Having an underlying technology platform that is scalable and provides easy access to valuable business data is critical for finance. Schwenderman highlighted cloud, in-memory, and components of big data as important areas for finance teams to begin their digital journeys, and said now is the time to set that foundation.
“It’s very hard to enable machine learning capabilities, cognitive capabilities, or block chain without having a strategy around that type of architecture,” he said.
Schwenderman said in-memory technology and big data approaches can process information significantly faster than traditional database structures, resulting in much richer data sets. He gave an example of the ability to drill down and analyze profitability by individual products, and then by region.
“Doing that today in a traditional environment of relational databases could take somebody several days. In an in-memory environment, I can run through multiple scenarios in a couple of hours,” said Schwenderman.
Another benefit of in-memory data is the ability to capture transactions in real-time and develop a current view into business performance.
“The ability to look at cash flow position or orders versus inventory position in near real time is pretty important for someone who is trying to figure out an effective use and distribution of resources,” said Schwenderman. “By bringing different types of data sets together and being able to process them at a faster speed, we can really look at information that adds better context to business decisions, [all] when you are trying to evolve to being a business partner and away from a steward and operator.”