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Design Day Adjustment To adjust the study data to design-day levels, the annual transaction data provided by Contractors' Warehouse (for the calendar year 2004) were analyzed to determine the design day adjustment factors needed for each store. As discussed previously, the design-day level chosen for this study was the 5`I' busiest sales day of the year. To determine the appropriate adjustment factor for each store, the daily transaction total from the 5'h busiest day of the year according to the Contractors' Warehouse data was divided by the daily transactions total that occurred during the study day. The calculations for determining the design-day adjustment factor for the Pomona store are shown below: Daily Transactions on Design Day =Adjustment Factor Daily Transactions on Study Day Example: 5`h busiest day in 2004 had 832 transactions Study day had 753 transactions 832 = 753 = 1.105 Study day experienced a peak parking demand of 99 spaces. Estimated design-day peak parking demand = 99 x 1.105 = 109 spaces Conducting the study in October appears to have been successful because the Montebello store had more transactions on the study day than even the busiest day in 2004. Without having the transaction totals for 2005, it was therefore assumed that the study day was the busiest day of 2005. Therefore, the peak parking demand for the Montebello store was factored down to represent the 5`h busiest day. Table 5 shows the peak parking demand observed on the study days as well as the peak parking demand calculated for the design day (the 5`h busiest day of the year) and for the busiest day. As shown in the table, the calculated design-day peak parking demand is higher than that observed on the study day for both stores. Based on the daily transaction total of the study day, the peak parking demand calculated for the 5`h busiest day includes 11 more occupied spaces than during the study day at the Pomona store. Since the Montebello store ha~pened to be studied on the assumed equivalent of the busiest day of the year for that store, its 5` busiest day peak parking demand is 9 spaces fewer than that observed on the study day. Also shown in the table, none of the design-day peak parking demands exceeded the capacities of the store parking lots, and neither do the busiest- daypeak parking demands. In fact, both stores have about 30 or 50 more parking spaces than would be needed on the 5`h busiest day. Table 5 -Peak Parkin Demand on Stud Da , Desi n Da and Busiest Da Parkin g Peak Peak Parking Peak Parking Excess Parking Store Total Capacity Parking Demand Demand Capacity' # Store Name Parking Available Demand Calculated Calculated based on Capacity on Study Observed for for the 5'" and t°' Day on Study Design Day '" Busiest Day Busiest Da Da 5 Busiest y 703 MONTEBELLO 113 113 88 79 88 34 25 705 POMONA 185 163 99 109 116 54 47 arxing capaclry avanaole on study day menus the peak parking demand for the 5`" or 15` Busiest Days Parking Study of Two Contractors Warehouse Stores - Fina! Report Page 10 n-I a 31 A-36