Academic journal article The Journal of Business Forecasting

Demand Visibility Improves Demand Forecasts

Academic journal article The Journal of Business Forecasting

Demand Visibility Improves Demand Forecasts

Article excerpt

Describes why it is difficult to improve demand visibility and what can be done about it ... the more visible the demand, the better will be the forecast ... offers a four step approach to transform disparate demand signals into a competitive weapon.

Businesses rely on forecasts, whether formal or informal, for almost every important decision. Predictions related to revenue, unit demand, capacity requirements, material prices, competitor actions and customer behaviors all drive corporate planning. A single demand forecast may influence more critical decisions throughout a company than any other piece of information. Sales quotas, marketing budgets, capital expenditures, production schedules, hiring and procurement contracts are just a sampling of the decisions that may rely upon a single demand forecast. Given the importance of forecasting, it is not surprising to learn that a recent survey of nearly 250 senior financial executives reported that forecasting demand was by far the most critical problem within their companies' supply chains.

Regardless of the amount of resources deployed in predicting the future, there will always be some level of error. Then why do companies invest in a process that by its very nature is flawed? The answer lies in understanding the tremendous business benefits that can be achieved even through small improvements in forecasting. Simply removing a single percentage point of error from a demand forecast can add millions of dollars to a company's bottom-line. In addition, AMR Research has found that for every 1% improvement in forecast accuracy, companies can expect a 2% gain in Perfect Order Fulfillment.

How well demand forecasts can be improved depends on how visible the underlying demand actually is. According to AMR Research, Demand Visibility is the ability to see undistorted and accurate demand within the timeframe necessary to react to it. The more visible the demand, the greater the likelihood of accurate demand forecasts.


There are a number of factors that are causing demand to become less and less visible:

New Product Introductions: The rapid growth of New Product Introductions (NPIs) has shortened product lifecycles and expanded the numbers of SKUs that require forecasting. As a result of shortened lifecycles, the highly unpredictable launch and sunset lifecycle phases occur more frequently and for relatively longer periods of time than ever before. Meanwhile, the SKU proliferation resulting from NPI growth has driven forecasters and standard planning tools to forecast at less desirable aggregate levels to maintain desired levels of manageability and computing performance.

Opening of Global Markets: The opening of global markets has also made demand less visible. Wide differences in demographics, seasonal factors, packaging requirements and distribution channels across the globe further add to the number of SKU-locations that must be forecasted. The more SKU-locations to be forecasted, the less visible demand becomes because of the difficulties that arise in creating and managing so many distinct forecasts. Where there are a large number of SKUlocations, the forecaster is likely to concentrate more on product family and DC level forecasts than actionable SKUcustomer level forecasts.

Difficulty in Deciphering Historical Demand: Most companies rely on historical data to help predict the future. But they find it difficult to translate historical sales into market demand. Sales, orders, shipments and invoices are common examples of historical data that are often confused with historical demand. For example, does sales data truly reflect actual demand if stock-outs prevented some customers from buying product? This dilemma is just one reason why demand and sales are not the same. Sales data reflect specific purchases made by customers, which is quite often different from what customers demand. The primary reasons for this gap are that competitor actions, promotions, pricing, and product availability drive customers to make purchasing decisions that do not always reflect their intentions. …

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