However, Davis points out that by embedding intelligent agents in a simulation that is reacting to stochastic events, when those agents provide feedback that affects the outcome at different points along the way, the simulation spins out of predictability as minor adjustments to schedules get magnified over time. Therefore, to come up with an optimal plan, a 21st century supply chain solution should be able to run through the simulation over and over to determine the impact of each change in circumstances. The end result of the simulation would not be a single fixed answer but would be a distribution, a range within a standard deviation that would allow a planner to select an outcome based on the relative likelihood of that outcome actually coming to pass and the planner's — or the company's — willingness to accept a specific degree of risk. "If someone asks how many units we'll sell next month, and someone else gives an answer of 50,000 units, that answer is always wrong if the question really relates to a process where there is lots of stochasticity," Davis explains. "The real answer to the question is to show a distribution. It may be centered on 50,000 units, but you need to see the whole distribution."
The Future is Now
Davis has been putting these theories into practice both at NuTech Solutions and at a NuTech spin-off called VGO Associates (of which Davis is president), serving clients like Air Liquide, a producer of industrial gases. For Air Liquide, NuTech used so-called genetic algorithms and ant algorithms to determine the best production schedules and distribution points across a supply network that involved 40 plants and 8,000 client sites. The optimizer created for this project took account of such factors as power prices and customer demand projections, daily power costs and efficiency for every plant, production costs based on forecasted demand, and potential maintenance and power issues at each plant. While Air Liquide does not publicize the full impact of the new optimizer, the company has enthusiastically embraced the solution and touted its contribution to helping the company make more profitable daily operational decisions, yielding significant savings while improving customer responsiveness.
When will these kinds of capabilities hit the mainstream? No time soon, at least in the solutions offered by the major supply chain software companies, according to Davis. Niche companies like NuTech and VGO Associates already offer many of these types of capabilities, of course, and leading-edge enterprises are using solutions from these firms to tackle some of their toughest supply chain optimization challenges. But Davis believes that a truly 21st century supply chain solution will evolve from the conglomeration of various point solutions into a new type of supply chain planning system. "I'd be willing to bet you decent odds that in ten years' time there will be a supply chain solution that embodies all the things I've talked about," he concludes. In the meantime, companies looking to embrace complexity and take advantage of the new science of supply chain will have to settle for customized applications if they want to plan globally and optimize genetically.