Sales & Operations Planning (Fortune 100 Technology Company)

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In this case study learn how BRIDGEi2i helped a Fortune 100 Technology company to leverage a Teradata environment to pull Bookings, Builds and Shipment information onto 1 platform and to correlate supply chain health with KPIs, Inventory and Backlog – REAL-TIME.

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Sales & Operations Planning (Fortune 100 Technology Company)

  1. 1. A Case Study in Sales & Operations Planning A Fortune 100 Technology Company Quick Context Objective a. ~40,000 SKUs, 4 Regions, ~70 BUs, 3 Distribution Channels b. No single view of Supply Chain health in the organization which leads to low Lead-time Attainments • Ability for senior management to monitor Supply Chain health real- time • Single view to proactively identify issues for timely resolution Impact • S&OP at BRIDGEi2i spans two of our major solution areas where deep specialization has been developed over the years – Sales and SC • Domain clarity allows us to synthesize the right S&OP metrics Key Success Elements Our Approach 6 Months 3 Years Client Project length Length of relationship with client • Teradata is the single source of information for all Supply Chain related data • Simple, fast queries written directly to Production server to fetch real-time Bookings, Shipments and Builds at a product x Region level • Plan data is refreshed every month. A method to reconcile plan changes with supply chain performance is necessary • Plans and Actuals are readily available from Source – so no Algorithm was necessary • Adjustments to plans every month must be accurately reconciled with Actual performance to avoid giving a false sense of Supply Chain KPIs • Several accuracy filters were developed for this purpose • High-granularity, real-time dashboard is automated completely in SAP BO using Xelcius as the reporting platform • Queries must be fast, so all metrics were written as derived variables for calculations to be performed at real- time in-dashboard • Low latency in dashboard – high adoption in the Client SC community Data Management Algorithmic Play Operationalization a. To leverage a Teradata environment to pull Bookings, Builds and Shipment information onto 1 platform b. To correlate supply chain health with KPIs, Inventory and Backlog – REAL-TIME

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