Measuring open innovation
Innovation is without doubt a big deal, with many companies spending anywhere from 7-15% of their turnover on it. With many millions riding on this, it’s paramount that we have a strong idea of how to determine between success and failure. And this is not something that many do well. A BCG study back in 2007 found just 37% of executives reporting happiness with their innovation measurement.
It can often appear as though organisations focus purely on the I of ROI, with the Return aspect left largely to chance. It is however certainly possible to produce various metrics throughout the innovation process, from the number of entries, the finalists produced, and of course the commercial outcomes of the project. It should also be possible to compare the costs of innovating via the crowdsourced route vs more traditional avenues.
Suffice to say however, that this is far from the norm. The BCG study highlighted earlier found that 71% of firms used money spent as their primary innovation metric. Even those that do measure more only used on average 5 distinct metrics.
Now, make no mistake, measuring innovation is very hard. On one side you have fuzzy benefits such as increases in share price or knowledge assets. Maybe customer loyalty increases or your brand awareness improves. Perhaps even employee engagement will rise as a result of innovation. On the flip side, the implementation of innovation often see resources pulled from other departments, making attribution of costs somewhat trickier.
This should not undermine the importance of measuring what you do however, for the application of robust innovation metrics can help to support a more organised and systematic approach to the whole process, which will hopefully see a better return than the 10% suggested by some studies.
Whilst traditional metrics such as R&D spend or number of patents filed may have been appropriate in the past, the new world of open innovation requires metrics that are tailored to this specific environment.
Ernst & Young have build a measurement framework for open innovation based upon three distinct principles.
- Use unique metrics for each open innovation method – It perhaps goes without saying that the metrics you select should vary depending on the type of project you run, and the method you utilise. So if your project is designed to generate ideas it will require different metrics to one designed to discover new talent. Likewise, they advocate different metrics for different approaches, so for instance contest based projects will have a different means of measurement to the kind of open searches typified by Innocentive projects.
- Consider different types of measures for input > process > output > outcome – these should all be linked together, ideally to a core organisational KPI, with each distinct measure leading naturally onto the next. So for instance, input metrics might measure the resources that are invested into the project. Process metrics by contrast will look at how effective inputs are converted to outputs, which are then measured in the next KPI in the form of ideas generated or patents filed. The final outcome based KPI then determines the financial value of the outputs to the business.
- Consider how to utilize your open innovation metrics – it
should hopefully go without saying that simply measuring is but half of
the challenge. It’s crucial that these insights are then put to good
use. Pelz suggests three distinct levels of utilisation:
- Instrumental use – which suggests that metrics are used directly for decision making
- Conceptual use – which suggests that a metric is used more for general enlightenment than concrete action
- Symbolic use – which suggests that a metric is used to justify decision making
This framework gives organisations a nice model with which to apply their own means of measurement, depending upon the goals of their specific project.Original post