These days, most companies recognize the strategic value that supply chain network design projects can deliver, but when and how to initiate these large-scale projects are often open questions.
To have the greatest impact on your supply chain network, the answer is to do them continuously. Unfortunately, however, most companies still rely on one of two approaches to keep their supply chain networks “optimized.”
Periodic evaluation is no longer sufficient
The periodic approach generally operates on a one-to-three year 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 ultimately make recommendations to change their supply chain. Unfortunately, this strategy almost always 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. Furthermore, periodic analysis creates vulnerability within the network against unpredictable factors such as changes in freight fuel costs, capacity availability, or even changes in economic policy (e.g., tariffs).
Internal competencies collapse far too often
The second approach requires building an internal supply chain design team. Unfortunately, internal competencies often prove difficult to sustain due to the lack of critical mass (since team sizes of 5+ typically require mentoring and career paths), turnover/promotions, talent scarcity, and lack of executive commitment. Relying on a smaller team of 1-3 people is not a sustainable solution either since companies need the right scale to effectively operate with an internal team over the long term.
Hybrid structures are sustainable
However, there is a third method for supply chain design that many organizations may not realize exists. Utilizing a Managed Analytics strategy with a composite team allows an organization’s internal members to collaborate with specialized, unbiased consultants who serve as a dedicated extension of your team. This structure allows the composite team to maintain continuous network analyses through constant refreshing of the models, not only allowing for long-term end-to-end supply chain decision making, but supporting and encouraging ad hoc project requests as well.
Unlike periodic engagements, the managed analytics strategy provides a continuous analytical value stream, allowing for significant cost savings. Over the course of 12 months, for example, our work with a food manufacturer identified annual savings of $21M from distribution redesign, $6M through the optimization the its co-pack network, $6M from re-aligning a major manufacturing platform, and $2M by identifying the best use of current for 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, enhancing processes, leveraging the data and modeling skills of both organizations, and increasing the depth of knowledge of the client’s business.
A composite team model increases ‘speed to value’ by improving systems and data, enhancing processes, leveraging the data and modeling skills of both organizations, and increasing the depth of knowledge of the client’s business.
On the data side, composite teams become more efficient in processing and managing data in a more streamlined semi-automated fashion, and also navigating the organization’s data sources. In addition, it has been our experience that composite teams often identify data governance opportunities.
On the process side, the repetitive cycle of analytics drives efficiency. Over time, data inputs, model designs and desired model outputs tend to be fully (or at least largely) known. Consequently, the speed from data gathering to scenario runs can be greatly accelerated. As an example for one client, a composite team was able to develop processes to execute a monthly tactical model in 2-3 days, where that same model previously took 14-21 days per month to complete.
Finally, the continuous analytics fosters productive working relationships between the supply chain modelers and company employees on the composite team. The team is constantly working together on supply chain analyses, so the composite team develops a deep understanding of not just the company’s business and problems to be solved, but also how to work effectively with each other.
As the need for supply chain specialization continues and talent becomes increasingly scarce, organizations should look to partner with a firm staffed with highly skilled professionals to optimize their evolving network’s needs. Companies who utilize the managed analytics model have witnessed significant benefits by teaming with individuals who have over 10,000 hours of network design experience, who utilize proprietary supply chain design methods, and who possess the technical expertise needed to handle complex supply chain networks. Maintaining a culture of continuous modeling allows the organization to make better decisions and respond more rapidly to economic, industry and/or supply chain changes.
Dan Sobbott is a Director in Chainalytics’ Supply Chain Design competency where he focuses on helping organizations optimize their supply chain network strategy.
Morgan Mullis is a Director in Chainalytics’ Managed Analytics for Supply Chain Design competency where he helps clients achieve long-term value from their supply chain network.
