The design of a financial system interface is factor that enables but also limits the productivity of everyone who uses it. In didi’s quarter century of experience in financial technology, we’ve noticed that the majority of financial systems are designed without adequately addressing the most important aspects of business workflow: the subtle steps in the thinking process an expert develops throughout his or her career. As a result virtually every revenue-producing role on Wall Street is hobbled by the systems meant to support it.
Interface Design is all but ignored in financial systems. It’s commonly expected that a functional specification will capture all necessary workflow issues, and that design is at best a cosmetic polishing that might be useful for client-facing applications but adds no value to internal systems. There is nothing farther from the truth. It’s our experience that virtually every work process on Wall St. can be made significantly more effective.
Properly practiced, design is not just fashion or branding but an optimization process whose objective is to connect the information in the computer with business tasks in a deep and effortless way. Seen as an optimization process, it’s clear that we can focus on the working parts of the information transfer between computer and financial expert. But the skills needed to understand those working parts are not taught in business schools or computer science curricula.1 In a typical development cycle, a business analyst is asked to interview traders (for instance) to develop a list of use cases, a dictionary of the data needed to support them, then write this information up for a development team to code. This is an important step in defining what the system must do—but it does not capture how the traders work at a fine enough level of granularity to facilitate the real business processes: what really goes on in their minds.
To optimize a system’s interface we need to dig deeply inside the thought processes that are the essence of each business task. We need to support every sub-second cognitive step with data (or input opportunities) in exactly the right form to fit how it is being thought about at that moment. It also needs to fit all the other ideas that are part of that task. Traders themselves do not have access to how those processes work any more than a grown adult can describe in words how to tie a shoe or ride a bike. The processes have become “automatized,” so they don’t come out in interviews.
Engineering is applied science, and presumes an almost cookbook-like methodology to apply to problems, at least as a starting point. At didi we directly apply science and have developed such a methodology. The results are as remarkable as one might expect where no engineering has been applied before. Applying engineering practices from the wrong domain (e.g. Computer Science) can sometimes be worse than no engineering at all: human minds do not operate like computers.
The sciences we apply range from Visual Perception and Cognitive Science through Psycholinguistics.2 The cookbook-like methodology creates a working process that reveals to all participants exactly what progress is being made, and how obvious its absence was in retrospect.
An introduction to this methodology takes a 14-week college class (or a three-day intensive seminar at a financial firm), but some of its key underpinnings and findings can be hinted at here.
First, a thorough understanding of every element in a business role is compiled, including:
This exhaustive dictionary of things/processes/issues is then partitioned—not following database idiosyncrasies or within-firm silos of practice—but following business practices and needs. Thus a single screen might need data feeds from four or five different databases or even different business groups to accomplish a specific task. Don’t send the expert to five screens: bring the data to one.
There are techniques to turn this partitioned dictionary into candidate designs, e.g.:
How many financial screens exhibit the simple mapping that comes out of step 4: that the most important business issue is the most visually obvious thing on the screen? How many screens are explicitly tailored to ease the mind’s task-switching costs as an expert goes from one to another, as addressed in step 5? Standard UI guidelines address none of these issues.
Literally hundreds of techniques exist to tie on-screen visuals to mental processes. Perhaps the strongest value comes from the fact that screens designed to reflect the decades-honed best processes of the experts actually guide every new user to think like your most productive people. The benefits are concrete and create significant value in many dimensions; including productivity gains, lower training costs, risk reduction, and lower support/maintenance costs. Most important it results in improved morale and creativity in your best people because the system finally lets them think not as data entry experts but as the business experts they signed up to become.
1 Except Columbia University’s Department of Computer Science, where didi principal W. Bradford Paley was asked to teach the didi design methodology in graduate seminars.
2 See the “paper lecture” Interface and Mind, available from didi, for more details about how these sciences from the basis of cognitive engineering.
3 See the keynote talk-related notes MoMA Desktop/Data Rain: InfoVis as Design in an Art Museum, also available from didi.