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Abstract

When a leading healthcare provider decided to reorganize and consolidate their customer portal environments under one roof, they needed to tackle both an aggressive project workload, as well as keep advancing strategic initiatives. SDLC Partners was asked to help in supporting and structuring numerous endeavors that could assist the client in reaching business goals. As a long time partner, SDLC was able to assign a top level expert and project team, who possessed intimate knowledge of the industry, culture, and business environment, to assist them during these critical initiatives.

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The Challenge

A national clothing retailer was challenged by its current inventory process which was based on Weeks of Supply. Weeks of Supply is a simple calculation which projects the duration that current inventory will remain in stock. The calculation is based off the previous week’s sales (Inventory / LW Actual Sales=WOS). The retailer’s method of tracking inventory supply was very inefficient and outdated. For instance, many factors can play into a week’s sales such as a holiday, start of a new sale/season, etc. The retailer’s growing concern was that inventory of different product lines would be depleted at a slower or faster rate according to seasons of its particular sales cycle. This would directly affect the supply lines, planning and allocation, production, shipping, etc. A wrong calculation or forecast could lead to over stocking product or missed sales opportunities.

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The Solution

To gain a more accurate picture of its inventory count and reduce the risk of inventory miscalculations, the retailer needed to engage an external vendor to develop a more efficient method. SDLC’s Business Intelligence team was called upon to assess the problem and develop a plan to remedy the issue in a timely manner. The recommendation was to create a data mart which pulled disparate data sources at varying levels of detail. The data would pull Current In-Store Inventory, In-transit Inventory, In-Process Inventory, Last Week’s Sales, this Week’s Sales, Projected Sales (13 Weeks), and expected Floorset coverage based on how much needed to be displayed in each different store/store type based on the season. The data could then be quickly pulled and analyzed to enable accurate inventory forecasts based on the individual store’s needs.

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The Results

This method enabled the client to develop a much clearer picture of their supply lines at a very low level of granularity to a high level overview painting a true picture of Forward Weeks of Coverage for each store, region, and overall company performance. This has now become the standard method of tracking inventory progress for the client.

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