By Dr. Rajiv Saxena, APL Logistics
Look beyond the surface of the dramatic transformation in logistics, and you’ll discover one recent ‘trend’ that is anything but new and just as likely to be earning praise 10 years from now: supply chain optimization.
Optimization is the process of using systems, models and complicated mathematics to search out and identify the best-case solution for a challenge. Introduced in the 1940s, it’s been widely accepted in the engineering profession for years. However, it wasn’t until recently that it entered the logistics vernacular and became a cornerstone of many companies’ supply chain efforts.
Like many of today’s business developments, at least part of the reason for this change lies thousands of miles away.
Since China joined the World Trade Organization in 2001, more than $50 billion in manufacturing investment has moved there, and more growth is expected. As a result, Asia has grown to be one of the world’s preferred manufacturing continents, and the U.S. companies that have shifted their manufacturing there have found themselves faced with a staggering number of unfamiliar supply chain variables: multiple countries, cultures, carriers and modes, just to name a few.
This has made it difficult for many businesses to use one of their most effective supply chain planning tools—past experience—with any degree of confidence. The international history simply isn’t there yet. In light of this, optimization has proven to be a very effective and expedient supply chain planning alternative.
Other factors that have made optimization increasingly relevant have been U.S. port congestion, rising fuel prices, the current truck driver shortage and the numerous natural and manmade disasters that have occurred in recent years.
Optimization Basics
Optimization is effective for addressing strategic, big-picture issues, such as logistics network design (choosing how many facilities you should have and where they should be located), inventory deployment policies optimization and supply chain contingency planning. However, it can be equally useful when applied to more tactical opportunities, such as facility layout, product slotting, mode selection, route selection and carrier selection.
Moreover, it has many plausible starting points. For example, some experts say it’s best to optimize every time your company reaches a watershed. Others advocate optimizing based on pre-established intervals—every day for freight, every few months for a dedicated fleet or every year or two for a distribution center network. Some favor a path that’s familiar to anyone who remembers the halcyon days of Total Quality Management: beginning where your clearest and largest pockets of inefficiency exist and moving on from there. The beauty is none of the experts are wrong. When it comes to optimization, any time or place can offer room for improvement.
Optimization is often mentioned in the same breath as supply chain simulation, another popular decision support technique. The latter uses computer-generated processes to provide detailed, real-world answers to logistics challenges or questions.
Optimization offers a few advantages that simulation doesn’t. For one thing, it’s more forgiving in terms of the inputs companies need to get started. A simulation requires very specific and detailed facts and figures, and often, companies don’t have these detailed figures readily available; by contrast, optimization often allows you to provide inputs based on ballpark assumptions or commonsense estimates, and that can be helpful when you’re treading new ground.
Downside
Despite the many merits of optimization, it does have one powerful limitation: It’s only as good as the professionals who perform it.
There is no such thing as an Optimization for Dummies book or an “Optimization 101” course to which you can send your most technically oriented people. And, even if there were, you should be leery about using them because you can only make this complex process so easy.
Optimization tools need to be used by people who understand how they work and know how to capitalize on the full functionality of the systems. And, often, that requires hiring—and budgeting for—professionals with advanced degrees and substantial engineering backgrounds.
The important things businesses need to know:
- Optimization works;
- Optimization pays;
- In a world where nobody’s perfect, it will always be relevant.
Next Steps
Hire the right resources . Optimization's complicated, linear, non-linear and integer mathematical models require engineering aptitude. Put people in place who can 'do the math.'
If possible, start by optimizing your supply chain network. Start your optimization at a level that’s as strategic as possible because that’s probably where your exercise will yield the most dividends.
Don’t fence it in. If you limit your use of optimization to strategic exercises, such as contingency planning, you’re missing a significant opportunity to improve and fine tune many tactical elements of your supply chain.
Set quantifiable goals for your optimizations. You need to have specific measures for how you will know if your supply chain has been improved.
Where appropriate, reinforce your optimizations with simulations. Optimizations are excellent for finding best-case solutions for logistics challenges. Simulations are great ways to see how those solutions will play out, given certain circumstances.
If you don’t want to commit to an in-house optimization team, consider outsourcing. Many third-party logistics providers have in-house optimization departments.
Rajiv Saxena is vice president, global supply chain engineering for APL Logistics, which provides a wide variety of supply chain services and operates more than 20 million square feet of distribution space on six continents.
