Application Envisioning idea
Examples from three knowledge work domains:
(Illustrated above) An architect expects the act of grouping elements together within her building modeling application to be rapid and direct. She is surprised when she is prompted to specify seemingly unimportant information about a grouping before she can proceed with unifying it.
Knowledge workers often develop strong opinions about the time and attention requirements of specific work practices (A). Workers’ abilities to make accurate estimations of effort can be considered a valued part of their expertise. Additionally, experienced individuals have often become highly skilled at completing some operations and tasks, allowing them to invest much less effort in these actions than new practitioners (D7, K6).
A financial trader “test driving” a new trading application expects the optimal pathways for certain common tasks to be as fast as they are in the tool that he currently uses. His opinions about novel functionality are more open.
A scientist, while specifying the attributes of several clinical samples in her lab’s information management application, is surprised by how quickly she is able to enter required and desired information for each sample.
Product teams can strive to make the amount of effort that workers expend in an interactive application feel congruent to the benefits that a tool provides in their work practices. People may expect some elements of their work to be less effortful after adopting computing tools (E, K), especially in tedious tasks that they find less engaging and valuable in the context of their larger goals (D3, D4). When the characteristics of a functionality concept result in workers needing to expend more effort than expected, teams can attempt to reframe users’ expectations by communicating the value of these additional efforts (C1, K2, K7).
When product teams do not actively consider workers’ expectations of effort in targeted operations, tasks, and larger activities, resulting applications may contain interactions that users view as too difficult or demanding. Especially when extra effort does not provide understood and compelling value, workers may believe that these tools are based on a faulty understanding of their needs (A4, K3). They may also feel that time spent on inappropriately effortful tasks stressfully detracts from more important work outcomes (L1).
Conversely, applications can force too much streamlining of work, removing certain interactions and awarenesses that individuals enjoy or value in a practical sense (C6).
See also: B10, C4, C8, D,
G, J1, K8, K9, M1, M4
Application Envisioning questions:
More specific questions for product teams to consider:
How much effort do targeted workers currently spend on the specific operations, tasks, and larger activities that your team is striving to mediate? What benchmarks do they use?
What do targeted individuals and organizations think of these current levels of effort?
Do people find any of their current work practices to be repetitive or tedious?
What practices do knowledge workers not want to change, despite high effort requirements? Why?
What general expectations do workers have about the impact of computing tools
on the effort needed to accomplish their workplace goals?
How do expectations of effort vary across targeted individuals, roles, organizations, and other factors?
Which of your functionality concepts will likely be recognized as significantly reducing effort in certain activity contexts? Is this a compelling value proposition?
Where might workers accept additional effort in a new computing tool if it was seen as providing additional value? How could that value tradeoff be embodied and communicated in your sketched functional offerings?
What design approaches might make work feel like it is taking less effort than it actually is? What advanced analogies to other products and domains could inform your team’s ideas about reducing perceived effort?
How might your scenarios for desirable reductions in effort factor into the story of your product’s brand?
Do you have enough information to usefully answer these and other envisioning questions? What additional research, problem space models, and design concepting could valuably inform your team’s application envisioning efforts?
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