Plan Prediction Services

Any intelligent fool can make things bigger and more complex.  It takes a touch of genius - and a lot of courage, to move in the opposite direction.     

Albert Einstein


Planticipate forecasts how different demographic groups will rate each plan.

Earlier prototypes correctly predicted people’s top-ranked plan at least 70% of the time, and the current version should improve upon this.

Planticipate is a rare applicaton of scientifically rigorous, artificial intelligence to the very human process of people-oriented policy making.

It is:

(A)  Self improving:

Every app user is asked to consider some “situation” - a client, a goal and 2-5 alternative plans for achieving the goal. 

Situations can be either one of the examples embedded within the app, or a new situation entered by the app user.

Sincere users then score the situation's plans, both for twelve, key plan-evaluation criteria and for overall desirability, and their scores are automatically sent to the cloud.  You might worry about someone connecting these scores back to you, but this actually impossible, as explained in our Privacy statement.

Hence our cloud-based dataset to slowly accumulates knowledge about relationships between plans’ criterion scores and their overall desirability.  And because every sincere app user has also supplied their demographic details, such relationships are automatically updated for every demographic category to which each user belongs.

It follows that in ANY subsequent situation, provided that you first score alternative plans on the twelve criteria,  Planticipate will forecast each plan’s overall desirability according to up to 93 different demographic groups. 

Personal biases should balance out as more and more people use Planticipate  and so its forecasts should become more accurate - the app is self-improving.

(B)  Self-monitoring:

Planticipate graphically locates its plan-desirability forecasts within margins of error, which makes it obvious which forecasts are statistically significantly different from each other.  That is, if two plans' error margins do NOT overlap they are forecasted to be significantly different from each other in terms of overall desirability.  

The app also calculates Bayesian probabilities that its plan predictions are correct – it is self-monitoring.

(C)  Self-explanatory:

Planticipate always suggest, in graphic form, why its forecasts turned out the way that they did.  It uses innovative 'face charts' which are a demonstrably superior method for quickly clarifying multi-criteria. 

More exactly, a face chart showing the priority placed upon each criterion by the relevant category of people is displayed alongside all plans' face charts that show how strongly each one scored on each criterion.  It then becomes clearer how well, or otherwise each plan scored on each of the group's important criteria.

What now?

A free online short course shows you how to properly use Planticipate  to its full potential.

And/or simply run Planticipate .

Contact us at any time by e-mail: