The problem with measuring innovation is that you can’t measure innovation. This makes it a difficult thing to manage.

Now obviously, organisations figure out ways to measure how innovative they are – but they usually doing it by finding metrics that approximate some part of the innovation process. The fact that our metrics are all proxies leads to problems when we forget that they are only substitutes for what we are really interested in measuring, not the thing itself.

I ran across an example of this split between the measure and what we care about today when I was looking at twitalyzer. It’s a really nice free twitter analytics site that measures several things: your influence, your signal to noise ratio, your generosity (how frequently you cite other people), your velocity (how frequently you tweet) and your clout (ability to spur people to action). Influence is a composite measure that includes your clout, velocity and generosity, plus how often you are retweeted, and the number of followers that you have on twitter. It’s the last part of the measure that leads to potential trouble.

Getting followers on twitter is interesting. One strategy is to post interesting stuff for an extended period of time, and letting people find you (generosity, signal/noise and velocity all help with this). The problem with this is that it takes time. A faster way is to be famous. However, that’s not so easy. The easiest way to get followers is to follow a whole lot of people, and count on the web’s tendency towards reciprocity to work in your favour.

The problem with this is that you end up following a lot of people, which for me at least creates some difficulties. For me, twitter is a great information stream – it is part of my aggregating strategy. It helps me find innovation news and viewpoints that I don’t pick up in my rss feed from blogs. The problem with following lots of people is that this makes filtering impossible. There are tools that make it easier to manage large numbers of people that you follow – but they all work on the same principle – ignore most of them. Which means that if I do that, I’m not connecting.

My twitter strategy is to use it as part of my larger aggregate, filter & connect strategy. But if I try to manage the metric – ‘influence’ – I have to collect a lot of followers, which actually makes it harder to execute my strategy. This illustrates the problem with mistaking a metric like influence with what you actually want to accomplish.

The same thing happens when we manage innovation. One of the most common measures of innovativeness is patents. But no one actually needs patents – they need the things that patents somtimes provide – a competitive edge from exclusivity, monopoly profits, or the development of unique products. If we spend too much time managing the metric, we might not achieve the outcomes (profits, market share, etc.) that we really want.

How can we fix this? There are few things we can do:

• Don’t mistake the metrics for the thing we really care about – constantly remind yourself that since we can’t measure innovation directly, the metrics that we use are approximations, not the actual thing that we care about.
• Use multiple metrics – one way around this problem is to use multiple measures for innovation. There are many possible measures – how much we’re investing in generating ideas, how many new products/services/process improvements we actually introduce, profits from new products/services, senior management time devoted to innovation, innovation porftolio balance (both distribution of innovation efforts over time scales, and across the incremental-radical spectrum), and so on. Scott Anthony has done some outstanding work in this area, which he summarises here.
• Make sure that your innovation metrics are tied to your strategy – Think about what you are trying to accomplish, and make sure that your metrics measure actions that will contribute to the outcomes that you are trying to achieve.

Measuring innovation is one of the hardest parts of managing innovation. Avoid the trap of thinking that your innovation metrics measure innovation directly to make the process a little bit easier.

(picture from flickr/aussiegall – CC licensed)