Unite and Conquer the Demand Plan

DRP is alive and well, but it is only as good as the collaboration that goes into it


Death of DRP?

Automating a process like this has not been easy, but pushing DRP all the way to the store level is an adaptation that has provided much more effective collaboration in managing the supply chain. DRP can now also be used to build loads appropriate to a given channel — businesses no longer have to use fixed order quantities at the DC or the store level. Rather, companies can look at the demand picture and build loads that work from the viewpoint of the entire supply chain.

But does all of this mean we're moving beyond DRP to a new form of demand planning altogether? The answer is no. Let's take a look at the practice of double-entry bookkeeping. While new tools have been created to make the process easier, more efficient and more automated, the fact remains that double-entry bookkeeping is a fundamental element in the financial universe. No matter how many technological breakthroughs come about, the basic process will remain unchanged. Like double-entry bookkeeping, DRP is a fundamental element in the supply chain universe — it doesn't go in and out of fashion, but is simply adapted to meet the changing needs of modern business.

 

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In other words, DRP is a basic building block of any supply chain strategy. Nothing comes after DRP, since it is so fundamental. History shows that DRP has been and will continue to be adapted to whatever competitive realities exist. A better question would be to ask how new forecasting models will adapt to the basic truths that DRP exposes.

At the root, collaboration becomes key. While organizations might throw hundreds of thousands of dollars into sophisticated demand forecasting solutions, the most powerful computing system on the planet can't magically assess how much product a supplier has on hand or how many employees that supplier might have to manufacture those products. Unless, that is, the supplier is willing to divulge that information to their customers and raw materials providers. Without collaboration, a business might have the ability to know how much inventory they will need in the coming months, but they won't know how much of that inventory they will actually be able to get.

Beyond "Private" Forecasts

A problem many companies run into is the fact that each organization along the supply chain has its own "private" forecast of both production and necessity. For example, if a large retail chain cuts its order volume of product by 8 percent, then its main supplier might subsequently slash orders from its own suppliers at a rate of 10 percent, since that supplier doesn't have visibility into its customer's actual forecast. What's more, the component supplier might decrease orders by 12 percent, the raw materials supplier by 16 percent, and so on, all because each company is basing orders off of its own forecasts rather than a common one. For complex, global chains with multiple distributors and manufacturers, these inaccuracies have a cumulative effect as they work themselves through the supply chain. The result is a raw materials supplier that receives too few orders to stay in business.

This chain of events becomes a real problem for retailers when an upswing in demand is met by a lack of supply. Suppose the retailer that made an 8 percent cut to order volume experiences a rush on its stores six months later, requiring a 12 percent boost in supply. By this time, raw materials providers have scaled their businesses to a level that cannot provide for the new round of demand, resulting in millions of dollars in lost sales.

We should note here that the woes felt on the part of retailers have arisen because they have not shared their own demand data with suppliers to provide a single source of the truth. This is why many institutions have sought a better solution, namely, pulling data from point-of-sale transactions rather than from those at the distribution level. On paper, the idea makes sense. In the real world, however, retailers still have to take the final step by bringing store-level demand forecasting to the next level by giving their suppliers — and their suppliers' suppliers — visibility into their point-of-sale data.

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