Gotcha! Collaborative Sales ForecastingBy Sean Gallagher | Posted 2003-11-01 Email Print
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How can you forecast sales if you can't collaborate?Background: New Balance felt a burn in its purse strings, not its hamstrings, when it tried to collect demand forecasts from its 120-member sales force. Forecasts were hard to fill out. Few forms were turned in. Telephone connections discouraged users from even trying. Predictions of sales from the field were supplanted by the best guesses of executives at headquarters of what should get made and could get sold.
Problem: Trying to use the wrong tools. New Balance had forecasting and business-intelligence tools, but they required online access to large amounts of data in order to be completed. The sales force was on the go and its members were disconnected most of the time. So, the reps ended up manually punching numbers from printouts of reports out into Excel spreadsheets on their hard drives or entering unsupported estimates.
Resolution: Sales planning manager Teresa Holland brought in SRC Software, of Portland, Ore., because it provides "distributable workbooks," compressed data files that can be pulled up and viewed through Microsoft Excel spreadsheets. The files can act as a personalized data warehouse, allowing sales reps to analyze information from New Balance's enterprise-planning system without having to be connected.
Problem: The lack of access to real data made collaborating with retailers to create forecasts on a style-by-style level difficult, if not pointless. And putting data into Excel sheets by hand led to errors when sales reps typed in the wrong numbers for shoe styles. They also often changed the formatting of the spreadsheets. Those two problems meant long hours of proofing data back at headquarters if the information was to be used at all.
Resolution: SRC's approach to workbook files meant Holland could lock down the format of how data could be submitted. That meant a sales representative could only enter data in the manner that New Balance's demand-forecasting and manufacturing-planning systems could recognize it.
Problem: Information on expected orders had to be rolled up by hand, retyped manually from each individual forecast into a single consolidated one. Linking spreadsheets together to build an aggregate view was unreliable, and the size of the data sets in Excel often caused Holland's system to crash while she was trying to pull the data together for analysis.
Resolution: Because all data is in a preset format, a consolidated sales-forecasting sheet can automatically roll up individual forecasts. Holland now just has to "click a button" to order the aggregation.
Problem: Sending data to sales reps caused the network to slow to a crawl. At the end of each month, New Balance would send 10 to 15 megabytes of sales data to each of its 120 salespeople in e-mail attachments. The transmissions exceeded both available bandwidth and mail-storage capacity. Representatives found downloads could take more than an hour over dial-up connections. That prevented them from sending in orders or getting mail from customers and managers.
Resolution: A Web-based check-out and check-in system. Sales reps now upload and download files, when they can. Since sales reps check-in and check out files on their own schedules, there's no spike in network traffic. No longer are all reps sent files at the same time.