The Role of Data in Sourcing Success

It's difficult to source and buy direct materials at scale. While simple transacting may seem easy enough to understand, the process leading up to these decisions is extremely complex. For example, you have to make sure the supplier you're dealing with makes sense from both a cost and risk perspective. There's also the consideration of buying the right part or material; for instance, would purchasing more of an equivalent part or material found in other products deliver greater savings? Also, would it be more effective to buy from a distributor rather than the manufacturer? If so, which distributor would be the best choice? And would real-time marketplace pricing provide more negotiating power than depending on backward-looking "should-cost" data when negotiating with suppliers?

The Challenges Businesses Face While Using Data in Sourcing for Ensuring Sourcing Success

It's challenging to solve such problems on a large scale. However, most companies haven't even attempted to do so in the past. Instead, they've narrowed their focus to a particular set of issues. Due to resource constraints, procurement organizations are forced to concentrate on a few main categories: items that are either incredibly risk-prone or of significant strategic importance. However, this type of tunnel-vision focus often leads to a lot of unrealized potential and ignored concerns. Organizations end up saving cents and calling it a success; meanwhile, there are dollars to be saved elsewhere. All the while, they’re addressing a few specific risks but ignoring other supplier risk analyses altogether.

What Can Be Done for Data-Driven Sourcing

Data is available now, more than ever, to considerably widen sourcing's remit, bringing in these under-addressed purchased items and hazards. The availability of digital data has exploded in recent years. Capabilities such as data-driven sourcing and component aggregation over fewer stock-keeping units, as well as supplier risk analysis, aren't new. But what has been lacking is sufficiently granular data and sourcing insights with which to do it—and do it dynamically, in as close to real-time as possible, augmented by AI and smart analytics as much as possible.

Similarly, the amount of near-real-time sourcing data on global logistics networks, costs, infrastructure, and supplier locations has increased dramatically. As a result, suppliers can see their logistics costs, shipment status, and whether or not their production and logistics operations are working well in the case of natural disasters or political upheaval.

Things to Consider While Leveraging Data-Driven Sourcing for Enhanced Supply Chain Efficiency

The downside? External data doesn't—and usually can't—fit into typical enterprise systems. You have the data for a real-time window into global trade, but you still need to combine it with data from your enterprise systems and put it in a context that can be studied with advanced analytics. Although it's frequently claimed that using data in sourcing is more of an art than a science, data can help—and it's now more accessible than ever.

To discover how LevaData’s integrated supply management platform can help you capitalize on the power of real-time, AI-driven insights and analytics, schedule a consultation today.