The McKinsey Quarterly reported in October 2008 that 10% of organizations use the number of ideas and concepts in the pipeline as a lead innovation metric.
As an Innovation Consultant, I am often asked by R&D teams if this is an effective measure of success. This blog post will explore this controversial question and explain why I believe it is not the best metric.
When looking at lead innovation metrics, it is important to understand what data they measure. The number of ideas and concepts in the pipeline can be a valuable metric for measuring how much ideation a team is doing, but it does not necessarily reflect how successful those ideas are.
For example, if there are dozens of ideas in the pipeline, but none have been implemented or proven viable, then that data tells us nothing about whether or not those ideas are actually working. Furthermore, if all the ideas are coming from one person or one department—or worse yet, if those same people or departments keep coming up with new ideas without ever implementing them—this could indicate a lack of collaboration and communication across departments that could have negative consequences for innovation within the organization as a whole.
In addition to evaluating existing data points, lead metrics should include qualitative measures such as customer feedback and usage rates.
These metrics provide valuable insight into how well customers are using products and services developed by your team, which can help you identify areas where improvements can be made.
Additionally, customer feedback can provide invaluable insights into how customers perceive your product or service and how likely they are to recommend it to others. Listening to these voices can help you make more informed decisions about which projects should move forward in the pipeline and which should be discarded all together.
The number of ideas and concepts in the pipeline may seem attractive when considering innovation metrics; however, it only provides a limited view into what’s going on within an organization’s R&D department.
To honestly evaluate success rates, organizations must look beyond just numbers to incorporate qualitative data such as customer feedback into their lead metrics strategy. Doing so ensures that innovation teams have access to quantitative and qualitative data points when deciding which projects should move forward—and which ones need more work before they enter production. By considering both sides of the equation when examining lead metrics for success, organizations will be better positioned to make informed decisions about their product launches and ultimately increase their chances for success in today’s competitive market environment.
Ultimately, the pipeline’s number of ideas and concepts is not a reliable lead innovation metric. To truly evaluate success rates, organizations should use qualitative and quantitative data points when considering measuring progress. By doing so, they can make more informed decisions about projects worth pursuing—and which ones might need more time or attention.