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    How to Use Big Data Analytics to Drive Business Value in Procurement Forward

    Analytics | Innovation

    JAGGAER InsideSpend Thought Leadership SeriesIn this blog series, we profile leaders in the procurement industry. We hope their insights and experiences inspire you to achieve greatness in procurement. 

    A conversation with Walter Charles, Chief Procurement Officer

     


     

    As we gear up for REV2019, we’re revisiting this interview with Walter Charles, CPO of Allergan, who sat down with us at last year’s REV event to discuss the procurement challenges and trends facing manufacturing companies. 

    Having spent decades at Kraft Foods, Kellogg’s, Johnson & Johnson, and Biogen – at the time of recording, Walter provides keen insight into the state of procurement today and how big data analytics is disrupting the landscape to provide CPOs with meaningful answers for more strategic procurement execution.

     

     

    Procurement trends in manufacturing

    Q: What are the big trends in manufacturing? How are they impacting the procurement organization and proficiency?

    I believe disrupters are going to dominate the world. There are some trends I talk about in an article in Supply Chain World called “The Next Productivity Gear”. It covers how Biogen is rethinking how it approaches supplier discovery and how granularly we understand, clean sheet, and cost model the items we’re buying. We point out that you need some sort of big data analytics engine to handle the mass avalanche of data you’ve got. It can help you to get to more meaningful answers quickly.

    Imagine if you could include every single supplier possible in the bidding process to get an apples-to-apples comparison on critical criteria. What if you were able to find that “Uber” performer in every single category and unlock the value proposition for your business to drive value for it? This the power of big data analytics.

    With big data analytics, you can evaluate 600 suppliers just as easily as you can evaluate 6. So imagine sorting and getting to actual insights in seconds instead of months of pivot table hell with Excel or spreadsheets—which is the de-facto standard in the industry, by the way—for analytics bids. I believe it’s a game-changing framework.

    The Power of Big Data Analytics

    Q: What is big data analytics and what can it do?

    First, it helps your teams not only find cool ideas that can actually drive differentiated value for your business, it also allows you to change benchmarks and standards. For example, last year we went through a benchmarking exercise with a bulge-bracket consultancy. They indicated, “While most sourcing organizations deliver in six- to seven-times their costs; top core tile companies typically deliver about 10.4 their costs.” Biogen is at 13.7. This means we are delivering between 150 and 250% more savings with fewer people with bigger impact because of the tool constructs we’ve bolted on to the back-end.

    Q: Has your technology investment been critical to Biogen’s success?

    Absolutely. We’ve got technology that can crunch through data to get to actual insights in seconds. Even though you have technology, it’s important to note that you must also fundamentally rethink the methodology you use in sourcing. I call this “constraint-less bidding.” If you don’t have the constraints of whatever it is limiting your ability to get after the entire population of players who compete, think about the possibilities.

    Q: Does the big data component require data scientists?

    No. All you need is a very small population of people who understand how to leverage the tool to unpack the bids you’re after. I’ve done this at a scale of $10 billion at Kellogg’s and a scale of $12 billion at Kraft Foods. All I had was a small pool of six to ten people who were data-savvy. You’ll definitely need a category manager that can expand the aperture around what costs you’re looking at and the number of possible suppliers, to get at the data the business can use to make more informed buying decisions.

    Q: Why aren’t more CPOs jumping on the big data analytics train?

    I think we’re at the tip of the spear. Typically, the one degree of freedom you have in procurement at the large enterprise level is changing the processes you use to understand what you’re buying, and how you make that process the most robust it can be. But it takes time, knowledge, and tools to be able to do that.

    All of the major consulting firms say there are 64 elements you should be examining on every bid that you do at the sku level, as it relates to direct materials. Imagine trying to find 64 different slices in Excel—you would never do that. With big data analytics you can take out individual slices and examine it, such as labor content, inputs associated with bill of materials, distribution of transportation, components that drive the cost for a particular item, etc. And you then ask key questions like, how can I be a more effective purchaser?

    A real-world example of this was when I was at Kellogg’s. We were bidding a cocoa spec. Globally there are 13 to 14 specifications for cocoa. In our granular examination, we found out this particular cocoa spec was comprised of 25% sugar. Because I had a huge sugar contract for Frosted Flakes, I knew exactly what I should be paying and I compared the two side-by-side. This discovery resulted in considerable cost savings for the cocoa specification.

    Q: So you’re saying CPOs need to go wider and deeper to get after process improvements?

    Correct. Imagine 100 times more suppliers and 100 times more granularity in your cost exploration—in the end, you wind up with something that is very robust. For example, Kraft has 5,100 SKUs just product labels. It takes about 900 different suppliers to give Kraft the 5.3 billion labels they produce each year for their complete product line. Add to that the 100 cost elements per SKU and you’ve got about 450 million data elements that now need to be analyzed.

    Before big data analytics, it used to take two and a half years to do a label analysis. Now we process all 450 million data elements in just four months. We were able to unpack more costs, find more innovation, and fix our obsolescence problem using this tool. For example, labels for products that didn’t sell would just sit on the shelf and we would have to throw them away. Using our technology tool, we were able to identify those products that had a shorter shelf life and move those to a digital, just-in-time label printing construct.

    Today, I’m constantly going to my business with ideas on how we can change, pivot, and fundamentally disrupt the current ecosystem to a differentiated set of outcomes. Our buy at Biogen is about $ 4 billion and it’s pretty substantial. We have products in the pipeline that are designed to go after big neurological challenges, like Alzheimer’s. I am excited to support these efforts by doing things smarter and better than we historically have.

     


    Bio

    Walter Charles is the Chief Procurement Officer at Allergan, where his global procurement teams support billions of dollars in purchases annually. Walter has previously held chief procurement roles at Kraft Foods, Kellogg’s, Johnson & Johnson Consumer Supply Chain, Cordis and Biogen.

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