Make decisions efficiently, transparently and fairly.
1000minds Decision Making helps you to rank or choose alternatives according to multiple criteria or objectives and, depending on your application, to perform:
- Prioritization – prioritize alternatives and people in a consistent way that’s easily communicated.
- Value for money – compare alternatives’ value for money (e.g. projects, investments) and allocate resources.
- Group decision-making – include as many participants as you like, potentially 1000s.
1000minds is for ‘when good decisions matter’. (When do they not? Human history is a chronicle of both good and bad decisions – see famous quotes.)
1000minds implements our patented PAPRIKA method, which, as well as being scientifically valid, is very user-friendly (see our awards). 1000minds is fast and scaleable – e.g. depending on your application, potentially 1000s of people can participate.
In addition to our valued business and government clients, we’re honoured that 1000minds is used for research and teaching at 410+ universities and other research organizations worldwide – confirming our scientific validity and user-friendliness (see our awards).
Multi-Criteria Decision-Making (MCDM)
1000minds is based on MCDM (also known as Multi-Criteria Decision Analysis, MCDA) which involves these four key components:
- Alternatives (or individuals) to be prioritized or ranked
- Criteria by which the alternatives are evaluated and compared
- Weights representing the relative importance of the criteria
- Decision-makers and other stakeholders, whose preferences are to be represented
Most decision-making applications involve, at least implicitly, the process represented in the diagram below. 1000minds is especially useful at the “Model building” and “Challenging thinking” stages.
If you are new to MCDM / MCDA (or a little rusty!), you might find this article useful and interesting: What is MCDM / MCDA?
(From Belton & Stewart, 2002, Multiple Criteria Decision Analysis: An Integrated Approach.)
A 3-minute introduction
You can adapt or take inspiration from our library of example decision models, or build your own from scratch.