Network Optimization for a Successful Service Supply Chain

Best-in-class service organizations offer same day service level agreements (SLA’s) to meet expectations of customers using their products in mission critical environments. Often overlooked is the need to optimize the logistics network used to place service inventory within eight, four or even less delivery hours from the customer. While this seems simple on the surface, the complexity of analyzing drive times between a constantly changing list of customer service contracts and hundreds of stocking locations can leave basic questions unanswered.

  • What percentage of your 4-hour SLA customers can have inventory delivered within four hours from a stocking node in your current network?
  • Who are the customers that cannot be covered?
  • Which locations are no longer required due to changes in your installed base?
  • Where are new locations required to support changes in your installed base?

A successful service supply chain is built on an optimized network of sites capable of efficiently fulfilling customer demand. Baxter Planning offers a Network Optimization consulting engagement to help Prophet customers validate their current network and recommend changes by modeling the impact on customer coverage.

Find out for yourself how Baxter can optimize your service supply chain inventory.

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The Framework for Network Optimization Consulting

Baxter’s Network Optimization consulting engagement is performed in 3 stages:

  1. Discovery: All Network Optimization projects begin with an in-depth review of the customer’s current network. Our Network Optimization Questionnaire helps Baxter experts understand your unique network, coverage agreements, current logistics costs, and specific network optimization goals.
  2. Modeling: The Baxter Consulting team takes findings from the discovery phase and utilizes Prophet’s powerful Network Modeling module to generate scenarios that explore the viability of different network structures. These network scenarios are customized depending on your organization’s goals, whether it is to evaluate potential locations to add, identify under-utilized locations to remove, or perform a regular validation of current network capabilities. These scenarios can be reviewed individually or Prophet’s Networking Modeling tool also includes functionality for comparison of multiple network configurations.
  3. Analysis: Baxter consultants facilitate the analysis of the modeled network scenarios by providing data supporting any recommended network changes as well as analytics detailing the impact on key operational metrics. This includes a map visual depicting stocking locations alongside customer install base both before and after modeling, a comprehensive list of any sites added or removed, and any change in customer coverage. The Baxter team will also provide analytics that enable the customer to understand the impact on key metrics such as change in inventory investment, improvement in projected service level, any impact to transportation costs, and savings in warehousing inventory costs.

Why Wait?

Inventory managers often believe that setting a minimum stocking levels for all materials will guarantee material availability and improve service levels but that may not always be the case. Stocking one unit everywhere using overrides or minimum service level constraints is generally not an optimal strategy. For example, setting a blanket service level of 95% will apply equally to all parts across all locations. That means that very expensive parts with a low failure probability will require stock at every location since a stockout would yield a 0% service level. However, taking a total cost optimization approach means that a planner may rather accept the risk of stockout since the cost to expedite once every 12 – 18 months may be lower than proliferation of expensive or bulky material.

Conversely, parts with low cost and high volume, for which it would be unthinkable to have a stockout, may have their target stocking levels capped at the blanket 95% service level in locations where it would make more sense to stock 98% or higher. In other cases, customers set safety stock rules to keep one unit at all locations supporting install base, but this discounts any differentiation based on customer, SLA, or location attributes. We may be able to achieve acceptable service level over a large group of install base with less inventory if the install base population is dense and the replenishment lead-time is short. Conversely, we may need to stock more parts for the same size of install base (resulting in a higher service part to install base ratio) in sparsely populated or geographically hard to reach areas.

Network Optimization Software, Service Supply Chain, Prophet Software