Why Demand Planning?

An unsophisticated forecaster uses statistics as a drunken man uses lamp-posts – for support rather than for illumination.

• After Andrew Lang </em> All business planning is underpinned by forecasts – sales of new and existing products, availability of Raw materials. Yet no one has a crystal ball that they can peek into and see the future. For retailers, this is a serious problem – without visibility into what will sell how does one plan what to manufacture? The problems are compounded because in some cases the planning horizon could be very long stretching to years. The factors that influence sales volumes like fashion, the economy can all undergo significant changes during the planning horizon. So the question that begs an answer is that is there really any value in forecasting and using the forecasts for demand planning?
  If the pattern in demand were truly random would there be any benefit of a forecast? I suppose yes – even in such a random scenario, a mathematical approach might determine the bounds in which demand would vary thereby allowing for an optimal inventory level to minimize losses(due either under or overstocking). We will learn about how to identify if the demand pattern is random in a future post in this series.

A typical forecast function can be written very simply as $ V_{Forecast} =V_{Trend} + V_{Seasonal}+ V_{Noise} $ where $ V_{Forecast} $ is the value of the forecast $ V_{Trend} $ is the trend component of the forecast $ V_{Seasonal} $ is the seasonal component of the forecast & $ V_{Noise} $ is the noise component of a forecast ]

Although there may remain some degree of unpredictability in some components, there may be others that are evidently predictable. Trends, Cycles and Seasons may be present and foreseen. Forecasts impact and can help improve decisions around the purchasing of raw materials and at each stage of the supply chain as the raw material moves from merchants to manufacturers, and further down the supply chain to the end customer. Therefore purchase, manufacturing, distribution and markdown decisions can all be positively influenced by accurate forecasts. Inaccuracy in forecasts can lead to either over-purchasing or under-stocking and could be detrimental to the competitive advantage of the company. Over purchasing negatively affects storage space, inventory and blocks invaluable cash in unnecessary stocks. On the other hand under purchase can cause a shortage of raw materials leading to delayed products and lost revenue on account of stock-outs. Finding the right balance can thus

• Improve customer satisfaction due to increased product availability
• Improve cash reserves by reducing redundant inventory
• Increase revenue by improving product availability
• Improve margins by reducing the need for markdowns
  While forecasting accuracy is the most important aspect of demand planning there needs to be an overall strategy for demand planning. For example, strategically identifying the correct product mix to take the best advantage of the accurate forecasts could be one such step. In the next part of this series we will look at some of the traditional forecasting methods at play.