Wednesday, 30 November 2011

‘Not Everything That Matters Can Be Measured’

What’s the point of innovation performance metrics?

‘How should I tell my boss to measure my teams performance?’  This is a question I was asked by a client recently appointed to head an innovation incubator team within a large multinational.  It’s a pretty good question. 

She wanted to establish the ground rules before her sponsors designed the metrics for her.  This was a smart move, we all know how difficult it is to measure anything but ‘near to launch’ innovation.  The further away, the more risky or the more ambiguous the innovation the more dangerous innovation metrics can be.  The situation was exacerbated by the mixed portfolio of ideas, each subject to different technology, regulation, state of market development – a complex and dynamic innovation challenge.

So, to help with my clients quest I took soundings from innovation leaders managing multiple probes, partners and projects.  They were pleased to help and keen to hear my conclusions. 

For such a critical question I’d have expected to hear a well-worn measurement methodology.  I was disappointed.  I was searching for something that doesn't exist – there is no winning formula or established convention for measuring long-term innovation bets.  But there are a couple of perspectives on the subject my client did find very helpful – two golden principles in the absence of a silver bullet!

Golden Principle #1:  Manage expectations fast

Most holders of purse strings know it’s damn difficult to put hard measures to soft concepts.  But many haven’t heard a cogent argument as to why, so they just keep asking for the usual NPV or DCF analysis, you waste time cooking up easily gamed numbers that both parties have little faith in.  So here are my arguments that make a tame puppy of that scratchy beast of a finance director:

1.   There’s a double uncertainty to measuring ‘over the horizon’ innovation.  Discounted cash analysis often paints an optimistic picture as it measures an uncertain upside versus steady state finances – but as we all know if we don't innovate our state will be anything but steady – at best uncertain, but probably declining.  Conventional accounting isn’t built to handle this much uncertainty

2.   Large corporates demand big results from incubator programs.  There are a lot of zeros flying around.  But this isn’t how big innovation is born, most game changing innovation starts small, ugly and unrecognisable – it certainly doesn't have big numbers to begin with.

3.   Corporate accounting favours sweating existing assets – and why not?  But existing assets (people, factories, technologies) are unlikely to give birth to great innovation.  Newcomers are unencumbered, they will account for the optimal asset at marginal cost.  This is very efficient and will enable small players to make much gutsier decisions like supertanker corporations.

4.   Every business and every innovation project is different.  For instance it’s unlikely that Option Based Pricing (how much does it cost to get to the next decision) advocated by some in the pharmaceutical world (where project stages are long, well defined and accurately priced) are going to be much use in the frenetic world of say food and beverage innovation.  There is a real opportunity cost to measuring the immeasurable!

Golden Principle #2:  Metrics are for Dialogue

So if there is no metric that can accurately measure the return on incubator investment what can we do?  Fortunately the answer is simple – it's not the solution your boss might want to hear but’s it's a good answer nonetheless.  The point of incubator innovation metrics is to promote dialogue, to start valuable conversation.  Simple as that.  Kicking the tires on an idea is a priceless activity for senior management to engage in with incubator teams.   It is simple and imperfect metrics that will drive this to happen, whereas relying on seemingly accurate measures merely serves to distance incubators from sponsors.   Here are six different types of innovation incubator metrics that could form a balanced framework.  Maybe you’ll spend your time discussing better ideas, not cleverer measures?

1.   The ‘No Math’ Approach.  One big target number and one non-risk adjusted pipeline value.   If the pipeline value is 10 times the target then maybe that’s good enough.  Very simple, very fast.

2.   Risk Adjusted Valuation.  The standard innovation metric.  Working backwards from the desired financial outcome and factoring for anticipated innovation failure do we have enough probes and projects today?  Are we kissing enough frogs?  Working this through with a client recently we were able to quickly show that we needed five times the size of pipeline to hit our clients objectives.  Unwelcome but important news.

3.   Fast Faking Metrics.  How quickly are we prototyping ideas, moving them on or rejecting them?  You could measure idea ‘flow speed’ or conversely how ‘sticky’ the pipeline is – like unsold inventory there’s a cost to stalled ideas.

4.   Foundation Metrics.  Track a limited number of drivers, or precursors of success.  Instead of spending time measuring say the value of a solar panel innovation project, instead track the drivers of solar panel growth; new home construction, changes in technology efficiency, government legislation etc.  Focusing metrics on conditions for success forces us to exercise judgment muscles around the concept itself.  

5.   Skin In The Game Metrics.  Allow the intuition (ie the sum of all experience) of wise heads to score your innovation.  Ask the Incubator team to ‘buy in’ to options (real cash must change hands).   The Financial Services sector likes predictive markets - trading ideas using a virtual currency.  GE pushes many of it’s probes to JV calculating this will ‘prove them out’ better than actuarial techniques.

6.   Incubator Health Metrics.  How engaged are the team?  What is their reputation?  What’s the ratio of the team’s ‘useful time’ to ‘form filling, courses and reporting’? How many unsolicited job applications?  Boeing rate ‘how often the incubator asks for help’ as one of their most useful and telling measures.

(Thanks to my colleague Tobias Rooney who helped me build this post)