Demand management Forecasting

The objective of order and demand management is to forecast future sales as precisely as possible, manage customer orders from entry to delivery, and consolidate forecast and orders with supply chain inventory requirements in order to generate a holistic demand plan for purchasing, production, and distribution planning. 

Market-driven demand management utilizes data from market and channel sources to sense, shape, and translate demand requirements into an actionable demand response bidirectionally from market to market. A true market-driven forecast is an unconstrained view, or a best estimate of market demand based on channel data. Demand shaping is based on campaigns to combine price, new product launches, trade and sales promotions and incentives, advertising, and marketing programs to impact what and how much customers will buy. 

Using what-if analysis, demand forecasters can shape unconstrained demand based on current sales and marketing activities as well as external factors affecting demand. This includes weather, special events, and economic conditions to optimize volume and revenue while minimizing marketing investment. Figure 3.7 illustrates the four key steps in the market-driven demand management process. 

The implementation of a new demand management system helped a large U.S. direct store delivery company improve forecasting accuracy by 4 percent and increased service levels by 6 percent. Despite growing volumes, the company was able to hold inventory costs flat. The company also found that based on the new forecast, the sales department was better equipped to plan profitable sales promotions. The project s savings exceeded expectations. 

When we switched to our new demand management solution, we saw our forecast accuracy improve immediately. We also saw service levels take off in a positive way and our inventories decreased. We exceeded our original projections the accuracy is driven by a change from a 50,000-foot view of forecasts to a more detailed look. Now we can talk about a particular deal with a retailer and know what kind of lift is generated and then that drives the supply chain. There is no second-guessing, said a demand planner at a food and beverage company. 

The company used its demand management solution to build three additional attributes into its forecasts competitor activities, weather conditions, and promotion cannibalization of existing sales. 

A good demand management process will enhance the S OP analysis by providing a consensus demand forecasting environment that incorporates statistical methodologies, dashboarding capabilities and... 

Market-driven demand management is supported by demand-driven forecasting principles that have a significant impact on a company, whether the company sells products or services. Companies that have implemented a market-driven forecasting process have experienced four key benefits ... 

Implementing FVA into the demand management process requires that forecasts be recorded and saved before and after each cycle. Having the capabilities to store forecast history by a stream of activities (e.g., consensus forecast adjustments, managerial overrides, price lift calculations, etc.) is critical to measuring the value-added, or non-value-added, contribution to the overall process. Utilizing the statistical baseline forecast as the default is the key to establishing a benchmark to measure the effectiveness of all the touch points in the process. Unfortunately, few companies capture the appropriate data, or the level of detail on a historical basis, to conduct FVA. This is an opportunity. 

Leverage a demand management technology to automate forecasting workflow to create a more accurate unconstrained demand forecast. The enabling solution should provide a user-friendly interface that allows nonstatistical users (or planners) to systematically run what-if analyses to shape demand. 

Moving the forecast based on an enterprise view to a channel view. Learning to listen and use customer feedback cross-lunclionally. Implementing a program lo drive continuous improvement in demand management processes ... 

In this section, it will be performed a literature review for each one of the four categories of the Demand management - Statistical Forecast, Sales and Operations Planning (S OP), Collaborative Plaiming and Forecasting Replenishment (CPFR) and Vendor managed Inventory (VMI). This review allowed identify the DDSC characteristics for each category which was used to develop the five level maturity model. 

Based on Croxton et al. (2002), the demand management process is concerned with balancing the customers requirements with the supply chain capabilities. This includes forecasting demand and synchronizing it with production, procurement, and distribution capabilities. A good demand management process can enable a company to be more proactive to anticipated demand. 

For Croxton et al. (2002), demand management is about forecasting and synchronizing, and has both strategic and operational sub-processes, as shown in Fig. 4.2. 

Mentzer T, Moon M (2005) Sales forecasting management a demand management approach, 2nd edn. Sage, Thousand Oaks... 

For Demand Management, Statistical Forecast should be the basis due to the industry still applies the make to stock approach to optimize its asset base and reduce fixed cost. 

For demand management, it is suggested to focus in Statistical Forecast and Vendor Managed Inventory as described below ... 

In the section above, forecasting was viewed as a method of predicting demand from customers. This section examines demand management which is a term applied to all those methods used to influence customer demand. Examples include marketing promotions, advertising, customization, and... 

Demand management includes forecasting demand, accepting orders, and processing orders. It also includes stimulating demand when it is low. 

Based on these models several forecasting systems are commercially available in the market such as Predicast of Aperia, SAP Demand and Forecasting, Forecast Management by Demand Solutions and Optimate of D3S (Thomassey, 2010). 

Future human resource needs of supply chain management > Forecasting of labor supply and demand... 

This chapter considers how to get closer to the customer to determine what they really want and how to keep customers. In particular, the concept of customer relationship management (CRM) is explained. We begin with short section on the need to estimate demand and conclude with a short introduction to techniques for forecasting. As explained in Chapter 3 without some form of forecast of demand, management will have difficulty in establishing what the capacity of the operation is and what it should be. 

MODELS FOR FORECASTING, DEMAND MANAGEMENT, AND CAPACITY PLANNING... 

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