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Just-in-time manufacturers like Dell Inc. know what they need when they need it. This lets the company carry a smaller inventory, lower costs and still meet demand for its products. Many manufacturers have moved to streamline their forecasting processes to better anticipate and plan for customer demand. Storage managers can realize similar benefits and avoid overbuying storage by developing a forecasting methodology and creating the metrics to track it.
There are two basic approaches to forecasting: quantitative and qualitative. With storage resource forecasting, it's good practice to use both methods. In quantitative forecasting, statistical analysis is used to analyze historical resource consumption to provide a basis for determining future resource needs. Quantitative analysis provides a predicted growth rate for storage resource consumption and gives some insight into seasonal peaks that may occur, such as yearly application rollouts or semi-annual migrations to data warehouses. The chief drawback of using only quantitative forecasting is that history isn't always an accurate predictor of the future. Qualitative forecasting helps by adding the real-world
insight that's required for an accurate forecast.
Once the quantitative method has been completed and a base forecast is established, use the qualitative method to complete the forecasting process. While the quantitative approach provides historical information, the qualitative method anticipates future needs based on planned activities. With qualitative forecasting, information is gathered directly from users through regularly scheduled resource-planning meetings. During these meetings, users should provide information regarding new initiatives that may require more or less storage.
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