Case Study: Cincinnati Zoo

1.) What people, organization, and technology factors were behind Cincinnati Zoo losing opportunities to increase revenue?

The people factor behind Cincinnati Zoo losing opportunities to increase revenue was the poor management. When the senior management reviewed the operations of the zoo, they found that the managers did not had a knowledge of the business processes happening in the zoo on a day-to-day basis. This lack of knowledge prevented them from getting to know their customers. The organization factor was the outdated business processes. Cincinnati Zoo food business service had manual cash registers. Managers had to go through every receipts to know daily sales total. With this outdated business processes, the zoo had to hire part-

There were association, classification, ad sequence types of information observed from the data mining that helped the zoo better understand visitor behavior. The Cincinnati Zoo observed associations linked to weather. They noticed that on rainy days the numbers of visitors falls drastically, and on hot days the sales of bottle water and ice cream rise. Linking the weather forecast to the business intelligence system, the Zoo’s management can make better decisions regarding employees’ schedules and inventory needs. With the information obtained from data mining the Zoo’s management was able to classify their visitors market. They found one customer segment which consisted of people whom only purchased entrance tickets and nothing else. Management decided to implement a direct mail marketing campaign to those who classified in this category and send coupons of Zoo’s restaurants and gift shops. The Zoo’s decision of changing their marketing strategy into a more targeted marketing saved the zoo $400,000 from its annual budget. The last information observed was a sequence of people buying more ice cream during the last hour before the Zoo closes. So management decided to open the ice cream outlets the entire

The managers now had access to real time information. This made it easier and faster for them to find trends and develop a strategy to adapt to those trends. For example, when managers observed that food sales decreased drastically after 3PM each day, they decided to close some of the food outlets at that time. Decisions like this ones increase the operational performance of the