Demand Management How Demand Management

Demand Management

How Demand Management and Production Planning Are Linked to Logistics Planning -- a Critical Analysis

The ability of any organization to accurately predict individualized product demand and aggregate forecasts so that production and logistics planning can profitably fulfill sales is the essence of best practices in demand management. The intent of this analysis is to evaluate the role of logistics planning in creating a more demand-driven enterprise. There are a multimode of factors that influence demand management accuracy and performance, also influencing production and logistics planning and execution. One of the most difficult to anticipate and accurately predict is consumer demand for new products (Croxton, Lambert, Garcia-Dastugue, Rogers, 2002). Another is how pricing and product strategy decisions will influence demand for products at the mid-point of their lifecycles, especially with industrially-oriented products that are typically price inelastic (Hilletofth, 2011). Third, industries that have very high levels of seasonality and often see their entire product lines change rapidly as does the fashion industry does for example also make demand management particularly difficult (Jacobs, 2006). All of these factors together however have a major impact on the accuracy and performance of logistics systems, as they are often the most dependent on accuracy of forecasts and assessment of market conditions (Moodie, 1999). Logistics system in general amplify just how accurate and based on reality sales estimates and forecasts are (Godsell, Christopher, 2006).

Analysis of Key Success Factors for Unifying Demand Management, Production Planning and Logistics Strategies

The literature review undertaken to complete this analysis led to the definition of many diverse key success factors that are the most critical for unifying demand management, production planning and logistics strategies. The most critical of all is the ability to create consolidation financially-based view of all activity across each of these three core process areas of an enterprise (Moodie, 1999). The quality of the accounting and financial data that gives insights into which products are delivering the highest possible margin is one of the most valuable benefits of these enterprise-wide accounting and financial management systems (Hilletofth, 2011). Where these systems deliver the greatest value is in gaining insights into which products to discontinue or not, what the costs of keeping marginal products are, and how the most successful products are performing from a profitability standpoint (Jacobs, 2006). When this spectrum of profitability is known, logistics strategies can be quickly prioritized and those products with low and reduced profitability are managed more aggressively to cost targets (Godsell, Christopher, 2006). When an enterprise knows this spectrum of profitability by product there can be much more effective planning undertaken when time is the most limited resource an enterprise has in prioritizing their logistics strategies. Profitability analysis using demand management can also streamline production planning as the relative level of gross margin generated by product line needs to guide just how much production time and raw materials are dedicated to a given production plan (Croxton, Lambert, Garcia-Dastugue, Rogers, 2002). Profitability analysis as dictated by an accurate market forecast, captured as part of demand management planning, can drastically reduce wasted shipments, orders of low or no priority, freeing up hundreds of hours and millions of dollars in logistics systems costs (Hilletofth, 2011).

A second best practice that has emerged from this analysis is the finding that those industrially-based companies who have extensive investments in Product Lifecycle Management (PLM) systems have been able to gain greater control over product line extensions and transitions by coordinating more closely with demand management and logistics systems. PLM systems can accelerate logistics process and strategy performance based on the increased quality and quantity of information captured over the lifecycle of products (Godsell, Christopher, 2006). This approach relies on capturing knowledge that is both tacit and implicit within the enterprise, translating both of these types of information into greater intelligence that logistics systems can use for more efficient, economical operations (Godsell, Christopher, 2006). This best practice is prevalent throughout the fashion and retailing industries, as these logistics systems must be finely tuned to demand management and production planning for enterprise to be profitable (Jacobs, 2006).