Managed services in network design

Yogi Berra said he really liked Little League Baseball because it kept the parents off the streets.

Well, effective supply chain management keeps logistics professionals off the streets and fully absorbed. It can be compared to wrestling a gorilla: You keep going until the gorilla wants to stop, and, in the case of supply chain, that seems to be never.

There are probably as many supply chain operating models as there are companies and academics—all with distinct flavors and colors. The key question is how do you pick the right model for your specific set of circumstances?

Clearly, there’s a distinct difference between supply chains, depending on product mix and service requirements. Coal and grain are markedly different from apparel and electronics, so there’s no single strategy that is universal.

One of the vital decisions to be evaluated and analyzed is the degree to which you can—and want—to “variablize” your supply chain in order to optimize performance and harvest value. Of course, the model changes depending on your corporate structure.

For example, in low-margin businesses with high fixed costs, converting certain expenses from embedded to variable can help reduce risk when times get tough. In high-margin operations, where supply chain costs are a negligible percentage of revenue or cost of goods sold (COGS), it may make little difference.

So, the key questions are:

• What does supply chain optimization look like for me?
• Where are we today?
• What does “good” look like and where do we want to be?
• What are the gaps?
• What is the best and most effective way to close those gaps?
• What and how much should I attempt to do in-house versus contract with a managed services provider?
• How do I find the right partner(s)?

Supply chain veteran Yei Sung Kim, senior manager from EY Business Consulting says: “A managed service network optimization would be considered opex, rather than capex, making the approvals process easier for the organization. It would also allow your organization to free itself from hiring highly specialized labor full time for certain work [e.g., freight sourcing and optimization] that occurs once every three years to four years.”

A fundamental view of supply chain optimization is providing the highest level of service my customers need at lowest total landed cost. Easy to say, much harder to do, in part because of constantly shifting conditions and priorities, not to mention that each vendor and customer has their own set of unique set of requirements.

So how best to manage all of the moving parts?

Artificial Intelligence (AI) will assuredly affect the ability to better manage supply chains by enabling the automation of many repetitive, non-value-added activities beyond what’s being done today—and do it much more quickly and accurately—optimizing asset utilization.

The process for continuously updating real-time changes in transportation services, as an example, is one way to amp-up supply chain performance. Advanced algorithms, such as those used by Uber and Lyft ride-sharing services enable the highest and best use of expensive assets—vehicles and drivers—to minimize non-productive downtime and non-revenue miles.

That’s something that improves both service and cost and is simply not feasible to do with humans. This type of application is now migrating into trucking services and potentially other forms of transport. It can also be employed to improve inventory management by tracking and monitoring stock levels and sorting out replenishment requirements without having extensive manual intervention.

In those cases where contracting for services is a better bet than doing them in-house, one of the key challenges is working with third-party logistics (3PL) providers and sustaining value over time. An illustrative scenario might be as follows.

• Year 1: Shipper elects to outsource transportation management to a 3PL on the promise of taking 10% out of freight cost. At the end of year one, low and behold, operating costs have dropped by the promised amount.
• Year 2: Additional benefits are sought by continuing to aggressively manage and improve operations, resulting in an additional 2% to 3% reduction in costs.
• Year 3: The fruit of the benefit has had virtually all of the juice squeezed out of it, but the 3PL fees remain the same, or may even rise.

This scenario is not uncommon and leaves the shipper in the position of either continuing to work with the 3PL to find alternatives; shave the 3PL staffing and fees because the incremental benefits have functionally evaporated; or start the whole process over and try to find a new player with new ideas and new methods. And, of course, there’s the option of in-sourcing it all again.

None of these are optimal, but the new promise of AI-enabled operational improvements just may be the most innovative and transformational path toward continuing sustainable benefits—something to consider and explore more deeply.