All ideas are equal… huh? Insight from innovation challenges

It doesn’t matter how many ideas you have:  all ideas have the same likely value.

Sounds counter-intuitive… but take a look at the below.

Rob Spencer, the data scientist at Imaginatik, distilled the chart above from a specific innovation challenge as part of an innovation journey for a Fortune 50 client he is working on.  The data is drawn from a large dataset, with the most prolific author contributing 360 ideas.

What is this telling us?

First – the mechanics of what’s here:

• Idea value = +1 for a positive conclusion and -1 for a negative conclusion.  This isn’t a monetary value – you won’t get realized monetary value at this early ideation stage – but it is a good surrogate for value since it indicates the review team’s commitment to implement.
• The overall average idea value this organization is 0.14 which is quite typical across dozens of similar types of analytics Rob has conducted – e.g., this organization accepts a small fraction of ideas to explore further and rejects the rest.
• Each blue dot is a person, showing how many concluded ideas he/she had and their average value, as measured by material (potential) impact and ‘worth-while to explore’ further.
• The wide orange line is this 0.14 average; the thin orange line is a running average.

Second – what is this telling us?

• Value input is distributed across all ideas; no trend exists between the most prolific contributors (who put in hundreds of ideas) and the most limited contributors (those at the end of the long tail who put in just one or two ideas).

Of interest?  Perhaps.

Not incidentally, this observation challenges two opposing views one sees in the literature of innovation:  some writers think that there are “idea people” who are both more prolific and better, and others suggest that it’s the rare fringe contributor who’s more valuable.   Nope:  all the same!  How prolific you are doesn’t make your ideas better or worse.  And we see the same pattern across job titles.

Of use? Definitely.

The data speaks, and the insight is pragmatic:  it also doesn’t matter where you are in the organization. Whether assistant to innovation senior vice president, on average, the ideas have the same (potential) value.  Hmmm… now that’s noteworthy.

Given what we know about the very consistent long tail of participation in voluntary challenges, this has a powerful conclusion – namely, half of all your ideas – and now we know, half of your value – comes from people who only ever contribute once or twice.  With what implication?  The criticality of playing at scale!  Unless you’re using an efficient, for-for-purpose management system that makes it easy to handle large-scale inputs, you’ll end up throwing away most of your valuable ideas!

Caveat: kindly don’t make the mistake of reading this as “all ideas have the same value.”   They don’t, since there are always good and poor ideas.

• What the data show is that ideas have the same likely (or probable, or à priori) value when they’re binned by contributor effort (head or long tail) or by contributor job title (modest or upper management).  In other words, an idea from a very active participant is just as likely to be useful as one from a rare contributor, or an idea from an Assistant Clerk is just as likely to be useful as one from a Senior Vice President.

Many more data-based insights coming soon!

Look who’s talking… and why it matters

A colleague and I had drinks the other night with the head of innovation from one of America’s largest, and most prestigious corporate banks. They, like, many are dabbling in innovation – having set up a small dedicated team in service to catalyzing new sources of revenue and profitable growth with their corporate clients.  It’s a global bank with a vast array of talents at all levels of the organization – well-honed to how they have done work for decades.  Of all the lessons she has learned, and results she has already catalyzed – leading to a much more material investment and focus from corporate – she bluntly put it out there and said, “you know, innovation is nothing but a talent management challenge, and opportunity.’

*That* is interesting.

And insightful.

After all, what are businesses but sets of practices and capabilities – codified into products and services, technologies and assets, derived from once tacit knowledge – insight that, over time, got honed into productive practices and capabilities.

So, of course, from one perspective, innovation *is* nothing but a talent management challenge – and opportunity.

Hence the need to figure out how to get folks engaged in all aspects of innovation – and hence all the ink spilled and energy expended on how to create a ‘culture of sustainable innovation’ and how to ‘unleash the creative potential of our employees’ and so many other fluffy calls of need.

Let’s ground this, around one specific tangible and pragmatic expression of engagement.  A previous post discussed the long tail of participation along an innovation journey and the analytic-based observation that an idea from a very active participant is just as likely to be useful as one from a rare contributor, or an idea from an Assistant Clerk is just as likely to be useful as one from a Senior Vice President.  The single point here is that importance to take another look at the data – to ‘see who’s talking to whom, about what.’

The images above are drawn from two different companies in differing industries.  What is interesting is to see patterns of engagement around specific ideas that get built on, that groups emerge from people working on the same ideas from different parts of the organization (and outside the organization, but we’ll get to that)., and that new collaborations can be identified (and hence nurtured) with the larger dots and lines depicting the most frequent contributors.

In these particular cases, the pattern on the left tells us that this organization is extremely ‘cliquey’ – people don’t collaborate outside of their own teams.  They would benefit by some coaching and motivation to increase cross-fertilization – with help breaking down the far-too-typical silos.   In contrast, the one in the middle is *too* collaborative – with everyone talking with everyone else.   They probably need to stop gabbing, make some crisp decisions and move to implementation.  And the one on the right? A nice balance of focus and attention building upon a set of ideas across teams.

So what?  Insight into patterns of engagement and ‘traceable’ capabilities to highlight who talks with whom, about what, from where – in service to honing tacit ideas into possible new sets of business practices and assets with great impact.   Productive and wasteful patterns of collaboration exist; patterns that insightful managers and leaders will come to know, and ‘nudge’ directionally towards greater impact.

We’re working with a pharma company with a clear need: find out who is working on a set of molecules not only within their company but also within their network of universities and biotech firms.  Sounds simple?  To state, yes.  To execute on, hardly.  But critical to do – given the urgency to figure out how to reduce the risk and increase the speed through clinical trials.  How? By ‘reducing the risk of time through better search – find – connect’ across experts both inside and outside the global company’s walls.

Look who’s talking now!

It’s about the lines, not the nodes: changing what to look at, and why

I was speaking with someone on my team the other day… we’re working on a big hairy audacious project to support a global roll-out into over 10 countries, based on sophisticated mathematical modeling (underlying the products) and significantly different environments to which the products, technologies, processes, governance and, ok, lots of other stuff needs to be adapted to “fit.”  We’ve been working with “deep experts” in a variety of fields, globally and this person, let’s call her Nell, was intimidated.  “Jump in – and guide the discussion,” I encouraged her.  “But I don’t have the expertise any of these people have,” was her response. 

“So what” on big data – more musings

SO much attention on micro-segmentation may be going down the wrong path.  Sure, the principle that we need MORE data to understand LESS – e.g., specific behaviors – is one of the wonderful ironies, and value, of so-called big data.  HOWEVER, the implication of this need not be to “create micro-segments” as an end in itself, as a blunt hammer.  The challenging, yet important, question is: how do I configure my discrete assets in ways that drive value.  The creation of thousands of micro-segments to support an equal number of customer experiences should, arguably, not be an end in itself.  Granted, it may be an important thing to do operationally.  Yet, it may not offer sustainable value over time…  despite this “creation of thousands of personal experiences” has become arguably *the* hot strategic topic of the day.  Rather, we might want to step back to complement the flurry of activity and ask a simple question: what is it that my customers are doing with me, and what is it they want to do –that “objectives” thing.