Once everything is placed onto the chart, discuss the results and compare items, prioritizing those in the quick-wins and big-bets quadrants. For example, developers may have yellow dots and rank effort, while designers may have orange dots that represent impact on the user.Īfter team members have silently voted on items, the items can be placed collaboratively on an effort–impact matrix (the x-axis represents effort, while the y-axis represents impact) according to the number of impact and effort votes received. It’s also possible that certain team members vote on a single dimension, according to their expertise - for example, UX professionals may rank impact, while developers may rank implementation effort.Īs a first step, team members assign a vote to those items they believe to rank highest within their domain of expertise. Team members are given colored dots (one color per dimension) to vote for those items that they consider to rate highly on one or both dimensions.Ī general rule of thumb is that the number of votes per person is half the number of items being prioritized. Items are gathered on a whiteboard and their relative scores on the impact and effort dimensions are established through voting. The more technically complex the item, the higher effort it will require. ![]() Effort is the amount of labor and resources required to solve the problem.The level of impact an item will have on end users depends on the users’ need, their alternatives, and the severity of the pain point the item solves. Impact is the value the item will bring to the end user.This prioritization method uses two primary criteria to rank features that are considered for implementation: the impact that the feature will have on the end user and the effort required to implement that feature. When setting up multiple matrices, set up your axes so that the Quick Wins (or whatever the equivalent best-outcome quadrant is) is positioned in the same spot (for example, always in the bottom left position), in order to easily compare several matrices and identify the items that consistently fall in best-outcome quadrant. While we discuss impact–effort matrices in this article, you can easily replace each axis with other criteria or use multiple matrices to assess more than two criteria. Fill-ins comprise low-effort, low-impact items that may be easy to implement but may not be worth the effort as their value is minimal.Ī comparative matrix is a malleable tool.Money pit includes low-impact, high-effort items that are not worth the business investment there are better places to spend time and resources.Big bets include high-effort, high-value items they should be carefully planned and prototyped, and, if executed, are likely to be differentiators against competitors.Quick wins include low-effort, high-impact items that are worth pursuing.It can be subdivided into four quadrants: The resulting matrix captures the relative effort necessary to implement candidate features and their impact on the users. ![]() An impact–effort matrix assigns items to one of four quadrants: quick wins, big bets, fill-ins, and money pits.
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