100 APPLICATION ENVISIONING IDEAS | E. PROVIDING OPPORTUNITIES TO OFFLOAD EFFORT
WORKING THROUGH SCREENS
E4. Automation of Task or Activity Scenarios In certain situations, entire tasks or larger activities in knowledge work can become extremely routine, describable, and tedious. In response to these cases, product teams can envision concepts for targeted automation functionality, which can change the nature of work by allowing individuals to focus more of their efforts on less routine and higher value efforts. Examples from three knowledge work domains: A scientist designs a workflow in her lab’s information management application. In this workflow, lab technicians will feed prepared samples into laboratory robotics, which will automatically gather experimental data. Her lab’s computers will then automatically perform a number of algorithmic transformations on the data before storing the results in a repository where she can then analyze it graphically (see illustration). An architect enters parameters for the beginning and ending of a curved shape in her building modeling application. The computing tool extrapolates the entire surface of the form, including some of its engineering and construction details, based upon a set of customized functional rules and defined material properties. A financial trader books a transaction in his trading application and then immediately focuses his attention on his next potential deal. Behind the scenes, a whole series of crucial small tasks are automatically processed across a number of systems to make the completed transaction a reality. Historically, automation was an early focus in the application of computing to many workplaces. Today’s product teams developing knowledge work tools may find that valuable opportunities for extensive automation of existing work practices (A) are not especially prevalent in the markets that they target. In certain cases, however, customizable (C8) automation of tasks or larger activities can provide transformative value in the context of workers’ status quo practices (A9) and overarching organizational goals. When product teams do not actively consider how larger units of work practice might be usefully automated, opportunities to reduce or eliminate unwanted effort (D2, D3), prevent certain types of errors (C9, G3), and drive precise, high quality outputs (A4) can be lost. Adopting highly “manual” applications may lead to people spending the same amount of time, or even more time, on less desirable, “lower level” work and user experiences. These “lower level” actions are often accomplished at the expense of other tasks that may better contribute to workers’ desired outputs (L1) and larger goals (A5). Conversely, when misapplied, larger scale automations can erode individuals’ sense of control (E6) and drive corrections and workarounds that may require more effort than doing work without automated support (D4). Workers may place a high value on how they currently accomplish the tasks and larger activities that product teams perceive as prime candidates for automated offerings (A4, C6, E5). Even in cases where people desire larger scale automations, targeted work practices may contain prohibitive requirements for flexibility (A6, A7, A8). See also: C10, D, E, F6, I, K4, K10, M
A�er my lab technicians prepare samples and put them in certain instruments, our lab’s automa�on can do a remarkable amount on its own, with human eyes only on errors and excep�ons...
LAB AUTOMATION CONTROLLED BY COMPUTING APPLICATIONS Automated data collec�on
Automated data ﬁltering Automated movement of data in study repository Automated calcula�on of resultant values in study
Automated tes�ng against previously coded hypotheses Automated messaging about data availability
And at the end of the automa�on pipeline, if all goes well, I receive accurate new data from the experiments I deﬁned long before any of the lab work was even started...
Is your team targeting any tasks or larger activities that have highly predictable and standard series of operations? What functionality concepts might you envision to automate these sequences? What could be gained or lost, from the perspectives of targeted knowledge workers and their organizations, in the adoption of such expansive automations? More specific questions for product teams to consider while envisioning applications for knowledge work: Which of the work practices that your team is striving to mediate could be rationalized to the extent where automation may be a feasible option? What tasks or larger activities, in practice, present “too much” variability for such functionality to be effectively defined and used? Which work processes do targeted knowledge workers find tedious and time consuming? How do these routine processes currently distract from more meaningful and higher order pursuits? What established processes do workers value in their current form, without automation? Why? Which processes in your sketched application concepts might be usefully automated under the general goal of reducing users’ efforts? What value could targeted organizations gain from extensive automations in the context of their larger goals and overlapping activities? How might automated processes impact targeted workers’ desired sense of meaningful visibility, direct control, and self determining agency? What larger design and technology trends could influence your team’s ideas about substantial automations in your computing tool? How might the strengths of computing be applied to valuable and appropriate automation scenarios in your product’s scope? How could larger scale automations reduce the incidence of certain errors or improve the quality of certain work outputs? What other benefits could result? What might the user experiences of providing inputs and receiving outputs be like in your sketched functionality concepts? Will workers need to actively monitor your team’s envisioned automations? What alerts and cues could guide their observations and awarenesses? What interaction methods could allow users to locate and override the effects of specific automated steps? How might individuals recognize and recover from certain cases of problematic automation? What settings and customization functionalities could help ensure that automated processes will operate in accordance with the goals of targeted individuals and organizations? 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
Working through Screens: 100 Ideas for Envisioning Powerful, Engaging, and Productive User Experiences in Knowledge Work This heavily illus...