I had lunch the other day with Joel Trammell, CEO of Khorus and serial Austin entrepreneur. Khorus provides a software based management system for CEOs to optimize the performance and alignment of their organizations. Joel was telling me how his philosophy is to let the people in the functional areas of the organization worry about data. What he tries to get out from the functional leaders on down is predictability and accountability for those predictions. CEO’s and other company leaders are drowning in data, but how is that helping them know how the company is doing relative to its strategic objectives? Forecasting results is a lot more than just data analysis and requires a combination of good data, knowledge of the people in the organization, and comfortable transparency that allows people to provide real information regardless of their position in the corporate hierarchy. Khorus provides a software platform for enabling this information flow throughout the company. People input their forecasts (revenue, product delivery, budget, anything that affects strategic objectives), then they are held accountable via incentive programs and management against those projections. It’s common sense management that provides visibility to the CEO on the reality of what’s happening in the company. Data can be used to inform or to mislead – at the end of the day you need people to be accountable for performance.
Regarding validity of data, I read this article, “Most Scientific Findings Are Wrong or Useless”, that talks about how a lot of the data that scientists use to support their “findings” are either flawed or downright wrong. Its conclusion is that “science isn’t self-correcting, it’s self-destructing.” And this is happening in many corporations as they gain more integration between systems thus access to data. There is nothing wrong with using metrics/data to measure performance and to even predict performance. I call this using trailing edge and leading edge indicators to help measure organizational performance. At the end, data is great for accountability and also useful for driving organizational change. But all data is not useful everywhere in an organization. Make sure it’s accessible to the experts (the people doing the work), then hold them accountable for meeting the targets they have provided.