Data Science Is Changing the Procurement Landscape

By Christian Ries

For years, supply chains have relied on manual data entries from spreadsheets to assess spend and opportunity. At the same time, large companies with several supply chains  combined their sourcing efforts in order to compile enough accurate data to run enterprising bids. In short, sourcing was a monumental undertaking that required laborious, front end data analysis, and worst of all, it stymied progress.

Fast forward to the present: The internet of things, digitization, shared services supply chains, and fast- acting ERP systems provide sourcing teams the data they need to create and deploy competitive bids.

No longer are data teams required to manually extract and enter PO/invoice data into spreadsheets. No longer are sourcing executives stymied by insufficient data. No longer are  site specific invoices invisible. No longer is there a reason to source using estimates.

Data makes sourcing what it is today.

Here’s How:

  • Total Cost of Ownership

The advances in data visibility (ERPs and/or hard-installed or cloud based AR/AP systems) allow sourcing teams to capture the total cost of ownership of a particular sourcing event. This is important because teams can now gain insights into logistics and freight that were not possible to gain before.

This increased transparency into pricing models has given teams the ability to source for optimal value instead of optimal price. Increased transparency  also empowers buyers to push back on suppliers and toe-the-line on both price and logistics. This prevents suppliers from decreasing pricing, only to pad and increase logistics charges, a game we at Arkestro coined “Hide the Ball” in a previous blog post (Link article)

  • Accurate and Nimble Data

When accurate data is easy to access, it allows sourcing teams to be agile. Is acute spot shortage of an item critical to your operations? No worries. With easily accessible, accurate, and quickly deployable data, sourcing teams can get a request quickly, allowing them to be responsive to market changes.

  • Predicting Bull Whips 

In the past, it was difficult  to examine seasonal bullwhips. Compiling manual data from many suppliers to examine seasonal availability and demand was a laborious task and, often, anecdotal at best. If one extrapolates the lack of visibility across organizations who buy for multiple sites, disciplines, or categories, it is very clear to see how supply chains could over or under source.

With advances in the availability of data, strategic sourcing teams can now examine trends or bullwhips. This allows sourcing teams to optimize, not only the value, but the downstream supply chain operation.

The advances also ensure that end users are paired with suppliers who can meet the demand and assure a steady supply during seasons subject to bullwhips. With more data, sourcing teams can drive further savings by ensuring that their organization buys the right quantities, at the right time, at the right price.

In the end, data is only as good as the method used to deploy it. As data moves faster and is increasingly accurate, the tools used to interact with it should be the best in the business..

And that is why Fortune 100 companies use Arkestro to deploy their data. Arkestro delivers a 16% average cost savings, drives significant reductions in time, and as a result, increases throughput. To learn how you can get the most out of your data in sourcing, get a demo.

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