James Redfern, CFO at Reltio, has seen a radical change in the B2B software market since joining Accenture as a strategic consultant in the late 1990s. Having spent 10 years as executive director of Morgan Stanley's Technology Investment Bank, he has a keen eye on the details of his SaaS business model and the requirements of private capital providers when investing in the software business.
At Reltio, a data management and unified platform, Redfern's job is to guide SaaS companies through the arrival of AI, a fundamental market shift. Luckily, Reltio has adaptable capital and has $100 million banks from multiple fundraisers. It also operates above the break-even point of cash flow, says Redfern.
In a Zoom interview, Redfern explained how AI experiments with product monetization, including how its SAAS business will adopt new revenue metrics, focusing on strategic finance, and how Reltio will move to an AI-first organization.
How did AI development affect the SaaS business?
Over the past few years, SaaS has been under much pressure. [corporate] The budget has shifted to what I call direct classic AI. Currently, what businesses are trying to implement is LLM and the core model. As businesses advance further along their journey, we are confident that they will recognize the same data challenges they have faced in the past with dirty data. AI models run on data that requires cleaning and play a role in the process.
You have shown that there are new revenue metrics specific to your SaaS business. What is it and why is it used?
Emerging metrics are called “experimental revenue.” The vendor works with customers to investigate whether what is being developed is useful to them without the need for a multi-year contract. In some cases, it's actual revenue. In some cases, “We [the customer] You will pay when you deliver this feature or this product. ” Companies are growing very rapidly, with some of these numbers increasing rapidly.
But that is unknown [these deals] It is as sticky and retainable as a multi-year SaaS contract. Startups need to bring in dollars, which increases their motivation to experiment with customers, prove their products, test their hypotheses, and ultimately lead to huge business. We'll see how it works.
Are companies moving from SaaS products for AI?
Rather than deviating from SaaS products, multiples are under pressure within the SaaS industry. I think one of Morgan Stanley's research analysts called it the SaaS recession three years ago. Expenses and growth were not in places that were pre-2022. IT budgets have shifted to experimental AI activities. In 2021 and 2022, SaaS multiples were out of hand, but 30-40% of companies also had a significant number. The number of SaaS companies currently growing at that rate [is much lower].
Let's talk about Reltio's finance department. What are you focusing on?
When I arrived I already had a very strong leader. I concentrate more time and energy on strategic finance. Some of it relates to budgeting. It's natural to think of budgeting as a one-year cycle. However, companies often do not link their budgeting process to corporate strategy through multi-year financial modeling. So I'm pushing hard in that direction. Ultimately, they think like an investor in terms of capital allocation, ensuring that the metrics are in sync with the company's long-term strategy.
Think of the concept of 40 rules, one of the traditional indicators of SaaS business. The 40 rules state that in combination with a certain level of profitability, a certain level of growth must be achieved. If the numbers aren't in the right place, where do you adjust them? If it's growing slowly, you'll need a larger margin. So we need to think not only about cost, but where we can grow, where we can and cannot. That's what I find most interesting and exciting about this role.
I think the company has an overall AI strategy.
I think AI works even faster than the Internet. It is destructive and has a huge impact. We implement extensive internal enablements where employees work as evangelists for using AI.
Additionally, internally, additional filters have been installed for employment. For each new hire or backfill, the hiring manager must complete a five-page survey. Did they check if [the job] Can it be run with AI or can it be refilled? Have they weighed and looked at employment alternatives? We're not trying to slow things down dramatically. We are just telling people that we are obsessed with thinking through how we use AI. We clearly consider ourselves an AI-first company.
Externally, we have a very large database of information that our customers need to integrate. Many of them have many people who do this match work [data] Between systems. We can build AI agents to help them and we market along with them.
Are you thinking about making it public? Have you built your infrastructure to do so?
My mantra on the team is that we want to be publicly prepared. This means you need to be typing quarterly numbers, working with good quarterly cadence and being clean audited. This does not include anything called “gory” seconds reporting activity.
Plus, we're not in that zone in terms of size, size and growth expectations for publishing. When you're big and things move a little faster, and when you're a simple story, being published is an absolutely great option. But I'm a huge private equity fan. I think operational discipline and controlled ownership are absolutely appropriate models, especially when it's in the transition. At certain stages of the company's lifecycle, it makes a lot of sense to be in one of them. And ultimately, the market decides the right answer to it.
