Demand chain
The demand chain is that part of the value chain which drives demand. Concept. Analysing the firm's activities as a linked chain is a tried and tested way of revealing value creation opportunities. The business economist Michael Porter of Harvard Business School pioneered this value chain approach: "the value chain disaggregates the firm into its strategically relevant activities in order to understand the costs and existing potential sources of differentiation". It is the micro mechanism at the level of the firm that equalizes supply and demand at the macro market level. Early applications in distribution, manufacturing and  purchasing collectively gave rise to a subject known as the supply chain. Old supply chains have been transformed into faster, cheaper and more reliable modern supply chains as a result of investment in information technology, cost-analysis and process-analysis. Marketing, sales and service are the other half of the value-chain, which collectively drive and sustain demand, and are known as the Demand Chain. Progress in transforming the demand side of business is behind the supply side, but there is growing interest today in transforming demand chains. Without marketing / supply chain management (SCM) cross-functional collaboration, firms cannot  be expected to respond optimally and promptly to customers' requirements. Challenges. At present, there appear to be four main challenges to progress in transforming Demand Chains and making them faster, leaner and better: Linking supply chains to demand – "demand driven" v "forecast push". The challenge of improving the link between demand and supply has occupied many supply chain specialists in recent years; and concepts such as "demand-driven supply chains" (Demand Driven MRP), and customer-driven supply chains have attracted attention and have become the subject of conferences and seminars. The fundamental attribute of a "demand driven" supply chain is , unsurprisingly, that material movements (or replenishment execution) are directly triggered by demand itself. Those parts of a supply chain that directly responds to orders, such as "make to order" or "assemble to order" are, therefore, "demand driven". "Make to stock" supply chains can also be "demand driven" if individual echelon replenishment quantities are determined by the need to simply replace stock that has been consumed by the immediate downstream activity (i.e.. sold to a customer, used by a manufacturing process or moved to another distribution location). This is in contrast to "forecast push" supply chains in which the customer facing  echelon replenishment quantity is calculated using a forecast of future requirements and a minimum stock balance (i.e. safety stock) while all upstream activities are coupled directly to the forecast using MRP calculations. Due to inevitable forecast inaccuracy, "forecast push" supply chains suffer excessive and unbalanced stock levels and, despite a great deal of expediting (and associated costs) are prone to service issues. Such supply chains also experience the bullwhip effect. This occurs due to forecast error being amplified as it cascades up the supply chain and it has the unintended consequence of driving up supply chain costs and service issues , due to supply capacity being unable to meet the spiky demand pattern and the entire chain becoming unstable as a consequence. By contrast, "demand driven" supply chains are protected from the need to be buffered from variability and bullwhip by the impact of "process decoupling' and are thus able to meet planned service levels with significantly lower inventory levels and capacity costs.("Factory Physics" 1996, Hopp & Spearman) "Demand driven" supply chains do use forecasts for the purposes of planning – but not replenishment execution. Forecasts are used for capacity and financial planning which are the main components of "Sales and Operations Planning . The accuracy and strategic value of S&OP is actually enhanced when supply chains are demand driven" because they are less prone to unplanned capacity utilisation, "fire fighting" and focusing upon resolving current performance issues (i.e.. inventory and service). "Demand driven" supply chains also use forecasts for Event Management (e.g.. stock build for anticipated events) when postponement strategies are not an option. Despite academics having, for many years, written a great deal about the benefits of driving supply chains with demand (e.g.. Forrester 1958, 1961 - "Industrial Dynamics"; Burbidge 1983 - "5 Golden Rules for Avoiding Bankruptcy"; Christopher & Towill 1995), only since 2002  have 'demand driven' concepts begun to be adopted by supply chain management software providers and industry. (e.g..Lean Planning, Demand Flow Technology, Demand Driven MRP Information systems. Information about activities and costs is an essential resource for improving value chain performance. Such information is nowadays readily available for the supply chain, due to the widespread implementation of ERP technology (systems such as SAP), and these systems have been instrumental in the transformation of supply chain performance. Demand chain IT development has focused on database marketing and CRM systems. Demand driving activities and associated costs are still recorded in an inconsistent  manner, mostly on spreadsheets and even then the quality of the information tends to be incomplete and inaccurate. Recently, however, marketing resource management systems have become available to plan, track and measure activities and costs as an embedded part of marketing workflows. Implementation of MRM systems often reveals process issues that must be tackled, as Gartner have observed Process improvement. Processes in the demand chain are often less well-organised and disciplined than their supply side equivalents. This arises partly from the absence of an agreed framework for analysing the demand chain process. Philip Kotler and Robert Shaw have recently  proposed such a framework. Describing it as the "Idea to Demand Chain" they say: Budget segmentation, targeting and optimization. Demand chain budgets for marketing, sales and service expenditure are substantial. Maximising their impact on shareholder value has become an important financial goal for decision makers. Developing a shared language across marketing and finance is one of the challenges to achieving this goal. Segmentation is the initial thing to decide. From a strategic finance perspective "segments are responsibility centers for which a separate measure of revenues and costs is obtained". From a marketing perspective "segmentation is the act of dividing the  market into distinct groups of buyers who might require separate products and/or marketing mixes". An important challenge for decision makers is how to align these two marketing and finance perspectives on segmentation. Targeting of the budget is the final thing to decide. From the marketing perspective the challenge is how "to optimally allocate a given marketing budget to various target markets". From a finance perspective the problem is one of resource and budget allocation "determining the right quantity of resources to implement the value maximising strategy". Optimization provides the technical basis for targeting decisions. Whilst mathematical optimization theory has been  in existence since the 1950s, its application to marketing only began in the 1970s, and lack of data and computer power were limiting factors until the 1990s. Since 2000, applying maths to budget segmentation, targeting and optimization has become more commonplace. In the UK the IPA Awards have documented over 1000 cases of modelling over 15 years, as part of their award process. The judging criteria are rigorous and not a matter of taste or fashion. Entrants must prove beyond all reasonable doubt that the marketing is profitable. It enables marketing to be brought centre stage in four important ways  First, it translates the language of marketing and sales into the language of the boardroom. Finance and profits are the preferred language of the modern executive suite. Marketing and sales strategies have to be justified in terms of their ability to increase the financial value of the business. It provides a bridge between marketing and the other functions. Second, it strengthens demand chain accountability. In Marketing Departments awareness, preference and satisfaction are often tracked as alternative objectives to shareholder value. In Sales Departments, sales promotion spending is often used to boost volumes, even when the result is unprofitable. Optimization modelling  can assess these practices and support more rigorous accountability methods. Third, it provides a counter-argument to the arbitrary cutting of demand-chain budgets. Return on marketing investment models can help demonstrate where financial impact of demand driving activities is positive and negative, and so help support fact-based budgeting. Finally, demand-chain profitability modelling encourages a strategic debate. Because long-term cashflow and NPV calculations can show the shareholder value effect of marketing, sales and service, strong arguments can be made for putting the demand chain on an equal footing to the supply chain.