Demand Management: The function of recognizing all demands for goods and services to support the market place. It involves prioritizing demand when supply is lacking. Proper demand management facilitates the planning and use of resources for profitable business results.
Source: http://www.apics.org/ (10th ed.)
The last few decades have seen an increasing demand for enterprise software applications that can streamline supply chain processes and provide lean manufacturing capabilities. At the other end of the supply chain, companies have been moving towards outsourcing their product distribution in order to keep sales overhead in check without sacrificing revenue.
These recent trends have resulted in a unique dilemma. While companies can produce products more efficiently, they have little knowledge regarding what to produce, for whom and when. They now have better visibility into their supply chains but they lack the same kind of visibility into their often-fragmented demand chain (more…).
The current economic slowdown and huge inventory write-offs resulting from this lack of visibility have highlighted the need for a systematic way to predict and manage demand. New technologies provide the capability to extend supply chain visibility that can support a truly dynamic collaborative internal environment; but companies are looking beyond sources within the enterprise, such as sales and promotions groups, to include customers in the demand management cycle (1).
Accurate forecasting remains central to the success of a demand management initiative, but demand management is much more than just forecasting. Traditionally, forecasting involves looking at past demand data to predict future demand. Demand management goes beyond the static forecasting of yesterday, replacing it with a more fluid, ongoing view of determining demand that involves all demand-chain constituents. Currently there is a thrust towards real-time synchronization of the supply chain to the demand signals. This collaborative method enhances the accuracy of forecasting since all factors affecting that forecast can be viewed by all stakeholders, including customers (2). Companies can begin to bridge the gap between their supply and demand chains by doing the following:
1. Reshaping relationships with channel partners to ensure accurate demand forecasts. Manufacturers should implement a closed-loop process for gathering, analyzing and filtering demand forecasts from channel partners. The demand management system should be tightly integrated with management systems for entitlement and other benefit programs for channel partners. This would help to ensure that just-in-time manufacturing is performed for the right products, in the right quantity, at the right time (more…).
2. Basing inventory allocations on real-time demand forecasts that incorporate information from all channels—both direct and indirect.
This increases revenues by targeting allocations to those channels and locations that are the most effective sellers (more…).
3. Ensuring that your own house is in order.
According to Andy De, director of solutions marketing for i2, demand management solutions are most effective when paired with other supply chain applications. Says De, “Having an accurate picture of demand is irrelevant if you don’t have a supply chain that can meet it.” In addition to cooperation from other supply chain partners, in order to achieve the benefits of a truly dynamic collaborative environment, companies need to get their internal demand management processes in order (3). For example, the promotions group in a company responsible for creating and driving demand is often disconnected from the operational group that produces the product and as a result ends up spending money promoting a product that operations cannot deliver. Ensuring that the different groups that have a stake in the demand process are connected is important.
4. Ensuring the presence of accurate intelligence along with collaboration and automation.
New technological developments have enabled real time flow of information within and across enterprises leading to better forecasts and an enhanced ability to respond rapidly to customer requirements. The downside to these automated processes is that they could be transferring bad information. Despite sophisticated statistical methods, it is impossible to eliminate market uncertainty from the forecasting process. Customers’ purchasing departments have every incentive to inflate estimates. It is important to have people in place who can analyze the forecast to see how it fits in the total market so that the company builds to actual end-unit demand rather than estimates that have been distorted as they travel through intervening layers (4). Providing greater supply chain visibility to downstream supply chain partners will eliminate their need to overstate forecasts.
5. Choosing demand management applications that address the unique challenges faced by the specific business. Many existing applications fail to fulfill the specific demand management needs of companies. Some enterprise applications support fixed pricing strategies but their solutions cannot easily maintain dynamic forms or manage prices across channels. Other applications are limited in terms of other demand management challenges. Certain customer relationship management systems, such as those from Siebel Systems or KANA, assist sales personnel but lack insight into price sensitivity and supply chain capacity and are therefore of little value in terms of deciding which orders to take and which offers to recommend.
In the near future, companies are likely to embrace three continuous demand management strategies that incorporate feedback loops from downstream processes and market conditions: I) linking forecasts based on causal variables, like economic indicators, to current sales activity and field-level orders to create market sensitive demand forecasts that set corresponding capacity and inventory recommendations; II) linking capacity to changes in demand so that companies can optimize service levels, safety stocks, and inventory levels, even in conditions of sudden demand variability; III) adjusting price and contract terms to changing market conditions (5).
Lavey, P. (2001, September). Best practices in enterprise relationship managment. KMWorld.com.
(1) Anderson, A. (2002, June). Togetherness pays. MSI, 20(6), 60-65.
(2) Jones, K. (2002, June). In the driver’s seat with demand management. MSI, 20(6), 62-64.
(3) Anderson, A. (2002, June). Togetherness pays. MSI, 20(6), 60-65.
(4) Parker, K. (2002, February). Events happen but demand is always. MSI, 20(2), 40-43.
(5) Kilgore, S.S. (2002, March). Continuous demand management boosts margins. MSI, 20(3), 44-46.