IBM Planning Analytics and Decision Optimization Demo – Race Against the AI


In October we organized a challenge for IBM Think Helsinki participants at our booth. The goal was to create an optimal shopping plan for purchasing Christmas presents. The challenge was to minimize expenses while still having time to purchase each specified gift in time.

The competitors raced against an optimization algorithm. With an analytical approach and a bit of luck, the top 13% of them found the optimal shopping plan. This took them 3 minutes on average. The algorithm, on the other hand, spent less than 10 seconds to find the optimal plan and to prove that there is no better option.

The competitors performed well and realized the benefits of optimization algorithms. They can be used to improve planning quality as well as saving time for the human planner. The real-world problems are much more complex than the problem used in this competition. The number of possible solutions grows exponentially with the size of the problem, but a good optimization algorithm can find the best solution very quickly despite this.

In our competition the planning was done in IBM Planning Analytics and IBM Decision Optimization. The optimization algorithm could be run by pressing a button in Planning Analytics. Using this setup, a human planner could edit values, save scenarios, create visualizations, and quickly obtain the optimized solutions for each scenario.

On the video you can watch what the competition was like and how the algorithm provides the optimized solution to a new scenario.

IBM Planning Analytics and Decision Optimization Demo

If you are interested in optimization and Planning Analytics, please don’t hesitate to contact us.