Building a supply chain network design team isn’t as simple as it sounds

These days, most companies recognize the strategic value that supply chain network design projects can deliver. But when and how to launch these large-scale projects is often an open question.

To have the greatest impact on your supply chain network, the answer is to do them continuously. Unfortunately, most companies still rely on one of two approaches to keep their supply chain networks optimized.

Periodic evaluation is no longer enough

The periodic approach operates on a intermittent cycle. In this scenario, every one to three years, the company decides to charter a project, pull together a team, gather data, run scenarios and make recommendations to change their supply chain. Unfortunately, this strategy usually results in a significant loss of time to value due to the lengthy gaps between engagements and missed opportunities for network savings as a result. Also, periodic analysis creates vulnerability to unpredictable factors such as freight fuel costs, capacity availability or changes in economic policy (such as tariffs).

Internal competencies collapse far too often

The second approach requires building an internal supply chain design team. But internal competencies often prove difficult to sustain due to the lack of critical mass. Teams of more than five people typically require mentoring and career paths. Then there are turnovers and promotions, talent scarcity and lack of executive commitment. Relying on a smaller team — one to three people — isn’t a sustainable solution either. Companies need the right scale to operate with an internal team effectively over the long term.

Hybrid structures are sustainable

A third method for supply chain design that many organizations may not realize exists uses a managed analytics strategy with a composite team. In this approach, an organization’s internal members collaborate with specialized, unbiased consultants who become a dedicated extension of that team. This structure helps the composite team maintain continuous network analyses through constant refreshing of the models. Renewal allows long-term, end-to-end supply chain decision-making and supports and encourages ad hoc project requests as well.

Unlike periodic engagements, a managed analytics strategy provides a continuous analytical value stream that allows significant cost savings. For example, over 12 months, our work with a food manufacturer found annual savings of $21 million from distribution redesign. Additionally, we located $6 million through optimizing the co-pack network and another $6 million from re-aligning a major manufacturing platform. We found another $2 million by identifying the best use of frozen distribution. The speed to this value is worth emphasizing: four separate, strategic projects were delivered within one year — a common cadence for these types of projects.

A composite team model increases speed to value by improving systems and data and enhancing processes. It can leverage the data and modeling skills of both organizations and increase the consultancy’s knowledge of the client’s business.

On the data side, composite teams become more efficient in processing as well as managing data in a more streamlined, semi-automated fashion. That includes navigating the organization’s data sources. Composite teams often identify data governance opportunities, too.

On the process side, the repetitive cycle of analytics drives efficiency. Data inputs, model designs and desired model outputs tend to be known over time. Consequently, the speed from data gathering to scenario runs can be greatly accelerated. As an example, for one client, a composite team developed processes to execute a monthly tactical model in two to three days. The same model previously took 14 to 21 days per month to complete.

Finally, continuous analytics fosters productive working relationships between the supply chain modelers and company employees on the composite team. The team works together constantly on supply chain analyses, so the composite team develops a deep understanding of not only the company’s business and problems to be solved, but also how to work effectively with each other. A culture of continuous modeling allows you to make better decisions and respond more rapidly to economic, industry and supply chain changes.

— By Dan Sobbott & Morgan Mullis