it'.

The HBR article I emailed was 'Please Don't Hire a Chief Artificial Intelligence Officer'
I asked my client to simply substitute 'KM' for 'AI' and 'Chief Knowledge Officer' for 'Chief AI Officer'.

Try this yourself with the following paragraph from the article and you'll see why...

'However, I also believe that the effective deployment of AI in the enterprise requires a focus on achieving business goals. Rushing towards an “AI strategy” and hiring someone with technical skills in AI to lead the charge might seem in tune with the current trends, but it ignores the reality that innovation initiatives only succeed when there is a solid understanding of actual business problems and goals. For AI to work in the enterprise, the goals of the enterprise must be the driving force.

This is not what you’ll get if you hire a Chief AI Officer. The very nature of the role aims at bringing the hammer of AI to the nails of whatever problems are lying around. This well-educated, well-paid, and highly motivated individual will comb your organization looking for places to apply AI technologies, effectively making the goal to use AI rather than to solve real problems'.

The problem with creating 'Chiefs' is that they imply clout, but often have none. Witness the number of Chief Knowledge Officer jobs that were created around the turn of the century and how many remain today. I can't think of one. 

Before any roles are created, it's essential that those with real clout understand how organizational learning or knowledge transfer can help them achieve their personal objectives and solve 'actual business problems'. Get that right and you're more than halfway to your strategy. Creating hollow roles are probably unnecessary nails.

Motivating deep experts

Every now and again you hear something that is so simple, you wonder why you hadn't thought of it before. I had one of those moments listening to an superb Knowledge and Innovation Network webinar yesterday. Ian Corbett was presenting on 'Helping experts become catalysts for knowledge and Innovation'. KIN members can see Ian's slides on Memberspace in the Management Buy-in special interest library.

Ian, originally a geologist by trade, has done a lot of research on 'expertise' and is now applying it to charitable education projects in South Africa, where he lives.

The 'aha' moment during Ian's talk came when he was explaining how to get the best from deep experts or technical teams. The defining characteristics are:

1. They value face-to-face interaction (plays to their inner ego)
2. Low tolerance for admin and passing fads
3. They seek innovation, not reuse
4. They want autonomy

Pretty obvious when you think about it eh?

Yet how often do managers acknowledge these simple needs? KIN had a good look at intrinsic motivations at the recent Spring Workshop on Behavioural Economics. Looking at these 4 motivational factors, they might nicely define what intrinsic motivation means for a deep expert.

Next time you are working with a group of experts, what will you do to act on, or at least acknowledge these?

Source: APQC

KIN members can see Ian's slides on Memberspace in the Management Buy-in special interest library.

Facts don't change minds - what we think we know is not what we know

Think you know how a toilet works? This article in New Yorker shows that we really know a lot less than we think. This is noteworthy when considering how knowledge is transferred between 'experts'. It is also shows the importance of communities of practice or networks in validating knowledge. "People believe that they know way more than they actually do. What allows us to persist in this belief is other people. In the case of my toilet, someone else designed it so that I can operate it easily. This is something humans are very good at. We’ve been relying on one another’s expertise ever since we figured out how to hunt together, which was probably a key development in our evolutionary history. So well do we collaborate, Sloman and Fernbach argue, that we can hardly tell where our own understanding ends and others’ begins. One implication of the naturalness with which we divide cognitive labor,” they write, is that there’s “no sharp boundary between one person’s ideas and knowledge” and “those of other members” of the group".

http://www.newyorker.com/magazine/2017/02/27/why-facts-dont-change-our-minds

#failoutloud

KIN has long stressed the importance and power of learning from failure. In this short, funny and revealing post, David D'Souza publicly shares his experience of what not to do in a TV interview.
His post uses humour, it's punchy (note the bullet points) and is in the first-person. I doubt I'll ever be on TV, but everyone could immediately relate to and learn from this.
Now that's real learning from failure - the antithesis of a dry 'lessons learned' report.

David was a speaker at the KIN Winter workshop on 'Organisational knowledge in the era of Machine Intelligence'. You can see the video of David's inspiring talk here.

Innovation; Eureka or Bernard?

Alexander Fleming was by all accounts a brilliant scientist, but poor communicator. His 1935 discovery of penicillin would have gone unnoticed but for Florey and Chain later industrialising its manufacture. The three shared the 1945 Nobel Prize for Chemistry. Great innovations abound where an individual's discovery or invention is capitalised upon by others. 'If I have seen further it is because I have stood on the shoulders of giants*' is often (mis)attributed to Newton.

This trope goes some way to dispelling the 'Eureka!' myth of the lone individual conjoring-up an instant solution in his/her bathtub. In reality, neither the brilliant individual, nor serial or incremental innovators reflect contemporary innovation models. Co-development or collaborative problem-solving, particularly involving diverse sectors, is much more effective.

Last year I hosted a fascinating site-visit to Bletchley Park, the site, now museum, where Britain's secret WW2 code breakers worked. We saw first-hand the importance and effectiveness of diversity in collaboration. Diversity of skills, social backgrounds and crafts all played a part in successfully developing innovations of remarkable importance.

Innovation is Combination is the title of a recent article about by Greg Satell on modern innovation models that transcend organisations or existing networks. As Greg says:

"The 21st century, however, will give rise to a new era of innovation in which we combine not just fundamental elements, but entire fields of endeavor. As Dr. Angel Diaz, IBM’s VP of Cloud Technology & Architecture told me, “We need computer scientists working with cancer scientists, with climate scientists and with experts in many other fields to tackle grand challenges and make large impacts on the world.”

Today, it takes more than just a big idea to innovate. Increasingly, collaboration is becoming a key competitive advantage because you need to combine ideas from widely disparate fields". 

*This phrase is more correctly attributed to a chap prosaically called Bernard of Chartres.

Got a badge? Can I be your friend?

Got a Fitbit or Nike FuelBand? Your employer might soon be asking you to wear one at work.

We live in an ever more connected world and visualising digital connections and interactions is now very easy. However, the most effective networkers instinctively know the importance of building relationships face-to-face. Until now, the only way of mapping those real-world relationships and personal networks has been though survey-based techniques, such as Social Network Analysis (SNA or ONA). Indeed KIN has conducted SNA surveys in the past and will be doing so again this summer.

The advent of cheap, wearable bluetooth or wifi trackers, now gives the opportunity to effortlessly produce sociograms of how teams interact or indeed of entire organisations. Of course there are significant privacy concerns here. Firstly, how do you feel about your movements being tracked in real-time and secondly how will that data be used? Even with assurances of anonymised data and analysis, I'm really not sure I want my bosses tracking my every move. Having said that, they are already doing just that with my 'digital footprint', particularly email and internal messaging.

MIT spin-off Humanyze claims to be working with several large financial and energy companies, mapping employees movement and connections using wearable trackers or 'badges'. They claim network analysis can improve teamwork, collaboration and process optimisation. Some of these programs are being promoted as ways of getting sedentary workers to move around more. If this is the case why not give them a Fitbit?

At least in being asked to wear, and display, a badge, the individual is openly participating in being tracked. I have this amusing/dystopian vision of a badge-wearer I'd rather not be associated with approaching me and hightailing out of there before the system connects us. Conversely, influential and senior people being stalked by 'badgers' wanting to game the system.