When Matt Tischler stepped into the CFO role at customer-favorite children’s clothing company RuffleButts, he came face-to-face with some significant challenges.
“They had a pretty solid foundation set up in that they had an ERP,” said Matt. But as is typical, when you start digging into reporting and generate some information, it leads to even more questions. The process of accurately answering those questions was extraordinarily time-consuming—and, of course, led to more questions that Matt wanted to answer.
“I was unable to just drill into data, which I knew was possible once the right infrastructure was set up,” he said.
How to sell a data warehouse solution to the board
While Matt navigated the existing tools at RuffleButts, he would hit walls when pulling information by a certain dimension. Previous analysis was good, but in a snapshot sort of way. Trying to pull trend analysis would cause overload because of the sheer volume of data.
He put in some nights and weekends working with exports out of the ERP into a free trial of a program that could pull together a clearer picture of the customer journey. It took hours and hours to build it; when he presented it to the board, they loved it.
They wanted more of it.
At which point Matt let them know, “If you want this more readily available all the time, we need to invest in a proper data solution because it’s just impossible to do it consistently without that.” Consistency is what drives the value of data in any business.
Transforming RuffleButts’ data insights practically overnight
With support of the board, Matt got to work.
“I needed to liberate the data, to get it out of the system,” Matt shared.
He explored two different pathways toward what they needed. One was developing an API solution to extract data; the other was a third-party solution that worked within the existing ERP architecture. For the small, lean, fast-growing RuffleButts, the latter solution proved to be the right one in terms of speed, maintenance, cost, and accurate insights.
And it wasn’t several quarters or even months before they had the implementation rolling and started seeing results. They had all their data loaded within a day, started transforming the second day, and published their first dashboard within a couple of weeks.
Yes, it was that fast.
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