Daily Archives: July 18, 2014

Are You Doing It Wrong?

If you’ve been following the media, you know that we have reached a point were most major business publications are now putting focus on Supply Chain as your top risk and your top opportunity.

You also know that these same publications, and the solution providers that follow, and reference them, have been preaching the following solutions to not only tame the risk but increase the opportunity.

Comprehensive Category Management

Spot buying individual categories at market lows or evening running reverse auctions at opportune times is not category management. And for that matter, neither is an event that covers the entire category. At this point you probably think that the doctor is losing it a little, because how could it not be category management if you are addressing the whole category?

It’s Simple. Category Management isn’t just about grouping all seemingly related items and running an event, it’s grouping items that have related characteristics that allow the items to be sourced effectively under the same strategy. For example, while it might make theoretical sense to group printers, ink, and paper together — because you use them together, from a sourcing point of view, ink and paper often go better with office supplies and printers with hardware. You can probably get them thrown in for free with a server purchase. But that’s just the start. If you source a lot of metal parts, you should probably group them by primary metal, since the price of steel, aluminum, etc. will largely dictate their prices and it might even make sense to not only source all of the parts from the same supplier but even buy the metal on behalf of the supplier with your better negotiating power and/or credit rating.

Supply Chain Risk Monitoring

Natural and Man-Made disasters devastate supply chains when they result in raw material or product unavailability for weeks or months. When a company doesn’t understand their dependence on a single source or the risks that single source is subject too, they can figuratively get caught with their pants down to say the least.

As a result, most leading companies in the Risk Management arena are now tracking and monitoring their tier 1 supply base for not only missed deliveries, but late shipment dates and inquiring immediately when something is late shipping. However, by the time a shipment is late, it’s often too late to go to another source if the reason for the lateness is the lack of an important raw material. So the smarter companies also ask their suppliers to let them know when their suppliers miss a delivery. This is better, but sometimes this is still too late. You need to track the primary sources of the raw material and their ability to produce. Not only the companies, but their locations. All natural and man-made disasters in the region and then evaluated for impact and if the producer of the primary raw material or part is potentially at risk, they make sure, or ask their tier 1 supplier to make sure, that the raw material or product can still be delivered on time and if it can’t, these leading companies immediately seek a secondary source (or lock up available supply pre-emptively) — not two weeks after the tier 1 supplier required the raw material to meet the commit date.

Big Data

The only buzzword on par with big data is cloud. According to the converted, or should I say the diverted, better decision are made with better data — the more data the merrier. This sounds good in theory, but most algorithms predict demand, acquisition cost, projected sales prices, etc. based on trends. But these days the average market life of a CPG product, especially in electronics or fashion, is six months or less, and the reality is that there just isn’t enough data to predict meaningful trends on. Similarly, every disruption impacts the cost, and these disruptions are as unpredictable as future sales predicted using trend models with insufficient data.

You use all of the data available to validate your operations, procurement, and financial situation. Not to blindly predict future sales or prices. An over-reliance on big data is often more dangerous than not having data at all.