Harvard Business Review
MAY 6, 2015
One type is what we call “activity” metrics, which show that you’re busy stoking the boilers of innovation. The other type of metric, an “impact” metric, shows that the ship is actually going somewhere. The five most commonly used metrics were: Revenue generated by new products.
Harvard Business Review
SEPTEMBER 10, 2012
It tends to be short-term, uses familiar (traditional) metrics and development systems like Stage Gate. Almost every company has a Stage Gate process because they work well for incremental innovation. Because consensus and familiar metrics are death to breakthrough. So let's talk about incremental.
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CO2
APRIL 1, 2022
Many corporate visions also don’t provide a clear way to know if you’ve reached your goal because they lack tangible metrics. Bill Gates’ vision for Microsoft (“A computer on every desk and in every home”) would have been a lot less tangible had he written it as: “Becoming a world leader in the software industry.”
CO2
APRIL 1, 2022
Many corporate visions also don’t provide a clear way to know if you’ve reached your goal because they lack tangible metrics. Bill Gates’ vision for Microsoft (“A computer on every desk and in every home”) would have been a lot less tangible had he written it as: “Becoming a world leader in the software industry.”.
Harvard Business Review
JULY 5, 2011
Incremental innovation can be pushed down into the organization where the strategy is clear, decision metrics are understood, and management models like Stage-Gate create a level playing field. So Stage-Gate models can unintentionally kill potentially big ideas. Old models don't work.
Harvard Business Review
MARCH 2, 2018
Establishing appropriate performance metrics and assigning attribution. Sometimes, innovation centers at the front line of human-centered design do not have robust metrics for recognizing incremental but critical successes. Be prepared to revise metrics as the center evolves and celebrate small wins. Acknowledgements.
Harvard Business Review
NOVEMBER 6, 2018
These data scientists design, define, and implement metrics, run and interpret experiments, create dashboards, draw causal inferences, and generate recommendations from modeling and measurement. Data quality and data governance: tools, processes, guidelines to ensure data is correct, gated and monitored, documented, standardized.
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