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Data vs. Information vs. Insight

During a recent presentation I was asked a central question of analytics… What is the difference between data, information and insight? For those who work in the analytics domain this seems like an odd question because we have become so fluent in these concepts. For many of us, the idea that some people don’t ‘get it’ seems odd. The truth, however, is that these terms often get used interchangeably in the general lexicon. As such, these questions are extremely valid and very important to answer.

Data is the raw numbers that we capture according to some agreed to standards. Having consistent standards is very important since having data recorded according to different standards can be extremely problematic. For example, there is the age old question of how long is a piece of string? The answer depends on what measurement standard you are using. If we use the Metric system we may come up with some number. That number can vary depending on if we are using meters, centimeters, or millimeters. Using British Imperial/US Customary units will result in an entirely different number. As such, one of the most important steps in any analytics effort is defining standards we are applying. When doing analytics projects, one of our first tasks is to go through the client’s current data structure and normalize that data. In other words, we make sure that all the like things are being measured in the same way.

Information is a collection of data points that we can use to understand something about the thing being measured. Going back to our string example, let’s say we have 100 pieces of string that have been produced by our company. We have agreed to measure them in centimeters and to record the length of each of those pieces of string. Each measurement is considered a data point. Taken together, however, all these data points provide some very useful information. For example, if we need all the pieces of string to be 10 cm long, but many of them are not, we then know that something is not quite right with our process and we might need to take some action to address this issue. How do we know what actions to take? For that we need insights.

Insight is gained by analyzing data and information to understand what is going on with the particular situation or phenomena. The insight can then be used to make better business decisions. Going back to our pieces of string, if we know that our pieces of string are not what we want, we now have to analyze the data to determine what actions to take. So for example, if we find that our mean (i.e., average) length of string is 9.5 cm we now know that our strings tend to be shorter than we want. To make the right business decisions, we need to know how consistently our process produces these pieces of string. To find that out we look at how much variance there is in the data, as well as the upper and lower limits of our outputs. One approach is to look at the standard deviation, which is a statistic that tells us the average amount by which the various measures deviate from the mean. If we found in this case that our standard deviation was say .25 cm we know that even though the strings are too short, they are fairly consistent. Our insight might be that while our process is not what we want it to be it is doing things the same way most of the time.

Now we can look at our upper and lower limits to see what our longest and shortest piece of strings are. Let’s say we find that our longest piece of string is only 9.75 cm and our shortest is only 9.35 cm, this would mean that there is a pretty good chance that our process for producing the pieces of string are simply cutting them too short. This insight is that we need to check our machine and adjust where and when it cuts. Since not all the pieces of string are coming out the same size, however, we know that there are other issues that may be driving out process not being what we want. To address those we need to gather more data after we make our change, compile that data into new information, the analyze it to gain new insights until we can make the necessary business decisions to drive our desired outcomes.

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About the Author

Jimmy Brown, Ph.D. is a senior level management consultant with eighteen years of experience leading efforts to develop and implement practical strategies for business performance improvement. Dr. Brown has held senior level consulting positions at leading firms such as Booz-Allen & Hamilton, Accenture and Hewlett-Packard.

He can be reached at www.jimmybrownphd.com or via Twitter @jimmybrownphd