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Supply Chain Innovation – Driving Latency from the Supply Chain

By Jeff Bodenstab21 Apr 2015

A shift in supply chain planning is underway. The traditional hierarchical supply chain model is changing due to a tightening link between planning and execution.

One form of this new strategy is called “Predictive Commerce” which connects upstream demand sensing with downstream supply chain planning and execution in a single model. It moves closer to real-time execution with continuous re-planning—taking advantage of increased granular demand visibility down to the SKU-Location level.

Planning processes today are mostly disconnected and disjointed, often operating in technology and business process silos. A 2014 benchmarking study by Supply Chain Digest showed that 83% of 400 responding planning executives characterized their planning environment as poorly to moderately integrated at best. For example, many companies perform “product flow optimization” (optimizing routes for product flow within the supply chain) but don’t communicate these policies to inventory optimization—losing information crucial to a better stock mix.

The foundation of a Predictive Commerce application is an integrated predictive forecasting and dynamic replenishment model. It takes advantage of new ways to capture the demand signal and its impact on the supply chain. It leverages data readily available from ERP (but not used to its greatest benefit) or a Demand Signal Repository (DSR) for cross-functional decision making.

The added visibility allows each supply chain function to make smarter trade-offs to manage and control “total cost to serve”, a key metric of supply chain performance. These include strategic functions such as business scenario planning; planning functions such as demand sensing and multi-echelon inventory optimization; and execution optimization, such as order fulfillment, load building and transportation route optimization.

Forward-thinking companies are using Predictive Commerce techniques to improve supply chain process and business performance:

  • Reduced Latency in the Planning Process—Decreasing planning time and increasing high-quality decision making frequency lifts customer satisfaction, asset utilization and profitability, and reduces transportation and inventory costs.
  • An “Outside-In” Approach—Moving from a mind-set of “what are we going to make today” to “what are we going to sell today” is the “outside-in” approach to demand management. Outside-in utilizes demand streams like order-lines, POS data, web-based transactions, and customer warehouse data to improve demand insight
  • Convergence in Planning and Execution—Capturing an integrated demand signal and propagating it across the value chain gives visibility to logistics, manufacturing and customer-facing teams.  Synchronizing upstream and downstream functions allows them to deliver improved service with the most effective cost structure.
  • Collaborative Decision Making—Shared decision making bridges organizational silos, creating a bi-directional flow of information that increases the likelihood of repeatedly achieving desired business outcomes.

Next week we will review how some companies are getting started in Predictive Commerce.

Click below to read a brief on Digital Transformation in Supply Chain Planning.

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