SCDigest Editorial Staff

SCDigest Says:

After a bit of a lull following the dot com fallout, we’re seeing strong renewed interest in supply chain optimization technology, both traditional, and in new areas such as multi-echelon inventory management. What do you say? Send us your comments here

For more than a decade, optimization software has been central to many supply chain software systems and internal company supply chain initiatives.

In some cases, companies have the operations research and technical talent to build their own optimization applications in such areas as factory scheduling, transportation planning, network design, inventory management, and other areas. More often, optimization comes from deployment of packaged supply chain software applications available from dozens of vendors.

In either case, Dr. Don Ratliff of Georgia Tech University, a long-time researcher and practitioner in the area of optimization tools and technology, says optimization can offer companies substantial improvements in cost and performance.

“Supply chain and logistics optimization is neither easy nor cheap but it is the biggest opportunity for most companies to significantly reduce their cost and improve their performance,” Ratliff says. “For most supply chain and logistics operations there is an opportunity to reduce cost by 10% to 40% by making better decisions.”

1. State Quantified and Measurable Objectives:  For example, a delivery operation might define the objective to be to “minimize the sum of the daily fixed cost of assets, the per mile cost of fuel and maintenance, and the per hour cost of labor” by some percentage. These costs are both quantified and reasonably easy to measure.

2. Faithfully Represent Required Logistics Processes in Models: It’s easy to make mistakes in the model such that it doesn’t represent the way things work in the real world.

3. Explicitly Consider Variability: Too often, models associated with supply chain and logistics optimization either assume that there is no variability or assume that using average values are adequate. This often leads to errors in model results and poor supply chain and logistics decisions. Ignoring variability is generally a recipe for failure.

4. Ensure that Data is Accurate, Timely, and Comprehensive: Data is what drives supply chain and logistics optimization. If the data is not accurate and/or it is not received in time to include it in the optimization, the resulting solutions will obviously be suspect. For optimization that focuses on execution, the data must also be comprehensive. For example, having the weight of each shipment is not sufficient if some loads are limited by volume of the truck.

5. Design Fully Automated Data Transfer: Manually entering anything other than very minor amounts of data is both too time consuming and too error prone to support optimization.

6. Provide Results in a Form That Facilitates Execution, Management and Control: Solutions provided by supply chain and logistics optimization models are not successful unless people in the field can execute the optimized plan and management can be assured that the expected ROI is being achieved. Web based interfaces are becoming the medium of choice for both management reporting and execution.

7. Build Algorithms that Intelligently Exploit Individual Problem Structure: An irrefutable fact regarding supply chain and logistics problems is that each has some special characteristics that must be exploited by the optimization algorithms in order to provide optimum solutions in reasonable time. Understanding the differences in optimizer alternatives and in tuning the one selected for each problem is key.

8. Don’t Forget the People: You cannot expect a complex set of data, models and software to be operated and supported without considerable effort from people with the appropriate technical and domain knowledge and experience.

9. Support the Technology with the Right Process: Failure to put into place processes to support and continuously improve logistics optimization and react quickly to changes in the operating environment invariably results in optimization technology being either poorly utilized or becoming “shelf-ware.”

10. Calculate a True ROI: Proving ROI requires two things: (1) an honest assessment of the total cost of optimization, and (2) an apples-to-apples comparison of the solutions being produced by optimization versus benchmarked alternatives.

Comments SCDigest editor Dan Gilmore: “After a bit of a lull following the dot com fallout, we’re seeing strong renewed interest in supply chain optimization technology, both traditional, and in new areas such as multi-echelon inventory management. I think Dr. Ratliff’s guidelines are worth considering for any company starting a new initiative.”

What would you add or change with Dr. Ratliff’s 10 rules? What has your experience been on optimization projects? Let us know your thoughts at the Feedback button below.