Four Groups

Following on from a discussion on Linkedin, Steven Forth, co-founder at Nugg recently asked the following:

Are there also analytics than can let teams know, in advance, that a project is likely to fall behind or fail?

This question gets to the heart of the recent ideas around predictive team analytics and the notion of a ‘Physics of People‘. It also follows on from another piece from Steven where he wrote:

Emotions matter and teams need to have some form of empathy. Not something software is generally good at, so we need to find ways to compensate for this.

In addition to the points raised by Steven is research from Harvard, MIT and others, pointing to the fact that 10 – 40% of team performance is determined by psychological factors such as empathy, relational cohesion and the nature of interpersonal communication.

Predicting Team Performance

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A recent post by Om Malik (here) sets about dissecting the recent departure of JC Penney CEO Ron Johnson after only two years in the job. Formerly the head of retail for Apple; clearly it was expected that he would be able to bring some of the Apple retail magic to JC Penney. Malik’s assertion that spectacular success is as much down to the collective efforts of groups and contextual factors as it is the ability of key individuals to drive things forward reminds me of Bill Taylor’s HBR article (here) questioning the emphasis organisations place on “superstars”. At the time Taylor’s article generated a huge (mostly negative) response. However, I’m starting to think that the unquestioning belief in the “we only hire the best” mantra is rapidly losing its allure.

The notion of the superstar is a beguiling one but unfortunately for corporate HR departments, it is an overly simplistic view. Surely, success has far much more to do with more complex variables such as; working environment, culture, relationships and other contextual factors than with the brilliance of a few key employees. As Boris Groysberg wrote (here) we really are fooling ourselves if we think that success can attributed to the abilities of talented individuals. In short, to transform any poorly performing group or organisation, requires far more than the parachuting in of someone with a great track record in a completely different environment.

I’ve been thinking a lot about the value of actionable and predictive team analytics recently and a post from Naomi Bloom struck a chord.

From her piece:

Analytics — what types of actionable, embedded, and/or predictive analytics with what types of visualizations, e.g. network analyses is becoming quite prominent when organizations try to figure out what roles and individuals have the greatest business impact? And I should emphasize here that this is about getting real insight to decision-makers in a form they can use when they’re in the middle of making that decision rather than just having a wonderful report-writer or business intelligence solution with which they can figure out the questions and search for the answers. Please note that I haven’t treated so-called “big data” as a separate topic (although everyone’s calling anything big data at the moment) because the real goal is actionable, ideally predictive, analytics, for which the management of big data is a necessary but not sufficient capabilities.

The significance of actionable and predictive team analytics cannot be understated. Tools that offer decision makers simple, actionable, valuable and consistent advice is key. Additionally, these capabilities have arguably been missing from the practice of anyone wanting to improve the engagement, well-being and performance of their staff or team members.

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Based on the recent comments from Stowe and Justin, the idea of a Physics of People is both valuable and represents something potentially unique. Given that the idea has the potential to transform business, the following post outlines the five criteria by which any transformation might take place.

A Starting Assumption

Although there is no shortage of models, assessments, psychometrics and techniques that help raise self awareness and provide insights, none offer predictions about people that are either regular or reliable enough to be used on a widespread basis.

The large number of tests, models and approaches is evidence of this. If a particular tool did provide useful and reliable predictions that improved understanding and decision making, then it’s usage and popularity would increase over time. Given that the vast majority of techniques and approaches have been on the market for 20 or 30 years plus, this is ample time for a consensus or market leader to have emerged with these qualities.

The other example that illustrates this assumption is the perception that HR doesn’t add value to the business. There is no shortage of commentary around this and in many cases, this line of reasoning has persisted since the Personnel Department was renamed Human Resources. The fact that HR can’t call on any widely used method or approach that offers reliable and actionable predictions and insights about people is probably one of the reason’s for this current perception of HR.

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I was interviewed by Justin Kirby on the subject of Socialogy last week.

Justin and I had previously collaborated on Collaborative Innovation on behalf of Nesta.

The interview runs to about 20 minutes and the main topics we covered were as follows:

• Four Groups’ 4G methodology and human capital management software platform
• The 5 factors required for business transformation, i.e.
  • Simple to explain
  • Scalable and predictable
  • Changes to people’s jobs
  • A return on investment (ROI)
  • External validation
• The use of these 5 factors of existing innovations versus Social Business
• Stowe Boyd’s ‘Physics of People’ and the holy grail of predicting behaviours

Listen to the interview below.

