How To Estimate and Prioritize UX Work (Framework) (https://lnkd.in/eGQrPm2N), a very practical guide on how to choose and estimate the right level of research and UX work needed for a successful outcome of a project — along with the process to follow and UX estimates to set. Kindly shared by Jeremy Bird, and building on top of wonderful work by Jeanette Fuccella.
🤔 Planning is typically done for the delivery phase only.
🤔 Design, research, discovery, ideation are not planned.
🤔 Effort, estimates, roadmaps, capacity are rare for UX work.
🚫 Not every project needs the same level of research/design.
✅ Goal: set realistic expectations for UX work in a timeframe.
Jeremy suggests to estimate research and design efforts separately, and across different dimensions: we assess research by mapping Risks and Problem Clarity. And we estimate design effort needed by mapping Risk and Level of Complexity:
🔮 Clarity: Low ↔ High
New, unknown problems usually come with a lot of assumptions and very low clarity. Well-known problems with shared understanding in the team and some extensive research have higher degree of clarity.
🔥 Risk: Low ↔ High
Some projects are relatively easy to roll back and they don’t really affect business-critical workflows (low risk). Others are much more difficult to reverse and operate within users’ key journeys (high risk).
🚀 Complexity: Low ↔ High
Self-contained projects in well-understood workflows are typically straightforward (low complexity). Some projects that involve many systems, external dependencies, stakeholders scattered across teams with little existing knowledge (high complexity).
✅ We start by defining a problem to solve + business impact.
✅ Then, we shape desired user outcome and success criteria.
✅ Next, we assess design effort and research effort levels.
✅ Run a kickoff meeting to prioritize and decide the scope.
✅ Designers break down UX work, estimate it, add to Jira.
Estimates are hard to get right. Even with 20–30% buffer, I’m often underestimating the little nuances, blockers, constraints, unknown unknowns and bottlenecks hidden somewhere between complex dependencies and unresponsive stakeholders.
Considering risk early is a very, very effective way to guide UX work in the right direction. High risk always requires some level of research and discovery. And early prioritization helps UX teams focus their effort where they add most value.
Finally: I can highly recommend to consider Effort vs. Value curves (https://lnkd.in/evrKJUEy) for prioritization work as well. Much of the work isn’t completed once it’s delivered. More often than not, it will significantly add to maintenance costs over time. We better account for it early.
#ux #design
How to estimate and prioritize UX work
Always look out for the “perfect storm” across 3 dimensions: frequency, severity and user’s frustration. If users have to use a particular flow repeatedly, it’s a good idea to invest time and effort there — it’s a busy “path” that requires attention.
1. Frequency: “How often do you do this task? (Daily, weekly, never)”
2. Severity: “What is the consequence of this task being done incorrectly?”
3. Frustration / Effort: “How frustrating and difficult is this to do currently?”
It makes sense to prioritize tasks with high severity, high pain and higher frequency — we will probably be spending around 80% of our effort there. However, also pay attention to tasks with low severity but high frustration — they might be candidates for automation or deletion.
Finally, beware of tasks with high severity but low frustration — we don’t want to break what actually works for people; and we might be better off deprioritizing tasks with low severity and low frustration. The work there will be not particularly impactful, and there are probably other areas which need your attention more urgently.
Full article: https://www.linkedin.com/pulse/breaking-down-complexity-task-analysis-ux-vitaly-friedman-sjt4f/