There’s no doubt that big data is more than just a buzzword. Today, countless case studies, white papers, and testimonials support the notion that big data helps drive business growth.
When it comes to your enterprise resource planning (ERP) solution, data are essential. They’re what fuel your ERP solution and help people make timely decisions. However, some organizations run the risk of collecting too much data. Ultimately, this can lead to information overload.
Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers Ahave fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur.
Working with too much data can be confusing to decision makers. End users also find that when they suffer from information overload, data become confusing to work with. It may be difficult to sort and analyze. When this happens, the big data in your company’s ERP solution may not be the fuel for growth you expected it to be. Rather, it may become a hindrance to you achieving your goals. In addition to frustrating and constraining, your end users’ information overload can slow things down.
When pressed with too much data, the performance of your ERP solution will suffer, typically because the application and the server on which it resides are being taxed to their limits. These performance issues lead to further frustration for your user base.
There are two ways to tell if your ERP solution suffers from information overload. Start by looking at the performance of the ERP application and all affected servers. Are the resources near or at capacity? Is the application’s performance suffering (i.e., does it take too long to analyze data)? Is the system unstable?
Answering yes to any of the above questions means that you may be collecting too much data to feed your ERP solution. Work with your IT team to set up benchmarking tests to figure out if any of these issues are the result of the configuration, setup, or hardware. If you can eliminate these elements as causes, information overload is the likely culprit.
Not all indicators of information overload are easy to measure with baseline tests and automation. Some of them require you to get into the trenches and see how your users are working.
First, look at how you collect data and what type of information you feed into your ERP application. Is quantity stressed over quality? If this is the case, you can revert to the old saying, “garbage in, garbage out.” Only expect the garbage to trickle out slowly.
Next, determine whether your users are actually relying on your ERP solution or whether they’re turning to outside resources for information. If they’re skipping the ERP system in favor of spreadsheets or other tools because the ERP software isn’t meeting their needs, it may be because too much junk data are clogging things up.
Managing information overload isn’t as simple as cutting off the amount of data you collect. After all, people in your organization rely on that data to do their jobs. Some steps you can take include:
Finally, take steps to clean your data as often as you can.
Information overload has the potential to sink your ERP solution if you let it. Take the necessary steps early to see if information overload is becoming a problem so that you can proactively address it before your system and users suffer.