Universal Jobs-to-be-Done Model: Interacting with a Software Feature
This jobs to be done model takes a look at how software end users evaluate their experience when interacting with the software features.
This is a special post I will occasionally publish for paid subscribers. It’s the least I can do, even though I never intended to do so
End users of a software application have to navigate through some sort of an interface layer that contains objects/elements, which hopefully provide clues as to their purpose, and whether they should be used to trigger a desired action. Many factors could cause a user to struggle as they attempt use a feature through one or more user interface elements. The goal of the designer and the developer should be to minimize those struggles for the various circumstances end users find themselves in.
This could be a used to survey a user base (after the fact) or converted into a set of worksheets for workshop participants to provide feedback earlier in the design process. Most of this should be common sense to an experienced software designer.
This is based on my modified version of Jobs-to-be-Done modeling using inputs from a number of thought leaders who I take very seriously. It may not be perfect, but it’s better, much better, than failing fast.
⭐ Note on model integration: this universal model is designed to provide tight integration between metrics and steps, steps and the job, and ultimately the job and related jobs, or the job as a step in a larger job. This system is used to test-fit components of the model while building it, as well as to elaborate the prioritized metrics that describe a struggle within a segment into a compact and portable job story
Job Story Structure
As a [Job Executor] + who is + [Job] + [Situation] you're trying to [Outcome] + "faster and more accurately" so that you can successfully [Job Step]
Example:
As a software end user who is interacting with a software feature you're trying to know which user interface element will trigger the desired action faster and more accurately so that you can successfully identify the feature you need to use