Traditional business intelligence has been focused on knowledge creation. If it were a species, you might envision it feeding on raw data, digesting that raw data into information and then information into knowledge, and producing beautiful blooms in the form of visual representations of that knowledge. We use the visualizations and the knowledge itself to help us understand the past and the present, and to make decisions about the future.
As raw data becomes more abundant, more comprehensive, and of higher quality, business intelligence produces even more knowledge. But does more mean better? As the quality and comprehensiveness of raw data improves and even more knowledge is created, do the decisions that people make get correspondingly better? Not necessarily. Many people have difficulty telling the difference between useful and irrelevant knowledge. If the additional knowledge created is irrelevant, it simply adds noise and confusion that can hamper someone’s ability to make the right decision.
Business intelligence today has evolved beyond knowledge creation of what has happened in the past, to analytics and forecasting what might happen in the future. We’ve moved from reporting to analytics, which enables faster decision making at all levels of the organization (see Views from Spotfire’s Mark Lorion). We’ve added data mining, which is able to distinguish between relevant and irrelevant information, so that people don’t have to make that decision. We’ve also added predictive models and other forecasting tools, which evaluate any number of possible future outcomes and guide us towards the optimal decision.
Darwin said, “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptive to change.” This not only applies to the evolution of a species, but also to the evolution of business intelligence. The business intelligence that survives will need to do more than just evaluate all the possible outcomes to help determine the best answer. It will need to learn how to adapt to changes in the marketplace, and use that learning to improve future recommendations. It will need to learn how to improve on its own. Once it reaches that point, will business intelligence have acquired the ability to evolve by itself? Because of the speed at which it operates, will business intelligence be able to evolve faster on its own than at the hands of humans? Only time will tell!
Steve McDonnell
Spotfire Blogging Team