In today's interconnected world we have no lack of facts, statistics and data to help us make business decisions. This abundance however, can be confusing as we try to find insights about our customers and markets. We can simplify things through a better understanding of data types. Lets take a look at the basics ones:
1. Raw data:
Raw data consists of facts and figures that are single points of reference. For example, a car manufacturer can get all kinds of data about how many cars there are, how many people drive cars, and how long a tire lasts.
2. Information:
We produce information when we structure raw data in a way that gives it meaning. For example, we can combine data about people who bought cars this year with the types of cars sold to find out which people are buying which kinds of cars.
3. Intelligence:
Intelligence is information processed in a way that allows observations, reveals trends, or derives conclusions about a data set. Intelligence reduces the number of variables and allows us to make better choices by recognizing patterns. In our car example, we may see that many people in their fifties and sixties prefer SUVs. When we look at them as a segmented group, we may find many younger grandparents who like the roominess of SUVs for taking their grandchildren places--a possible pattern or trend.
4. Insight:
Insight involves the richest, most productive output from a data set. We receive insights at a deeper level. Often bypassing analysis, insights are usually felt to be true before being proven so. They come from a deep understanding of a system's behavior, one that goes beyond the data and relies on experience. However, before becoming part of the data set, insights must be tested to ensure that they are supported by the data. For example, we may have the insight that a step is needed on the passenger side of the SUV. Analysis of the data would show that younger grandparents are likely to have elderly parents with limited mobility who find it hard to climb up into SUVs. The step allows grandparents to choose an SUV to benefit their grandchildren without ignoring the needs of their own parents--a killer feature that might differentiate this vehicle from the rest of the market.
Many people can handle the first three levels of data management, but insight is crucial for growth. In commoditized markets, the data set usually holds the secret to differentiation.
Insight is the "secret weapon" of the information age. In business, this secret weapon can be the key differentiator to optimum customer experiences and ultimately, to increased loyalty. The goal must be to gain insight from data sets that clarify what our customers value most.