We all make decisions, but how should decisions be made? The standard approach to decision-making is rule-based (also known as expert systems, knowledge-based, decision-trees, if-then-rules, case-based reasoning, or dispatch rules). This approach involves the application of a rule to a particular situation. For example, a rule for an Automated Guided Vehicle (AGV) might say that each vehicle should try to follow the shortest path leading to its destination.

Although such rules can work well for simple situations (e.g. with one AGV), they fail dismally for complex situations (e.g. with multiple AGVs). This is because rules invariably suffer from myopia - they do not take into account the long-term ramifications of a decision. For this reason, advanced decision-making systems, such as computer chess-playing programs, have abandoned rule-based systems since the late 1970's.

The other approach to decision-making - the one embodied in Oasys is model-based and currently used by world-championship chess-playing programs - involves the forward application of a model and its effects on the state of the application world. This approach can be summarized in the following three steps:

1. Simulate the effects of each decision forward in time.
2. Evaluate the expected cost of each decision sequence in that tree.
3. Choose a decision that minimizes the expected cost.

According to decision-theory, it is not possible to make a better decision than one based on these three steps. At LDI, we believe it's time businesses made better decisions by using a technology built on this proven approach - Oasys.

Scheduling systems can help allocate resources for the future. But what happens when key resources suddenly become unavailable or events create resource contention? The result is that the schedules are discarded and managers end up making decisions on the fly - decisions that might not make the best use of resources. LDI offers solutions aimed at exactly that problem: how best to allocate resources in a dynamic world.

Customers want products yesterday. But with hundreds of customers how can you satisfy everyone? With poor decision-making, your best customers can suffer from missed deadlines, incomplete orders, and costly delays. Which customer orders should be completed now? Which ones should wait? How can you make decisions in the face of such complexity?

Real-time decision-making lets you exploit a particular situation to make better decisions. Better decisions in turn improve key performance indicators such as throughput. In a large business a small improvement in throughput can have a dramatic effect on profitability. For example, a factory where throughput is improved by 5% could improve profitability by 30-40%.

All successful businesses plan for the future. But what happens when the assumptions behind the plan rapidly change? Business planners often end up making off-the-cuff decisions that might not be the best for business. Isn't it time your business responded appropriately to rapidly changing events?

Contact us at info@lookaheaddecisions.com to see how our services can benefit your business.