The Top 5 Factors You Need To Realize Improvements In A Supply Chain Design Project

  • septembre 07, 2022
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It takes more to deliver a successful supply chain design project than building a model that solves problems in an optimization software tool. You need a reliable model that accurately represents your supply chain and can answer your questions. You also need buy-in from senior management. If that team is confident in what you’re doing, they’ll approve the changes and the operations teams can move forward with implementation.

You can have the most detailed and accurate model in the world, but if no one believes it and there’s no buy-in, no actions will be taken. Likewise, everyone can believe in the model, but if it’s over-simplified or you’ve cut too many corners, the implementation probably won’t produce the expected performance improvements.

Based on our experience, these are the top five factors to realize savings in a supply chain design project.

1.Depth of supply chain design expertise.

This element is part of the success equation’s rigorous model. Software for supply chain design includes Llamasoft’s Supply Chain Guru and JDA’s Supply Chain Strategist. They make things easier, but skill and experience are crucial components to achieving accurate and precise results. As an analogy, knowing how to use computer-aided design (CAD) software doesn’t make you competent to design a bridge. Supply chain design is both an art and a science. Should you aggregate products? If so, how? Can you narrow down your list of potential sites? How do you handle multi-stop transportation routes? How do you convince your boss that you’ve taken the right approach? Can you prioritize complexity with limited resources and time? Confident answers to these questions come only through experience.

2. Solid data foundation.

Data is critical to building a rigorous model. We all know the saying “garbage in = garbage out.” But there are nuances; not all data is created equally. Some data sets prove more important than others. Also, depending on the questions you seek to answer, you’ll need different data. For example, you may not need customer demand data when examining reverse logistics. Or, more subtly, you may not need procurement data if the inbound shipment data is relatively clean and complete.

Data is also part of the first element in the success equation: supply chain design expertise. A skilled modeler must deftly navigate hurdles like spotty, unreliable or simply unavailable data. For instance, access to DAT Benchmark Analytics data when you need truckload rates on new lanes or accurate less-than-truckload or parcel lead-times for service time modeling provides indispensable, precise route data for networked design.

3. Repeatable process.

A process is a means by which work is completed in a way that’s repeatable and traceable. Let’s not kid ourselves—your model will need to be revised, rebuilt or refreshed either at some point in the project or in a follow-up project. This update is likely to happen many times as questions arise and people question the validity or source of the data.

Having a systematic approach that documents data sources, assumptions, procedures and design decisions will help the modeling and build confidence in the results. Which leads us to the last two elements.

4. Buy-in from subject matter experts (SMEs).

Getting SMEs and relevant functional leaders (for example, the transportation, inventory and warehousing managers) involved early in the project is an effective way to achieve their buy-in. Having a transparent process with several touch points will cement their understanding of the effort and facilitate the project’s progress.

A comprehensive baseline review meeting that includes SMEs and functional leaders is a key step in any supply chain design project. You should strive to achieve not only consensus but unanimity that the model is an accurate representation of your supply chain to answer the questions you’re asked. After many weeks (if not months) of collecting data, cleaning data, validating data and building a baseline model, there’s typically a lot of pressure to jump quickly into running the optimization and what-if scenarios. Make every effort to validate the baseline model before moving on. Doing so will avoid having to re-run corrected scenarios down the line, which may result in cost overruns, late delivery and loss of credibility.

Getting SME buy-in will greatly facilitate achieving the next element.

5. Executive sponsorship and buy-in

Supply chain design is typically a strategic or long-term initiative. On the other hand, supply chain planning functions like tendering a load, reordering raw materials or scheduling production on a manufacturing line are tactical or short-term issues. For example, to move dry cargo, shift production to other facilities and establish cross-docks, — this is one project where you’ll need executive sponsorship and buy-in. With a rigorous model backed by SMEs and functional leaders, this will be much easier to accomplish. In effect, a bottom-up approach builds trust in the proposed solution.

Bringing it all together

To achieve a successful supply chain design project requires much more than building an investment-grade model. Likewise, if you achieve buy-in at all levels of the organization but build a model with average values and oversimplification, the outcome can be much less than you expect. So, remember that a systematic approach and idocumentation of data sources, assumptions, procedures and design decisions will make for accurate modeling that builds confidence in the results. Only this will secure buy-in of a model stakeholders can rely on.”after “less than you expect.

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