NTX Magazine Volume 4 - Page 72

INDUSTRY SPOTLIGHTS Logistics There it is in black and white. Right? One local professor says: “Maybe not.” The University of Texas at Arlington (UTA) is ramping up new technology this year to help with the critical decisionmaking, research that will help businesses make better decisions all along the supply chain. Dr. Kay-Yut Chen, professor in the Information Systems and Operations Management Department at UTA, is a renowned behavioral and experimental researcher who will merge the classroom with the boardroom, showing how scientific analytics can be used at every level, from entry to executive, and improve decision-making within a firm. “I always focus on the theme of human behavior. It has transformed it all, from how you run a supply chain from the tip of your finger -- but then you cannot get away from human information and human decisions. You want a computer at one point and, at another, you want human judgment. The key is understanding what a computer can do and what human behavior will do and where you need to rely on both.” Chen explains that any major company will have a wealth of data. However, data is just data. If you have a lot of data then it’s more difficult to make a decision. Using statistical and scientific methods to understand what that data says is very important. You have to look at the whole chain and understand the system of supply chain, how components flow like a network. In some networks, computers are very good at handling a component, like freight, or selling, where computers can look at historical data and provide the information needed to produce the right amount. However, with new designs 70 www.ntc-dfw.org Dr. Kay-Yut Chen. and business-to-business decisions, historical judgment cannot always be relied on. Utilizing behavior operation, which includes human decision and knowledge in every component, is important. The key is quantification – the measurement of data and human data, by measuring the whole ray of learning and treating the whole system, you can meet it and measure it enough. Chen also notes that there is a “sweet spot” in regard to human purchasing behavior. What do people want to buy? How many do you want to make? How much do people value each of the features of