Despite the fact that the term ‘peopleware’ was first coined in 1977 and a book by the same name was published in 1987, there is little contemporary mention of peopleware today in social business circles. With this in mind, there was an interesting call for the need to balance the software tools of social business with ‘peopleware’ via Jamie Notter recently.

From Jamie’s piece:

Today’s environment requires speed, which, in turn, requires the people and departments in your organization to collaborate effectively. Friction there slows everything down. We put up with that in the past and did okay, but the same won’t be true moving forward for a real social business. So I think as leaders start paying attention to what “social business” means, they will start to employ tools that enable better collaboration, both inside and outside the organization.

As the use of social business tools increase the speed of change, interactions and collaboration, previously hidden inefficiencies and communication problems are going to be discovered. It doesn’t matter how these inefficiencies are discovered (social network analysis, project delays, employee feedback etc.), the point is what to do about them.

Jamie believes that organisations will turn to more software tools but that the software tools themselves won’t resolve these frictions.

But I have a prediction: [companies] will over-rely on technology to solve this problem. The tools are becoming increasingly sophisticated and easy to use. So by all means, jump into those tools, but also recognize this: online tools won’t solve your silo issue. Collaboration software alone is not going to resolve conflict.

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Further to Stowe Boyd’s piece Socialogy and a Scientifically-Grounded Understanding of People and his Physics of People tag, I’ve been thinking about other people’s thoughts and ideas on the subject. What does the idea of a ‘Physics of People’ consist of and how it might take shape? The following extracts and quotes chart the thinking and writing on the subject over the past ten years or so.

Starting Points for a ‘Physics of People’

Cynefin

The first idea that I’m aware of comes from an article in the IBM Systems Journal. Written in 2003 by Cynthia Kurtz and Dave Snowden, the following extract is an initial call for a ‘Physics of People’, along with the recognition of the challenge involved:

We would like (but do not expect) to see simulations of human behavior able to encompass multiple dynamic individual and collective identities acting simultaneously and representing all aspects of perception, decision-making, and action.

This quote really leaves nothing on the table, conjuring up the idea of an omnipotent, all-knowing reality. Whilst this has an unmistakable element of ‘Big Brother’ within it, it’s also reassuring to know that physics itself seeks an understanding of reality that is equally, if not more profound.

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Stowe Boyd is starting some interesting research into what he’s called Socialogy. Stowe defines Socialogy as “The theory and practice behind social business, its tools and techniques, and their impact on business culture, structure, operations, and people.”

From the piece:

I am going to be talking with a lot of researchers, visionaries, and practitioners who are working to push business into the 21st century, and to explore their ideas about moving onto a philosophy of business grounded in what we know about the human mind, social networks, and the emergent behaviors of connected groups.

In the series, I pose one question to my guests consistently: ‘How do you think a scientifically-grounded understanding of people as social beings will change business in the future and how?’

Incidently, Socialogy isn’t the first term that Stowe’s coined – he’s the originator of the term ‘hashtag‘ and also coined ‘social tools‘ back in 1999 so it will be interesting to see how this new term does.

Socialogy and the Potential to Transform Business

Given Stowe’s question, I thought I’d have a go at answering this from the perspective of Four Groups.

A scientifically-grounded understanding of people, such as 4G, has the potential to change business in hugely profound ways, perhaps on a scale comparable to the industrial revolution, the introduction of the PC or the rise of the internet.

Such a statement is naturally loaded with many assumptions and implications, so it’s worth exploring both in further detail.

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Team deficiency accounts for startup failure almost 33% of the time, as reported by ChubbyBrain and Bruce Lynn. Although the original research includes 32 failed companies, it’s important to be cautious given the likely possibility of sample bias.

From the research:

Failure post-mortems often lamented that “I wish we had a CTO from the start, or wished that the startup had “a founder that loved the business aspect of things”.  In some cases, the founding team wished they had more checks and balances.  As Nouncers founder stated, “This brings me back to the underlying problem I didn’t have a partner to balance me out and provide sanity checks for business and technology decisions made.”  Wesabe founder also stated that he was the sole and quite stubborn decision maker for much of the enterprises life, and therefore he can blame no one but himself for the failures of Wesabe. Team deficiencies were given as a reason for startup failure almost 1/3 of the time.

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