IBM Research Scenario Planning Advisor (SPA) - overview
Preparing for the future is fundamental to the success of most human endeavors, from playing chess to running a multinational organization. The IBM Research Scenario Planning Advisor is a decision support system that allows domain experts to generate diverse alternate scenarios of the future and enhance their ability to imagine the different possible outcomes, including unlikely but potentially impactful futures. The system includes tooling for experts to intuitively encode their domain knowledge, and uses AI Planning to reason about this knowledge and the current state of the world, including news and social media, when generating scenarios.
The IBM Research Scenario Planning Advisor was designed to provide financial teams in IBM with support for their risk management goals. It does this by providing cognitive tools to assist analysts with two tasks: First, it provides situational awareness of relevant risk drivers by detecting emerging storylines; and second, it automatically generates future scenarios that allow analysts to reason about, and plan for, contingencies and opportunities in the future.
What is scenario planning? Scenario planning is a widely accepted technique by which organizations develop their long-term plans. Scenario planning for risk management puts an added emphasis on identifying the extreme yet possible risks and opportunities that are not usually considered in daily operations. Scenario planning involves analyzing the relationship between forces - such as social, technical, economic, environmental, and political trends - in order to explain the current situation, in addition to providing insights about the future. A major benefit to scenario planning is that it helps businesses or policy-makers to learn about possible alternative futures and to anticipate them. We use scenario planning because we cannot predict the future. We use AI planning, informed by expert domain knowledge, because some scenarios have never yet occurred and thus cannot be projected by probabilistic means. And we generate many different scenarios, exploring a variety of possible futures; because we want to be prepared for both expected and surprising futures.
Scenario planning is a plan recognition problem in disguise. A plan recognition problem is the inverse of a planning problem, where instead of being given a goal state, you are given a set of possible goals. The task in plan recognition is to find out which goal was being achieved and how. In previous work in our team and in related research, it was suggested that interestingly you can use AI planning to address the plan recognition problem and there are many advantages in using planning to address the plan recognition problem. Hence, we first characterize the scenario planning problem as a plan recognition problem and then use AI planning to generate many possible plans. In short, we transform the domain knowledge into a planning task, the risk drivers into observations, and the business implications into the set of possible goals. We then cluster these plans and present a handful number of scenarios to the users.
IBM Research Scenario Planning Advisor is currently deployment within IBM, and a number of other organizations are interested in its use. So far, the reaction to SPA has been very positive - users indicate that the tool is easy to navigate and simple to use; and that almost 80% of the scenarios generated possibly affect their organization directly or indirectly. In the research community, the reaction has been positive as well. The demonstration of our system won the best system demonstration award at ICAPS, the top conference on AI planning.
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