Why Big Brains Will Beat Big Data in Procurement


Today’s guest post is from Ryann Kahn, Marketing and Communications Manager at Source One Management Services.

Two weeks ago, the Sourcing Innovation blog published an article about how the three cognitive traps stifle global innovation. I couldn’t help but think about how the same points could be made in procurement: data (though usually we don’t have Big Data) can help overcome some common issues, but ultimately Big Brains are more important and effective at the same job.

Take a procurement sourcing project for example.

The commonly used traditional three-bid process is data driven. It implies that if you collect enough (i.e. three pieces of) data, then you are making a good decision. Now, by collecting three bids, you know you are not getting the worst price and service out there and you are encouraging some competition. But without category expertise or a strategic process in place, can you really consider the data alone enough to justify that you have made a wise and innovative decision? Data != strategic sourcing.

But the data itself can often lead to the confirmation bias that the doctor referenced previously. Was your RFP template (or software solution) structured in a way that drove you to the conclusion that you already had envisioned? For example, if you want to remain with your local incumbent supplier, does your scorecard penalize suppliers for not having a location near you? Did you only request pricing on a specific product, which you knew your preferred supplier had the best (or only) price available? Confirmation bias in the sourcing world is real and common. Many companies effectively eliminate competition with better solutions because of the way they structure their questions.

By contrast, a true strategic sourcing process uses data in a Big Brain process.

The first step is a spend analysis of data from contracts, supplier invoices, P-Cards, supplier reports, POs, and more. (That’s a lot of data.) Then we look at market intelligence, historical trending, new products or process enhancements and benchmark data. (Now that’s Big Data!) All of this information is pulled, assessed, and analyzed. But the data alone does not give a full picture of a company’s spend. It takes the “curious, open mind” to uncover the whole story. Data may suggest inadequacies, but only through more in-depth research and thorough interviews with stakeholders and end users will one be able to identify problems and usage requirements.

The next step of the strategic sourcing process is the sourcing strategy. Again, it begins with data collection to cast a wide net of suppliers and determine their capabilities. But the bulk of the work in this stage belongs to the Big Brain: creating the supplier strategy, envisioning an RFx strategy, and planning for an execution strategy.

Even if procurement evolves to join the Big Data bandwagon, data will never be able to replace a human category expert. A category expert comes armed with nuanced knowledge of market trends, characteristics, players, and history, and uses analytical skills to apply that to plain data. Or, as the HBR article says, “When we look at markets different from our own we often have little information”. An expert who has been intimately involved with sourcing a category for years will be able to achieve better results than a novice armed with data, or the most powerful e-sourcing tool, any day.

In the final phases of the strategic sourcing process, implementation and compliance, it is entirely the work of a Big Brain. Experts must ensure that a company is actually achieving the results that were identified in the earlier phases in terms of savings and level of service. These experts may use tools to help collect the data to support the process, but the tools themselves don’t do an adequate job of capturing the data that is important to the unique organizational situation.

Data can, and does, help make good sourcing decisions, but ultimately it’s the Big Brains that lead the way. A Big Brain will always be needed to strategically apply the data (big or small), and be the “curious, open-minded researcher” to make a good decision.

Thanks, Ryann.

Why are Your Inland Shipping Costs in China so High?

As this recent article over on South China Morning Post on Last Mile Transport’s Heavy Load for Truckers implies, it’s probably poor planning on your part.

Specifically, it’s expecting that China carriers can move your product from A to B as fast as North American carriers can get your product from C to D, where the distance from A to B equals the distance from C to D. Although China’s transportation infrastructure is much better than India’s transportation infrastructure, it’s still not on par with the US which gets a 4.14 ranking (out of 5) compared to China’s 3.61 (as per the World Bank’s Logistics Performance Index).

Not only is transportation infrastructure insufficient in some parts of mainland China, or overcrowded in many of the big urban areas, but there is also the restriction that trucks can’t be on the highways after midnight. (In the US, the worst you have to deal with is speed limits that drop 10 mph at night. As long as the driver hasn’t reached his daily driving limit, that truck can drive all night long.)

As a result, when you insist on unrealistic schedules, with penalties for late delivery, you end up costing the logistics company needed revenue that it needs to cover the highway and first-tier road fees, as 95% of the country’s highways and 61% of it’s first-tier roads are toll roads (and the company has to use these roads to ensure reasonable delivery times as the free roads are typically dirt roads not suitable for transport trucks). As a result, knowing that it’s going to be late on a significant number of deliveries unless it illegally drives on the highway at night (which will result in harsh fines), and, as a result, get hit with a large number of penalties, the logistics company has to increase its base rates to absorb the expected losses to stay in business.

Thus, if you acknowledged the reality of the transportation situation that Chinese logistics companies have to deal with, accepted slightly longer delivery times, and planned accordingly, you could reduce your mainland China logistics costs — especially if, instead of using one of the almost 10,000 small or mid-sized companies that can’t take advantage of economies of scale and end up absorbing a lot of empty miles, you use one of the few large companies that have enough trucks, and warehouses, to minimize empty miles and use their scale to their advantage. (Plus, shifting more to the bigger carriers will allow them to become financially stable enough to acquire some of the smaller carriers where their footprint is weak, and this should further decrease costs in the future. Furthermore, when the market sees consolidation working, some of the mid-sized carriers will likely merge to offer more cost-effective options. China is big enough that it can support dozens of major carriers, not just a handful like some of the smaller global marketplaces. As a result, even with significant consolidation, there should still be ample competition to keep prices low.)