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Business forecasting case study

Introduction Lean practices can be beneficial for all types of organizations. The primary objective of lean is to improve organizational efficiency by eliminating waste, which in turn will lead to increased profitability. Organizational efficiency is directly linked to profitability. Often times growing businesses can find their organizations facing challenges due to inefficiencies, causing their bottom line to take a hit.
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What is Business Forecasting?

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Business Forecasting Case Study | Case Study Template

I recently performed an extensive forecast accuracy analysis for a client. The results were surprising to the customer but not to me once I had studied their forecasting techniques. The results are not unexpected. Since the forecasting methodology is primarily a tracking of the order book and its actualization as shipments, we would expect the forecast to converge toward actual as the orders are taken and to continue to converge progressively as the forecast window enters the actual Season dates. Somewhat surprising however is the amount of deviation from actual that still exists in the forecast when the season is already half over. The other surprise in the graph is how much forecast deviation exists in the forecasts 1 year prior to the Season. Clearly a supplementary forecasting model needs to be applied.
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Business Forecasting: Understanding the Basics

It is not unusual to hear a company's management speak about forecasts : "Our sales did not meet the forecasted numbers," or "we feel confident in our forecasted economic growth and expect to exceed our targets. In this article, we look at some of the methods and processes behind financial forecasts as well as the risks in trying predict the future. Companies use forecasting to help them develop business strategies.
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The following four cases are from our consulting practice and demonstrate different types of forecasting situations and the associated problems that often arise. The client was a large company manufacturing disposable tableware such as napkins and paper plates. They needed forecasts of each of hundreds of items every month. The time series data showed a range of patterns, some with trends, some seasonal, and some with neither.
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