Most people are familiar with Darwinism. We’ve all heard the term survival of the fittest. There is even a humorous take on the subject with the annual Darwin Awards, given to those individuals who have removed themselves from the gene pool through, shall we say, less than intelligent choices.
Businesses go through ups and downs, transformations, up-sizing/down-sizing, centralization/ decentralization, etc. In other words, they are trying to adapt to the current and future events in order to grow. Just as in the animal kingdom, some will survive and dominate, some will not fare as well. In today’s challenging business environment, while many are trying to merely survive, others are prospering, growing and dominating.
So what makes the difference between being the king of the jungle or being prey? The ability to make the right decisions in the face of uncertainty. This is often easier said than done. However, at the core of making the best decisions is making sure you have the right data. That brings us back to the topic at hand: Data Darwinism. Data Darwinism can be defined as:
“The practice of using an organization’s data to survive, adapt, compete and innovate in a constantly changing and increasingly competitive business environment.”
When asked to assess where they are on the Data Darwinism continuum, many companies will say that they are at the top of the food chain, that they are very fast at getting data to make decisions, that they don’t see data as a problem, etc. However, when truly asked to objectively evaluate their situation, they often come up with a very different, and often frightening, picture.
It’s as simple as looking at your behavior when dealing with data:
If you find yourself exhibiting more of the behaviors on the left side of the picture above, you might be a candidate for the next Data Darwin Awards.
Check back for the next installment of this series “Data Darwinism – Capabilities that Provide a Competitive Advantage.”
Tagged: analytics, BI, Business Intelligence, data, data analysis, data darwinism, Data Governance, data integration, data management, Data Quality, EIM, enterprise information management, predictive analytics, reporting
