Create and Use Big Data: Dispatch From Procurement Leaders’ America’s Congress

I’m at the Procurement Leaders' America's Congress in Miami today. Having sat through the morning sessions so far, I can say the trip has been worth it already, not even factoring into the one-on-one discussions and catch-up with old faces and new. Indeed, the number of ideas and takeaways I’ve jotted down from the keynotes has been off the charts.

Walter Charles III, vice president and chief procurement office for Kraft Foods Group, kicked things off earlier today and has served as emcee. In addition to sharing war stories from his current role, including the exploding complexity of big data in procurement in sourcing efforts, he has also managed the overall main stage activities, including welcoming Rio Tinto’s Managing Director and CPO Ramsay Chu on stage.

For geeks like me, Ramsay stole the show this morning with story after story about data-centered initiatives including how to create and source new information that can take analytical problem solving in entirely new directions. He mentioned how Rio Tinto has started adding tags to tool belts for safety tracking of employees and contractors to make sure individuals do not move into dangerous/restrictive areas.

But the organization also thought to use this data to tie back to contracts for contractors to understand the “time on tools” and on the job – and specific worker location. They then thought to take a similar approach to tracking assets such as trucks and toolkits themselves to understand asset utilization and capital expenditure. In other words, tag everything because you won’t know how you can use the data in the future.

Ramsay described the future of analytics and big data as serving at the intersection of IT (traditional data) and OT (operational data) together. Now the good news: Creating operational data is something in procurement’s control – and it doesn’t even require asking suppliers for additional invoice and other document information. Just tag and go, as one first step.

As a related example, Ramsay suggested the concept of tracking tire replacement on trucks (a significant expense for mining companies – these are big trucks and giant tires). It’s one thing to understand historical replacement patterns. But why not put a sensor on a truck itself to understand such metrics as elevation, rate of change, velocity, etc.?

Historically, forecasting for tire replacement (and spares requirements) was less sophisticated. But with these new types of data, linking both IT and OT sources of information, it becomes possible to get far more prescriptive by identifying and fixing underlying problems versus just addressing the symptoms. For example, perhaps tires are wearing faster because of a “3% degradation in the road” based on underlying data from elevation, acceleration and breaking activities (all gleaned from the tracking sensors). In this case, as Ramsay suggests, don’t just replace tires more frequently – fix the road!

Stay tuned for more coverage from Procurement Leaders' America's Congress later this week. But don’t wait to start sourcing more data. Take Ramsay’s lead and start tracking and tagging what you can today.

Share on Procurious

Discuss this:

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.