Benefits of Vecco Control Tower in Life Sciences – Part 4

Benefits of Vecco Control Tower in Life Sciences – Part 4

Product Fulfillment Improvement in a Multi-tier Distribution Environment

Scenario Name: Collaborative fulfillment improvement

Industry Segment: Companies manufacturing make-to-stock products that are distributed though a multi-tier network. Capital intensive industries (with constrained manufacturing capacity) with volatile demand (multiple branding, multiple product sizes/s, seasonal, promoted, products etc.), e.g. Consumer medical devices, nutraceuticals, pharmaceuticals, Consumer take home medical tests.

Company Size: Any

Example Company in this segment: Johnson & Johnson, Unilever, GNC, Bayer, Omron Medical Devices

Department(s): Supply Chain Operations

User: Operations Planner, VP – Fulfillment

Economic Buyer: VP Supply Chain, VP Operations

Technical Buyer: CIO, Senior Management IT

A Day in the Life (Before)

Scene or Situation: Finished goods are distributed through a network of distribution centers and warehouses. For example, a plant produces product which is then shipped to regional distribution centers and from there to certain local distribution centers owned by third parties. The plant supports local demand as well as downstream demand from the regional distribution centers. The regional distribution centers support local demand as well as demand from the independently owned local distribution centers. The local distribution centers supports purely local demand in certain defined territories.

Inventory may have effectivity dates, as for promotionally branded or priced items, or for seasonal products. It may also have expiry dates, requiring disposal or return of expired product. It may have lot numbers and require traceability of ingredients, production facilities and handlers, or even require verification of environmental conditions through the production and distribution processes.

The challenge for the operations planner is to place inventory in the network appropriately to deliver a high level of customer service, while at the same time attempt to minimize inventory carrying costs and to ensure all product effectivity, environmental control and expiry / recall requirements are respected.

A further challenge is that the various tiers in the distribution network are not all owned by the brand owner. Several parties may own various sites and the inventory in each may be under multiple parties’ control.

Inventory is “placed” in the network by defining inventory policies for each unit at each location. The inventory policy consists of a minimum level (or safety stock) and a maximum level (not always used). Additionally, if manufacturing constraints or seasonal demand cause inventory to be built significantly in advance of when it is required – then the inventory policy may also contain a build level over and above the minimum level.

Desired Outcome:

  • High customer fill rate…minimal stock-outs
  • Optimize operations costs
    • Minimize amount of transfers (non-standard shipments, e.g. a shipment from a local DC back to a regional DC)
    • Minimize network inventory required to support the target end customer service levels
  • Ensure highest standards of product safety and security
  • Ensure highest level of flexibility for meeting major retail customers’ demands, in order to gain market shelf space

Attempted Approach: The planner uses a PC based planning program to calculate a statistical safety stock for all of the products and then sets the maximum inventory for each product as a function of safety. The statistical formula requires a number of inputs based on historical results that are time consuming to maintain, as the information is not all resident in a single information system. Particularly, distributor data is hard to obtain, so the planner is not able to update the data as often as it should.

Additionally, the safety stock formula works well for some of the products, but does not produce the desired result for others. Unfortunately, there is not enough time to evaluate and implement multiple methods – so the planner simply multiplies the result of the statistical formula by a factor if he/she doesn’t think it looks right. Maintaining the data and generating the inventory policies is time consuming, so they are not updated often.

Interfering Factors:

  • Information is contained in widely disparate systems, both in-house and in partners’ systems.
  • Every time in-house systems are final standardized – an acquisition of a new product line from a firm using different IT systems occurs!
  • The mapping of local demand points to specific distribution centers changes occasionally causing problems in maintaining valid historical data
  • Substitutions cause problems for the statistical formula calculation.
  • There is not an easy way to export the inventory policy generated in the offline tool to the ERP and WMS systems that use the policies.
  • The offline program is always a step behind in terms of updates to item catalog and acceptable substitutions.
  • New product introductions and end of life transitions
  • Expiry, effectivity and lot traceability requirements

Economic Consequences:

  • Total investment in inventory is excessive
  • Desired level of customer service is not being achieved – resulting in lost revenue.
  • Transportation costs are high
  • Excessive amount of inventory transfers required to rebalance inventory in the network

A Day in the Life (After)

New Approach: The company implements a closed-loop continuous process for inventory management that adjusts rapidly to changes in the supply and demand chain – across the whole end-to-end value chain.

