It's almost impossible to talk about any facet of technology these days without mentioning the elephant in the room - Big Data. So much time is spent discussing its importance and why we need to spend so much time dealing with the sheer deluge of information now afforded to us that we fail to step back and think strategically about what the desired outcomes of analyzing that data are. In a nutshell: we know it's important, but we may not know why.
A recent Government Executive article summed it up perfectly: "Before you go mining big data, you have to think analytically with some small data. It's data thinking that can prove to be really big." In fact, I would argue that this is even an understatement. Organizations are throwing huge sums of money into software and services to mine data and base major decisions on what is spit back out - but what if the data going in is incomplete or does not dive deep enough to provide truly effective feedback?
A favorite mantra of mine is "you don't know what you don't know," and it rings true in the world of Procurement. Many organizations using procurement management solutions are content with a fairly limited volume of information: who the suppliers are and from where they are shipping. It's likely they don't know that it can go much deeper.
A major point that separates SciQuest from its competitors is how we classify suppliers, getting down to levels of detail and information that our competition simply can't/don't and our customers never knew they could. If you are analyzing your data at the supplier level, you are not getting any more feedback that an excel sheet could provide. To get to a truly analytical level you need to move levels beyond suppliers and look at hardware, services, IT, materials, etc.
I am not saying that every inquiry requires this level of specificity; in fact some might not. What I hope you take away from this post is that organizations should be asking these questions before they ever think about analyzing data so they know what their desired outcome should be.
Want to learn more about data classification and how it can help you better understand your spend? Sign up now to receive our upcoming whitepaper on Spend Analysis Data Classification. We will take an in-depth look at the differences between supplier level vs. transaction level classification, and why is it important to understand these differences. We will also discuss the types of spend decisions your organization can expect to make by having access to accurate, highly-classified data.