It only took nine (9) days*, but we’ve finally reached the point where we are down to the seven (7) “future” trends that are actually new enough, with the right interpretation, to fall into the “future trend” category.
7. Supplier Pre-Payment
We’ll admit that this belongs in the ancient category with governmental regulation, margin pressure, and supply chain risk, because pre-payment has been around as long as demand has exceeded supply. So why is this in the like-new re-manufactured shoes category? Because you can pre-pay your supplier. You can pre-pay your supplier’s supplier. Or you can pre-pay the supplier of your supplier’s supplier. The first is old news. The second is ongoing news. But the third, well, that may just be remanufactured shoes. There was a reason that, once upon a time, companies were vertically integrated. That’s because when you could control the costs all the way down to the raw material extraction, you could minimize the cost.
So what do you do when you can’t control all the costs? You control the margin, and you buy when the market is good, or when you have the chance to lock in supply before prices rise even more. And if you buy on behalf of your supplier’s supplier, you can buy raw materials in bulk, often at a lower cost than your supplier’s supplier, and provide these raw materials at no margin to your supplier’s supplier, who is making the components or sub-assemblies, and keep costs down throughout the entire supply chain. Not just your little piece.
And with the right supply chain visibility, you can do more than just identify risks — you can track costs through the supply chain and do true multi-level should-cost modelling, optimize spend throughout the supply chain, and when it’s cheaper to buy on behalf of a supplier, or a supplier’s supplier, or to pre-pay a supplier so they don’t have to go to a loan shark to make payroll, do that. This allows you to take out cost where competitors without the same visibility and forethought can’t. It’s an old, old, old idea, but a new application of this idea can take your supply chain to the next level.
6. Data-based Predictive Analysis
While data-based predictive analysis is not new, as businesses have been doing sophisticated statistical trend analysis for decades (and SAS has been around for over 35 years), the application thereof in Supply Management is relatively new as there hasn’t been much in the way of good data for Supply Management before the implementation of a good sourcing or procurement suite. Furthermore, the applicability of data-based predictive analysis only gets interesting when there is significantly more data to analyze than what is within a company’s four walls, and the ability to access significantly more data is a recent phenomenon.
You see, not only does predictive analysis suffer from the same problems that spend analysis suffers from, but the magnitude is amplified where predictive analysis is concerned. Backing up, it’s impossible to do spend analysis on data you don’t have, and it’s impossible to do trend analysis on a product that is not yet released. In many verticals — fashion, electronics, etc. — product life-cycles are so short that you can’t do a reasonable spend analysis until the product is at end of life and by the time you have enough data to do a reliable trend analysis all you can predict is the obvious: sales of zero. Now, if you have multiple, successive, product lines in the same category — like yourPhone 1, yourPhone 2, yourPhone 3, etc. — then you will eventually be able to predict sales of the successor product with reasonable accuracy, assuming no major unexpected changes in the market. However, you’ll be left in the lurch when it comes time to predict spend and performance on a new product line. That’s why you need considerably more data than resides within your fall walls and that’s why data-based predictive analysis wasn’t really a reality until the last few years as it was only in the last few years that Supply Management products emerged that collected, tracked, and integrated market data with your data. This permitted you to not only do realistic should cost models on new product lines, but multivariate predictive analysis to judge how well, under a certain set of assumptions, your product could do in the market and how well your supply chain could perform (from cost and risk perspectives) under those assumptions. So while this is ongoing blues in the business world at large, it’s recycled shoes for Supply Management. The hand-me-down has the potential to acquire new life in Supply Management.
Are you excited that we’re finally discussing more recent trends, Mr. LOLCat?
* And you wonder why Tard is go grumpy. He knows the truth.