Case in Point: Forecast: High Visibility
GIW Industries manufactures slurry pumps for use in applications for mining, dredging, and similar industries. The company is content with its legacy, custom-built AS/400 transactional accounting system, but it has realized big benefits by upgrading its revenue forecasting capabilities.
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BPM Magazine: When did you purchase your current forecasting system, and why?
Linda Clover: Our primary system for sales forecasting is Systems Union's Alea. We bought it five years ago because our parent company uses it. We wanted better sales forecasts, and this was the obvious choice.
BPM: How does the forecasting process work?
Clover: It's a collaborative process. The sales team and executives give input on their expectations for sales of "sporadic use" parts. The field sales managers provide information about this demand down to the part number, which they know because they collaborate with their customers. The customers buying this equipment will often want to put it in place during a maintenance shutdown, so in most cases they know in advance when they're going to want the parts.
For new equipment sales or the reopening of a production line, we typically know even further in advance. New mine operations can be in feasibility, planning, and budgeting stages for several years. GIW will work with the customer during all of those stages to determine the best product solution for the application. Depending on the viability of the project and the time horizon, some of this data is also included in the forecast.
BPM: What role does your software play in this process?
Clover: I consolidate the forecasts in Alea. We include historical information on parts in our Alea cubes. We break down the information into different dimensions, including actuals, forecasts, and budget data by product, market, geography, type of data, and time dimensions, all the way down to the part-number level. Having the ability to drill down into all this information helps with authentication. For example, suppose a customer wants four of a certain kind of pump part and this looks unusual to us. We might do a more in-depth review of the historical data for this customer. With Alea, we have a lot of flexibility to do this kind of review and comparison and then update the forecast into the cube, without going from one system to another.
The other big benefit of this type of analysis is that it greatly enhances our statistical forecasting for products that are not "sporadic use." Some smaller parts that we sell have more predictable sales patterns, and we are just starting to use Forecast X from John Galt Solutions to predict sales of these products. But we're constantly trying to improve the performance of our forecasting models, and by drilling down into the data in Alea and seeing how our forecasts really performed, we've been able to dramatically improve our forecasting techniques. In our legacy system, these types of things would require lots of programming resources.
BPM: So, what would you say to another company that uses spreadsheets to try to manage its sales forecasts?
Clover: The greatest benefit Alea has given us is the ability to view our data. If we had not invested in Alea, our forecasts of one-off sales would not be nearly as accurate, and our statistical forecasting models would not be as robust. There's just no way a spreadsheet can give you the same insight into your data that a purpose-built forecasting tool will give you.
