100 APPLICATION ENVISIONING IDEAS | F. ENHANCING INFORMATION REPRESENTATION
WORKING THROUGH SCREENS
F5. Comparative Representations Knowledge work can involve standard comparisons, based on known and meaningful criteria, between work artifacts. Product teams can envision functionality concepts that automate certain comparisons between interaction objects and display resulting outcomes in representations that highlight any distinctions that are pertinent to workers’ goals.
What comparisons do targeted knowledge workers frequently make in the work practices that your team is striving to mediate? What specialized information representations could allow workers to accomplish valuable comparisons by quickly interpreting emphasized distinctions between selected interaction objects?
I have to quickly ﬁll this order...
Examples from three knowledge work domains: A financial trader chooses an option in his trading application to compare all available offers for a particular security. A special visualization highlights the differences between six offers that are currently available, visually emphasizing the most important characteristics and the magnitude of their discrepancies (see illustration). A scientist selects two categories of clinical data in her analysis application so that she can view a summary of differences between them. The application presents her with a visualization that graphically illustrates key distinctions in the data across several variables. An architect uses a feature in her building modeling application to compare two saved versions of a particular floor plan in a hospital proposal. The resulting view is a composite that assigns each version a color and removes all features that are precisely shared. Only the differences remain salient, in bright colors that call out which version of the model is the source of each discrepancy. Knowledge workers often make comparisons manually, without specialized representations for the task, by placing multiple printouts (J7), onscreen windows, or other artifacts within their visual field and scanning pertinent features (B1, G5). In some cases, individuals and organizations may define standard information displays that crystallize and bound certain comparative tasks (F2). Interactive applications can excel at automating comparisons (E3, E4) and displaying resulting outputs in representational formats that call out meaningful distinctions in informative ways (A). To envision displays that make comparative conclusions clear (C4, G1, F10), product teams can explore concepts for adapting established representations already used within targeted work practices. Teams can also ideate around workers’ concrete comparison needs in order to generate concepts for more novel representations (F3, K6). Depending on the bases of comparison (B6) and how standard individuals’ decision making criteria are (A4, A8, C8, F6), effective comparative representations may be categorically different from how the objects under comparison are typically displayed (F8). When product teams do not actively consider the potential role of comparative representations in their application concepts, opportunities to improve certain types of decision making and reduce or eliminate tedious, repetitive operations can be lost. People may find the exacting nature of manually comparing application content to be excessively effortful (D2, D3, K2) and error prone (C9, G3), increasing their short term memory burdens (E2) and reducing time spent on their higher order goals. See also: B3, E, F, G6, I, J6, K4, K5, L
More specific questions for product teams to consider while envisioning applications for knowledge work: What types of information artifacts do targeted individuals frequently compare?
What are some common bases of comparison? Which can be especially important in targeted operations, tasks, and larger activities? Which comparisons are currently accomplished manually, by workers’ placing multiple information representations in their visual fields, switching back and forth between screens, or other ad hoc methods?
The search results show that we have four diﬀerent sources for the security that I need... All four seem rela�vely similar, so I’m going to use the comparison view...
What comparative representations do workers currently use in their established practices? What value do these formats provide? What memory efforts and cognitive load are involved in particular types of comparisons? Are these acts relatively easy to accomplish, or do they present burdens that could be valuably reduced by your team’s product? Where might automated comparisons of application content provide valuable new support for analytical judgments and explorative sense making in targeted work practices? What larger design and technology trends could influence your team’s ideas about how information in your application concepts could be comparatively displayed?
I love the way this screen calls out diﬀerences in the info that I care about, including some more complex analyi�cs... And I’m removing sources that don’t look right...
So, it looks like it’s a toss up between the ﬁrst two... And the tool has put them ﬁrst because its rules generally know what I look for when making these decisions...
What improvements and extensions might you envision for existing comparative representations as part of incorporating them into your application concepts? What novel comparative displays might your team sketch, based on your understanding of workers’ goals and current practices? How could your computing tool introduce and frame the value of novel comparative representations? What instruction and initial scaffolding might be useful while individuals are learning to use these new displays? 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?
Published on Jan 13, 2010
Published on Jan 13, 2010
Working through Screens: 100 Ideas for Envisioning Powerful, Engaging, and Productive User Experiences in Knowledge Work This heavily illus...