By Victoria Nneji
Dr. Brenda Dietrich is the Arthur and Helen Geoffrion Professor of Practice the School of Operations Research and Information Engineering (ORIE) at Cornell University. On Sunday morning, she presented the first plenary talk of the meeting on riding technology waves over the course of history. Her message began in the 1960s. During that period, there was an interest in back office computing as many managers identified this as an opportunity to reduce labor costs and human error. Over the next few decades, personal computing and client service brought about a new wave of opportunity. However, information systems were divided by departments and this created “islands of automation” in which each computer was not utilized for about 20 hours a day.
By 1995, Dr. Dietrich presented how the introduction of the World Wide Web introduced network science and enabled search. Over the next few years, social, mobile, and cloud computing led to an “always on” culture for computers as well as humans. Within the past three years, robotic process automation (RPA) has piqued the interest of managers. Through observation of humans at work, analysts may identify opportunities for engineers to design automation. We can see examples of RPA in customer self-service and call centers.
With each of these waves, Dr. Dietrich highlighted that operations research may have missed the ride, but the field is primed to take the lead on whatever wave comes next. A key to this is presenting our work in a way that shows its marketability and profitability. And along with working on signals of value, preserving user privacy at each stage of development and operations is key.
Overall, today’s session by Dr. Dietrich was relatable. She discussed real-life problems that she faces (for example, sending her college-aged daughter just enough money to be helpful). She taught us that our work should try to solve such problems that may seem meaningless from a distance but are meaningful to affected users. Whatever our solution, Dietrich pointed out that the first phase of any trend is to take out costs. We can take this a step further by working with the data left behind to develop data-driven insights at the point of user decision making.