Metrics and Innovation KPIs
Making Innovation Success Predictable
1 Innovation process data aggregation 25,000+
2 Innovation-specific performance data
3 Team-specific performance data
4 Episode-related performance, time, and budget data
5 Innovation timeline management
6 Innovation Budget Management
7 Innovation ROI calculation
Only what you can measure, you can manage
Once innovation teams are working creatively on new solutions, thousands of pieces of information get created, including ideas, research, market feedback, and opinion. The innovation metrics could be theoretically aggregated in a spreadsheet, where each item can be voted on, and some formulas can compute values, influence factors, performance indicators, and success probability data. An algorithm for the overall ISI (Innovation Success Indicator) can be applied. Of course, the BlueCallom DEEP Software does exactly that and much more.
A billion-dollar innovation needs predictability
BlueCallom’s AI-driven Innovation KPI Framework
BlueCallom Innovation KPI Framework Data Stack
A data structure that you don’t really see
ISI | Innovation Success Indicator
The ultimate and single KPI of an innovation journey. The ISI is giving managers the success indication of 0% to 95% probability of success. Of course, there is a remaining risk to be considered. The ISI exposes the predictability to be successful in an accuracy that was never achieved so far.
EPI | Episode Performance Indicator
Each innovation journey has various episodes like innovation opportunity discovery, ideation, validation, and so forth. Some of those episodes are better indicators, like customer validation than others. An algorithm computes predictability contribution levels, gives it weight, and adds to the overall ISI.
OPI | Operational Performance Indicator
During the innovation journey time, budget, ROI are important data to navigate a team and those data may change underway, or also the goals may be adjusted as teams need to move forward.
TPI | Task Performance Indicator
Diving deeper into details, EPIs are fed by their respective tasks, ideation, collecting customer feedback, or market research. The system considers quantitative values as well as qualitative values from rating and review processes. The roughly 120 innovation-specific tasks, which are product and industry or customer type, independent, produce roughly 1,200 datapoints with 2,400 values plus cross-correlation data.
LPI | Lateral Performance Indicator
Lateral processes across an entire innovation journey produce another roughly 200 performance data from backward and forward correlations.
UPI | User Performance Indicator
Indicate key insights about the quality of the team in particular the degree of diversity and the strength o their cognitive abilities.
DATA | Innovation relevant performance data
All the above innovation performance-specific xPI data are collected in the background without the team needing to feed any system.
Why are we so sure about the results?
- We know from neuroscience and also from our own experience as entrepreneurs, as well as experiences with startups we guided to groundbreaking innovation in the past years, that creating ideas is neither accidental nor random.
- Based on the understanding, of how our brain composes ideas, we are able to stimulate innovative ideas and come to groundbreaking ideas within four weeks on average. On the contrary, if a team can’t get to a groundbreaking concept within that approximately 4 weeks timeframe, it most likely never will. That makes genuine innovation even more predictable than improvements.
- However, we know that the initial value of an idea is zero. Despite its strategic importance, the value of an idea only grows with its distribution in the market. The duality of brilliant ideation and relentless execution is driving innovation success. One is nothing without the other.