Product fraud: not just in food supply chains
Your story "Consumer product fraud—how to stop it now" (Q2/2011) was a good, thought-provoking article.
Adulteration is not limited to just the food industry; it also affects chemicals and pharmaceuticals. I know a chemical company in Dubai that earned millions of dollars by selling fake chemicals. Once when I was discussing this with a few of their managers, they told me that [this practice] was not limited to their own company. They said there are pharmaceutical companies that manufacture fake generic drugs to earn millions of dollars.
I know that quite a lot of companies indulge in these kinds of nefarious activities to make millions of dollars in profits. They do not care for human health or for doing business ethically.
Radhakrishnan Pillay
Dubai, United Arab Emirates
Store SKU forecasts should guide manufacturers
I enjoyed the article "Are you a candidate for produceto- demand?" (Quarter 3/2011) and agree with James Cooke's comments on produce-to-demand being a better model than the traditional bulk "make-to-stock" model for some manufacturers. However, I would argue that forecasting by SKU (stock-keeping unit) at the store level, and having that information flow back through the supply chain (i.e., from the store to the distribution center to the manufacturer) would produce better results for both the manufacturer and the retailer, in contrast to the manufacturer creating its own forecast.
There is a book called Flowcasting the Retail Supply Chain, by André Martin, Mike Doherty, and Jeff Harrop, which goes into detail about this new method of forecasting. Some of your other readers may find this as interesting as I did.
Rob Dold
Account Executive, Fortna Inc.
Nashville, Tennessee, USA
Why it may be hard to get "a commanding view"
The article "A commanding view" (Quarter 3/2011) presents the reader with a number of concepts that make a great degree of logical sense. The science presented is not new but the adoption rate is slow. There could be several reasons for this, and I would think that many in the CSCMP community would benefit from understanding what contributes to the low adoption rate.
I can see four barriers to adoption:
- Cost of implementation. It maybe the case that the necessary systems to reasonably enable a "commanding view" strategy are expensive to implement, and maybe the ongoing maintenance is expensive also.
- Speed of implementation. Product lifecycles are getting shorter, with the bulk of sales occurring shortly after product launch. If the time taken to connect new supply partners and configure the system is lengthy, then this may limit the usefulness of adopting this strategy.
- Complexity. It may be the case that there are insufficient numbers of people who are trained to implement and run these systems.
- Reluctant partners. To enable this level of business intelligence, suppliers, carriers, and customers must be willing to share the necessary business intelligence data. I can see circumstances where suppliers lack sophistication and big customers simply say no to sharing point-of-sale data.
I would like to see an article that presents a real case, with before and after implementation performance numbers, and that talks about cost and speed of implementation together with the availability of information and people who are able to support this new environment.
Alan J. Bishop
Principal, Scoord
Franklin, Tennessee, USA
