We’ve spoken in depth about the importance of monitoring the results of your projects. For R&D and innovation projects, this is especially important, as they can easily be mistaken as ‘cost centres’ without adequate proof that they’re delivering results.
When proving a project's value, assigning metrics is a great way to communicate and understand the value that's being generated. Unfortunately, this can often seem difficult, especially when the benefits provided by projects are more towards the ‘intangible’ side of the spectrum.
That’s why when managing multiple R&D or innovation projects, we would recommend first deciding on an innovation metrics framework.
It’s not just communicating and understanding value that’s a valuable use of a metrics framework. By achieving this, we unlock so much more. As this Arthur D Little report explains: innovation metrics drive change by:
As you can see, the advantages of implementing innovation metrics are far reaching. An innovation metrics framework therefore should be a priority if you’re running multiple innovation or R&D projects.
In order to decide on what makes an effective innovation metric, we need to first distil what the purpose of innovation metrics are, and where they’re going to be used.
We’ve already looked at what the advantages are. By identifying which of these is a priority, we can decide on the purpose. Based on the advantages previously mentioned, the purpose of innovation metrics may be to:
In this article from Mckinsey, they explain that effective R&D metrics (which are comparable to innovation metrics) should strive to ‘measure what R&D influences within the sphere of factors that R&D can influence’. Essentially we’re saying that innovation metrics need to relate to what is in the power of the innovation department to improve. Innovation is inherently risky, so measuring the success of projects alone can be counter productive. Instead, we should look at the effectiveness of the process - rather than say whether risky innovation projects become successful.
The same article from Mckinsey presents a comprehensive formula for assessing the productivity of an R&D department - which could theoretically be repurposed for an innovation department.
The formula considers output, based on gross contribution in innovation product benefits, multiplied by the achieved product maturity. This figure is then divided by costs of R&D to give a total productivity figure.
Though this formula is effective for measuring the productivity of an innovation or R&D department in pure economic terms, it misses some of the less tangible benefits that could be considered. Other metrics that may be employed to capture these benefits may look at things such as:
In this regard, the formula is useful for assessing productivity, and therefore should be a good starting point for an innovation metrics framework. Having said this, it should be considered alongside other metrics, which consider a larger array of an organisation's objectives.
When taking into account a greater variety of metrics, one effective approach is to use what we call the balanced scorecard method. A balanced scorecard tracks a variety of different metrics, with each metric assigned a weighting. These metrics can then be aggregated, according to weighting. By using this method, we can then calculate a ‘North Star Metric’, which we’ve explained in another article.
The advantage of using this method is that you can define the scorecards metrics and each weighting according to your organisation's objectives. By doing this, you can ensure that your ‘North Star Metric’ best resembles your organisation’s overarching strategy, taking into account all relevant aspects. Also, by deducing a North Star Metric, individuals outside your innovation department can easily understand with one metric, how effective your innovation department is performing.
When defining metrics, we would suggest drawing on the tried and tested ‘Inputs vs Outputs’, in relation to each aspect which is being measured. This allows each aspect's performance to be measured with context, providing indications on which areas may be over or underperforming in relation to resource dedication.
Building an effective innovation metrics framework which captures the innovation departments results in relation to the organisation’s efforts is no simple task. It will likely take multiple iterations, and should evolve over time along with organisational direction.
To make a strong start, we would suggest first liaising with key stakeholders, and gaining their perspectives on what metrics would be valuable for them. By considering their opinions from the outset, you’re maximising the chances that the first iteration will be as close to an accurate representation. It will then be a case of continually testing the framework with different types of projects and gaining feedback from key individuals. Once you have a framework that all key stakeholders can agree upon, you can begin implementing it within your department.