Jim Sinur

There seems to be a debate brewing over the use of simulation in an up front manner to ensure the deliverables of a process effort are baked in and tested before the “go live” date versus just iterating your way to a better model. This is an interesting topic to look at given the pressure for results that we are seeing today for a number of obvious reasons.

Pro-simulation:

Simulation not only allows organizations to try processes early with test data and validate explicit process assumptions (deliverables, activities, savings, resources, on exceptions ahead of BPM implementation, but there is much more. Simulation leverages process improvement with real behavior/data and can link simulation results with resource optimization/scheduling. In addition you can simulate decision alternatives in a reactive mode and simulate alternative scenarios in a proactive mode. Simulation is so easy today, why not leverage it?

Pro-iteration:

Why waste time and step near the edge of analysis paralysis? Why not create a good enough model and iterate to a better process over time? While this may not be the most perfect solution, you get to results fast and can quickly change to adapt to new targets and a better process. While there might be directional corrections, the basic trend line towards balanced results is there. This is a “no brainer”

Couples work:

This is not a “zero-sum” game. You can combine the best of the both and reap the benefits of both. One approach is to create a good enough model and use in line simulation to move to the desired end state quicker and reduce the number of iteration cycles. The other is to simulate basic assumptions about the savings and resources needed and iterate towards the desired end sate. Again this reduces the number of iteration cycles.