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BPM Optimization and Simulation


Jim Sinur is up next on optimization and simulation. The world is changing fast so he sees the use of optimization and simulation becoming broader than its traditional role of improving existing process. Optimization and simulation allows:

  • Try new processes in a safe environment
  • Give business people power to try changes before they go live
  • Help in scenario planning.

Key issues then are why optimization and simulation are important, how they help you survive and thrive and how you can get started.

Jim sees about 25% now using some kind of simulation v 5% a few years back and of them very few are using live data. Gartner defines optimization / simulation as using analytic tools and models to maximnize business process and decision effectiveness by examining alternatives before, during and after implementation and execution. Jim argues that we need to do more than we currently do – we need to be able to predict not just explain, do analytics inline not just offline and derive new events not just manage existing ones. But why is this important? We want to know how you can improve a process, add steps to it; or improve the decision making within the process; or make a more decision-centric process.

Companies can divide processes up into knowledge-worker, process-worker or computer-controlled processes and can use optimization and simulation to drive processes from expensive knowledge-worker processes to increasingly computer controlled ones. They can drive work to cheaper approaches and so free up people to work on higher-value work. You can monitor results and adjust policies as processes execute. You can, and should, develop and test scenarios to prepare and be proactive about changes.

Common uses of simulation are to try processes with test data and validate explicit assumptions. Companies are also using simulation to try different decision alternatives and process design changes. Optimization is coming too with predictive analytics, goal-directed processes, intelligent decision management with pattern recognition and data mining.

Simulation is the easiest place to start. Companies can create a sandbox to try things out to start creating a sense of the power of simulation. People can only use this if they are analytically minded and have access to good performance data. They need to be able to change process flows and rules, design and use dashboards and they need communication skills to share what they learn and persuade people to adopt it.

Gartner recommends building a simulation and optimization arhictecture incrementally. Logging process and rule changes as well as alerts of interesting events. Business Acitivity Monitoring, Data Mining/Analytics, rules and models are all required. Building a tool box to move from data/correlation/trends to understanding why with immediate feedback and an understanding of delayed effects. Ultimately it creates the ability to anticipate. But all this requires a culture change that focuses on actionable insight, sense and respond, alignment.

Pitfalls include technology that is not accessible to those who understand the business, lack of understanding of the concepts, invalid assumptions, solving for local optima and poor models.

Optimization and simulation contributre to survival because eliminate inefficiencies, find places that need attention and pre-test process and decision changes before deploying them. So, companies should focus on processes necessary for survival and use simulation to see how they could be improved. Soon, get focused on optimization in decision making and process design and make this part of the improvement cycle.

BTW Network problems are preventing me posting live from the show and meant I lost my whole keynote post – check out Sandy Kemsley’s post instead.


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