Isabel was a popular name in last week’s news reports—and no, she’s not the latest hurricane to whip up in the Atlantic and come hurtling toward the coast. This Isabel is instead a software system that falls under the broader category of a Decision Support System or DSS. Isabel allows doctors to click through medical knowledge related to a possible diagnosis. According to a 2003 Journal of the American Medical Association review of autopsy studies, doctors are increasingly using programs like Isabel to assist in patient diagnosis and to reduce errors.

In general, decision support systems are often characterized as tools and mechanisms (increasingly packaged software driven) that help decision-makers, such as managers, compile useful information from raw data, develop business models, compare results and solutions and ultimately solve problems and make decisions. However, appealing as these capabilities might immediately seem, much of their popularity in industry may be attributed to something slightly less appealing or the so-called “silver bullet” addictions among key managers – a voracious appetite for quick and concrete solutions that nevertheless permits marginal managerial effort and true understanding.

“What I see is a continued demand for ways to make decisions faster in a world where information is becoming more and more available – the result is not always ideal,” notes Elliot Bendoly, associate professor of decision and information analysis at Emory University’s Goizueta Business School who regularly researches the interface between operations technology and the role of people and behavior. “Many at the top ranks believe that managers below them should be able to come up with good solutions faster because supposedly it appears that the competition may be able to leverage DSS, if they aren’t already, to do exactly that.  It’s the same reason many firms continue to collect and store large reservoirs of data that they never ultimately use.”

According to Bendoly, the silver-bullet mindsets are particularly destructive for a number of reasons. System-driven solutions both reduce the amount of time individuals feel they need to allocate to decision processes and provide potential whipping posts when solutions in practice don’t work out. “Some decisions fundamentally don’t have to be made quickly because they have long-term implications and should be given enough time to be well-considered,” explains Bendoly. “Also, managers say, ‘I’m being proactive and I’m buying a system to help with the decision making.’ They then remove themselves yet more from the decision-making process by delegating the use of those systems to others below them. In the event that the suggestions developed by the system do not yield the kind of results that mangers are expected to provide to their higher-ups, they can always go back and say it was the system, the users, or the IT staff who didn’t put it in place the right way. In the process of delegating responsibility and they are also distancing themselves from blame.  Many managers are very much aware of this unfortunately and in fact capitalize on it.”

But the problems aren’t just with managers as often blind champions of DSS.  There’s a supply-side issue here as well. What role do suppliers play in developing systems that take into account how managers will use them? Bendoly and coauthor Cheri Speier of Eli Broad College of Business at Michigan State University, explore these and other related issues in their paper, “Silver Bullet Junkies and the Codifiers that Love Them.” The paper will be published next year in Decision Sciences as the lead article in a special forum that addresses how human issues relate to decision support technologies for operations managers.

Bendoly suggests that suppliers—the increasingly prevalent developers of DSS software—should look beyond the lure of immediate monetary gains inherent in flooding the market with technology that, while often not appropriately accounting for issues in the most meaningful and relevant way for specific end users, is still readily adopted. What is needed is ethical responsibility in design. “The right approach is to think about how the system will be used, not just whether the system does what you think it should be doing as a developer,” says Bendoly. “It behooves developers to develop systems that are going to be transparent, in terms of how they work and their limitations and that take into account the role of individual behavior. This is not just an ethical issue for developers, this is a sustainability issue. They’ve got to learn to be conscious about the individual, for ethical reasons and if they want to be successful. At some point the accountability for these kinds of issues is going to be there and they have to be ready for it.”

So how to get at these improvements in an already thriving DSS market? Changes, urges Bendoly, begin at the level of student and educator. They must begin thinking and learning in a more ethically responsible way. Structured approaches can reduce the lure of silver bullets and irresponsible use, write the authors, but they need to be engaged, studied and promoted. The role of academia in this process should not be underestimated. “Much that is taught out there on systems development is not done this way,” notes Bendoly. “Often academic models are feeding into this huge supply of developers who know how to put complex optimization and simulation packages together, but are not accounting for the human element and nevertheless are very successful in selling their products because there is demand out there for it and a scapegoating mechanism that allows for demand to exist. The missing behavioral element in many schools that teach operations is that this is just something they are not interested in. They have no interest in reaching out to the people who study human resources. The most problematic result is not in what they publish, but in how they teach their students that it’s fine to work this way and you don’t need to think about ethics whatsoever to be able to crank out tools.”

Academia has the ability to change things for the better. “Hopefully what we’re doing here at Emory is paying more attention to the individual, the decision maker who is under pressure to buy these systems and to ostensibly scapegoat,” explains Bendoly. Consideration of these elements of human behavior as well as the question of ethics in operations, both key contributions that “Silver Bullet Junkies and the Codifiers that Love Them” makes to the existing literature, are only just beginning to emerge, he adds. “My hope is that this research will make people think more about what they’re researching and what they’re teaching.”

Stay tuned for more Bendoly-generated analysis on how operational policy affects ethical behavior and how ethical behavior in turn affects the performance of operations policy.