Today’s finance leaders are facing difficult choices when it comes to optimizing their companies’ technology stack. On the one hand, they need to ensure they are prepared for the dawn of new technologies such as generative artificial intelligence, but on the other, they are facing increasing pressure to do more with less.
CFOs want to be able to leverage their companies’ data, and they want to do so “at the best possible price and performance ratio,” said Joerg Tewes, CEO of analytics database provider Exasol.
“As a CFO, obviously, you're looking to avoid having to make compromises,” he said in an interview. “And there are different requirements that companies have. There's performance scalability that you need.”
Shining a fresh spotlight on data
A veteran of the technology and software space, Tewes took the top executive seat at the data analytics company in January. Prior to joining the Nürnberg, Germany-based company, his past roles included time spent at Amazon serving as head of product management for its Fire tablets and Kindle e-readers, among other positions at the e-commerce giant according to his LinkedIn profile. He also served as CEO for augmented reality technology firm Avegant for just over three years, and has also logged time at software and computer manufacturer Logitech.
To ensure they can find that key balance between price and performance, companies need to make sure they are not only focused on data, but have the tools in place to effectively access it. Most companies today already put a “strong emphasis” on data, having started focusing on data analytics at least a decade ago, Tewes said.
However, many companies are also still dependent on the technology or the systems they started out with over 10 years ago — and the volume of data now streaming into businesses is outpacing what these legacy databases can handle.
There comes a point in time when one’s current system is no longer effectively serving the needs of the business, Tewes said — with queries that used to take seconds now taking minutes or hours, and with the system overloaded with more users and information.
“Then enterprises need to make decisions: ‘What do I do?’” he said. “Do I go and basically rip and replace my existing system that I have? Or can I make my system more scalable?”
Keep your eye on long-term costs
Deciding on which tools or software to implement when looking to scale your system is not a simple, either-or decision for finance leaders, however.
As the financial leaders of their organizations, CFOs are typically stuck having to balance a need for greater data capacity with its corresponding jump in costs — something that needs to be carefully considered, especially in the present macroeconomic environment. CFOs need to not only ask their teams about the potential use cases of new technologies, but for “a projection on what the cost of that technology is going to be down the road,” Tewes said.
“I think from a CFO perspective, you really have to ask the question, what is the mid-to-long term cost?” Tewes said of implementing technologies like generative AI. “When I start deploying these technologies, understand that data volume will explode down the road. More and more data gets generated, and then you will have to manage to deal with that data somehow.”
It’s also important to align key members of the leadership team such as the CFO, CIO and CEO on the importance of data-driven decision making when it comes to tools like generative AI. Looking ahead to how they expect one’s data volume to grow over the next three to five years is crucial for finance leaders here, he said.
“My advice for any decision maker in that space is try to think ahead, look at the data volume that you expect because…data volume just keeps on growing and growing and growing,” he said. “And you need a system and an architecture that actually scales with what you're planning to do, what you need to do in the next three to five years.”