Though it wasn’t his job, Matt Roher spent much of his time doing data entry. More important work — the work he should have given his full concentration — was neglected as a result.
Roher is a category manager at Rust-Oleum Canada
in Toronto, which recently decided to implement a business intelligence solution from Hyperion in order to modernize its paper-based sales tracking system. With the BI tool, the amount of time Roher spends doing data entry has been virtually eliminated, he said, leaving him free to plan sales strategies.
Rust-Oleum provides rust-protective paints and other coatings which are sold through third-party retailers, such as hardware stores. In order to create and analyze sales reports in Excel, it had to manually enter the paper-based sales figures sent by stores into its own systems. Data would be sent to Rust-Oleum by retailers in thick bundles of dot matrix printouts. The process was onerous and left little time for analyzing, or acting on, the results, Roher said.
“The data entry staff was me, and I’m not in a data entry role.”
Roher was spending two weeks a month on data entry. Other projects that should have been pursued were put aside. Also, while the data was being entered, errors inevitably occurred.
The tool, Hyperion Performance Suite, has dramatically changed Roher’s job and the company’s bottom line, he said.
“We now know if our business is up or down and can spend time analyzing data and trends and have time to act on them,” he said. “Before, a lot of time was spent on entry, and by the time it was done, we’d get new data.”
Now, retailers send their point-of-sale data straight to Rust-Oleum’s U.S.-based headquarters in Vernon Hills, Ill., which is already using Hyperion. The data can be sent in various electronic formats, such as Excel spreadsheets, or comma- or tab-delimited files.
At headquarters, it is added to the company’s SQL database, and now Roher can create reports within minutes.
More importantly, he now has time to analyze and act on those reports. Now, if a product is flying off the shelf at a certain store, it becomes readily apparent. Roher can drill down into the data or contact the store to find out what they’re doing. Alternatively, if a store is experiencing poor sales, Roher can investigate. Or, if a store is experiencing solid sales, but it appears to be making less revenue than other stores, he can inform the store that they can sell the product at a higher price in order to increase their revenue.
“If we can go to a store and say, you have room to increase sales doing X, Y and Z, they respond to it.”
Business intelligence tools are no longer solely the domain of business analysts, said Eric Rogge, a vice-president and research director at Ventana Research in San Mateo, Calif.
BI tools are increasingly being used by front-line workers making day-to-day decisions, he said.
“It’s this operational deployment which is driving demand” for BI tools, he said.
While business analysts used in-depth and complex analysis to analyze prospective initiatives on large project, operational BI users do simple and repetitive actions with the tools. They use them for everything from sales analysis to deciding which customer service representative to send out on a call.
As a result, they need much simpler versions of BI tools that hide some of the more complex tasks business analysts need, Rogge said.
They also need access to a much narrower scope of information so they aren’t overwhelmed by data that isn’t relevant to their task, he says. Trying to figure out which data is relevant to which worker is key, he said.
IT has to highly-focus the information it makes available to operational BI users, Rogge said. Operational users also need simpler interfaces, he added.
“It has to be brain-dead simple.”
He recommended companies deploying operational business intelligence avoid drag-and-drop interfaces.
It’s easy to create queries with such interfaces that may make sense syntactically but may be nonsensical semantically from a business perspective, Rogge said.