Real-time alerts on supply chain problems and notifications of key supply chain events are generated by the system automatically. Alerts and notifications are delivered to related users in email, SMS and other instant communication means. Generated alerts and notifications contain basic information of the issue. Alerts are escalated and delivered to related users repeatedly if actions are not taken within a specified time window. User can log onto the system to view all alerts and notifications in a single user screen. User can navigate from an alert to underlying business data to conduct detailed analyses to find the root cause of the problem. User can solely take actions or collaborate with co-workers to solve the problem. The collaboration can be achieved by issuing a problem ticket to initiate a workflow which invites all concerned parties to participate in the problem solving process in a well-defined and organized way. Once the issue is resolved, the alert disappears immediately. User can define or customize alert generation rules and subscribe to the alerts of interest. Alert summary is provided for high-level review. Reports can be generated on historical alerts.

The approach includes a platform for supporting an adaptive inventory management process with continuous product lifecycle tools consisting of the following sub-processes:

  • Automated generation of inventory target parameters (input to inventory target setting methods)
  • Generation of inventory policies (safety stock & maximum inventory): existing methods include: manual, statistical and periods of coverage
  • Inventory bounds (min & max limits) can be placed on system generated policies to smooth fluctuation of targets over time
  • Inventory policies can be time-phased to support product lifecycles
  • Ability to easily incorporate new methods & formulas into the platform
  • Metrics/reports to project inventory investment and turnover

Inventory policies can be generated and deployed by item, item group and location group. Generation of new inventory policies can be triggered manually or based on a schedule. New inventory policies are automatically exported to external planning systems.

There is a monitoring system that automatically highlights events that breach planning parameters, or may cause a future breach of parameters. Upper and lower limits can be defined on any inventory target parameter. The system triggers an alert to update parameters and generate new targets when actual results fall outside acceptable limits. Historical ending inventory, inventory targets and delivered service level are monitored against control limits to determine whether inventory target setting method is achieving desired results

Tuning capabilities include the ability to simulate changes to inventory target parameters and compare the results of different settings prior to publishing the new settings to the production environment. This also includes seamless integration with partners’ ERP, WMS and TMS solutions to ensure logistics and physical distribution capacities and constraints are respected, and the relevant partners are involved in the collaborative management process.

This solution includes finding, analyzing, solving supply chain problems and verifying the effect of the problem solving. This also includes support for generating business and network wide critical historical KPIs from supply chain data and forecasted KPIs from demand data, hence providing data for continuing improvement of fulfillment chain quality and efficiency.

Enabling Factors:

  • Vecco E2E Conductor with supply, demand and logistics capability
  • Overnight file exchanges with key suppliers
  • Overnight file exchanges with key logistics partners
  • Overnight file exchanges with distributors
  • Collaborative approach to fulfillment management

Resources Not Required:

  • No changes to existing enterprise systems at the company or its suppliers
  • No new IT hardware
  • No increase to Company data center workload, after set up of daily file exchanges

Economic Rewards:

  • Significantly improved available to promise, capable to promise commitments to customers
  • Higher speed of detecting and resolving fulfillment chain quality and efficiency problems, lower operating costs and minimized inventory losses
  • More predictable service rate – fewer lost sales due to stock outs
  • Lower transportation costs from reduction of inventory transfers and use of premium transportation
  • Lower inventory carrying costs (overall reduction in safety component of inventory)
  • Smoother product introductions and end-of-life transitions
  • Enhanced product recall capability
  • Enhanced partner and distributor/pharmacy loyalty
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