The unique insights provided by an operations science flow analysis led this company to achieve a massive increase in throughput and efficiency in a couple of months.

Last week we were below goal. that was terrible. This week we are above goal. Terrific, pizza for everyone! Are you just reacting to noise in the system? If so, you’re just increasing variability and its associated buffering requirements and, at the same, time creating unnecessary stress for your people.

This week we provide specific examples of leading and lagging measures. Leading measures track causes, not effects. To see the effects, track lagging measures which provide understanding of whether the causes were accurately described–true scientific thinking.

Measures motivate behavior. This week provides a list of important characteristics of measures used for measuring individual performance. Also provided are specific examples of these measures, including examples the average view may not have seen before.

Don’t be overwhelmed with measures and KPIs. In the operations science framework, required measures naturally surface. There are the vital few and everything else is just window dressing.

Don’t let your continuous improvement efforts end up just going through the motions. See how operations science helps you supercharge any process improvement efforts.

Organizations see repeated occurrences of poor performance even after investing tremendous amounts of money and time in implementing new software. This does not have to be.

Computers are much faster than people at processing information. This causes an excessive feedback problem that many don’t recognize. Companies invest millions and billions of dollars in IT but still end up with poor on-time delivery and high cost.

The operations science model for operations management provides quick improvements and long-lasting success.

Efficient frontiers provide a great benchmark of where your inventory performance is versus where it could be.