hey are. We can identify their location within the system, that is, the cell (or cells) that is serving each subscriber's user terminal. However, at least until recently, we have not identified the exact physical location of each subscriber over the length of each call. Yet, to design and grow good service, we need to know where our customers are. We once again turn to statistical modeling, applying a combination of common sense and knowl- edge of our market to picture what is happening and what is likely to happen. 48.1 Traffic Tally Calculations One reason for adding subscribers to our network model is to ensure that we have enough capacity for current use and to meet our growth forecasts. We do this by enter- ing the peak demand we have (or expect) to our model. We should remember that peak- demand times differ for different locations (such as commuter routes, offices, and shop- ping malls). We can vary the expected growth of demand based on forecasting from different marketing plans, coordinating cellular growth (described in Chaps. 31 and 45) with our simulations. We also can run the models with average or aggregate usage data to calculate the financial return on the investment in growth in specific parts of our network. We can work to answer such questions as Which of several buildouts will generate the most return on investment? What do we need to do to create hot spots to serve localized demand for wireless data? What will it cost to build an indoor picocell for a customer who wants a bid on providing that service? As we integrate subscribers into the model of our cellular network, we become able to address both business and engineering questions more completely. Once we have an adequate picture of radio propagation, we can move from there to subscriber traffic modeling. It is not enough to identify geographic areas of poor radio conditions, we also must identify congested areas so that we can plan for system growth. We also want to use the traffic data to decide which areas of radio problems to Downloade