Most of the talk surrounding big data involves how to derive insight from all that analytics. But then what? What does it take to turn that analytical insight into value to drive and benefit the organization? Here’s what you need to do after the data analysis is complete.
Make Sure the Organization is Prepared to Make Changes
Unfortunately, the results of data analytics sometimes indicate that you need to change directions. Are you ready to make the changes?
Sometimes, data can yield insight that the organization doesn’t really want to hear. It might mean that you’re doing something wrong or need to do something else that you haven’t been doing. Unless the departments and employees are on board with making the changes indicated by the data, there isn’t any need to run the analysis in the first place. However, it’s okay if you take time to make changes. Be transparent and upfront about what the analysis said, what changes this indicates need to be made, and why. Also, give people time to adjust to the proposed changes, especially when it means significant changes to their daily jobs.
Be Sure You Understand What the Analytical Results Mean
Data analytics doesn’t come back and say, “there’s too much waste in your processes,” or “the quality of this product needs to be improved.” What it does say is, “this process yields X amount of waste,” or, “X percentage of customers complained about product quality when they called customer service.” You need to be sure that you take the right steps based on the information. It can be easier than you think to make the wrong conclusions based on the analytics results, such as, “employees are being wasteful,” or, “customers will pay whatever it takes for good quality.” Obviously, these things aren’t what’s indicated by the results — those are conjectures based on the results that may or may not have any basis on the truth.
Determine What Needs to Be Done Based on the Analytical Results
What action makes the most sense in light of the data analytics? This answer isn’t always readily obvious.
Based on the results of data analytics, what are the reasonable steps to take? In the above examples, you probably need additional research to conclude exactly what’s leading to the waste and what is causing poor quality. You might be led to make changes in your suppliers or offer better employee training. Step back, determine exactly what the data is saying and what that means, and then decide what needs to be done with that information. In many cases, you’ll realize that the data can only tell you what is happening, not why it’s happening. It usually takes more research to get to the “why” of the matter.
Are you preparing for the changes that come along with taking on big data? You can learn more about adopting big data, choosing the right big data tools, and applying the insight derived from big data analytics to your business at Big Data Week. See the full conference schedule here