Most of these assumptions will have already been capture by the preceding tools and will automatically show up here. This is one of the most important tools in the flow. The goal here is to identify all of the assumptions within your hypothesis, prioritize them, and figure out how to get better information to help inform them. In this tool we will focus on making sure your assumptions are consistent, prioritizing them, and selecting a few favorites to work on.
In addition, there may be critical assumptions that the success or failure of your project depends on, which may not be reflected or described in quite the right way within the context of the other tools, so the Assumption Manager Tool also includes the ability to define these instead of, or in addition to, the detailed assumptions captured in the tools.
Whether they are explicitly stated or not, any new innovation project is based on a huge number of assumptions. If those assumptions are explicit, then they can be assessed and managed proactively. Unidentified assumptions at a minimum represent opportunities for miscommunication or significant differences in assessment or potential value or risk between stakeholders, if they are making different assumptions about the same choices or uncertainties; At worst, unidentified assumptions could represent hidden risks that could result in costly failures.
The goal of iteration in most innovation methodologies is to scale investment commensurately with confidence in the desired outcome through experimentation and evidence gathering on increasingly specific assumptions and uncertainties. Since resources for experimentation and evidence gathering are usually limited, it’s a best practice to focus those resources on improving confidence in the most significant assumptions first. If those prove invalid, then you can either stop or redefine the hypothesis and avoid wasting any more resources on an unviable concept. Assumptions are prioritized based on two key factors: Impact on the overall project, and the evidence the assumption is based on.
Evidence – Evidence is the data upon which an assumption is based, which can range from a complete guess or “SWAG” which represents to lowest confidence, through to “Real-world Actual Data” which are facts. The greater the evidence, the more confidence you have in the accuracy of the assumption
Impact – Impact is how materially the assumption impacts the success of the project based on the defined success criteria. For some assumptions in the Evaluation Tools, the impact can be calculated by the software. In other cases, it’s dependent on a subjective user input.
