by Pete Kovac
Believe it or not, there can be too much of a good thing, especially when it comes to your supply chain analytics
With the emergence of Big Data and everyone wanting to get as much data as humanly possible, we have to ask one question: Is this data helping or hurting the business?
Data collection has exploded in the past few years with the rise of big data analytics, especially because now we can have access to massive amounts of data on small screens, such as smartphones and tablets, 24/7. The increased use of in-memory databases has surged the use of big data analytics. But in-memory databases also come with a hefty price tag such that some companies are putting off purchasing them for future expansions. Working without in-memory functionality leaves many businesses making a few common mistakes in gathering large amounts of data for reporting.
What is a data point and the business decisions that you will make from it worth to you? When you look at data points, you need to be sure that you are looking at data that will lead you to correct business decisions, quickly. One mistake that we see all too often is companies not understanding what data to pull in, so they pull in everything and then try to sift through the chaos later.
Data just for data’s sake is fundamentally wrong. If you’re looking at a data point and cannot make a business decision from it, then that data point is irrelevant; it’s simply a dot on a screen.
How positive are you that the supply chain data you’re pulling in and looking at is the right data on which to base business decisions? You might not be. You might be chasing the proverbial white rabbit.
Your IT department’s frustration will grow with constant pulling of data. Running multiple extraction programs for massive amounts of data will slow down overall system performance. For example, you extract data for 365 days every day into another table for reporting. That could add up to millions of records being copied, every day. Do you really need all that data? Probably not.
The fundamental reason why we have data and use data is to support sound decision-making. But how do we sift through all that data and focus on the correct key performance indicators (KPIs)? The easy answer is methodology. Having a methodology or sound approach as to which key performance indicators you’re going to focus your daily tasks on is critical.
KPIs are the difference between having actionable data vs. noise. The correct KPIs will drive users to immediate action. With daily KPI monitoring, business users will become more disciplined and engaged, and not only will they understand what the data is telling them, but why.
Without a solid methodology, you go back to pulling data that cannot give you direction. Once KPIs become a part of your business process, you’ll find yourself using less data to track changes, see trends and make faster, more educated decisions.
Tags: Big Data, key performance indicators, KPIs