Lauren Morton is a new leader with fresh perspectives. She’s got an engineering background and an MBA from Harvard Business School, all before consulting for Deloitte and transitioning into RevOps at Science Exchange.
Science Exchange is one of those rare creatures—a B2B marketplace—in the science space. It helps big pharma and biotech companies outsource scientific research, from human biospecimen studies to pre-clinical trial work. (If you’re in the market for a little miRNA expression profiling, I highly recommend them). As such, it’s steeped in scientific and data science rigor and must grapple with a high degree of regulation, and Lauren is right at home given her expertise in change management, data governance, and operations.
I sat down with Lauren to talk about the nature of success in RevOps and what makes a truly data-driven company tick.
This interview has been edited for brevity.
An Interview with Lauren Morton, Senior Director of RevOps at Science Exchange
Nick Bonfiglio: What do you wish you knew when you started in science tech?
Change management and execution are much more difficult than I had ever imagined. Now, there’s stringent regulation in this space for good reason—we want to ensure everything going to a patient is safe.
But as a side effect, there’s a high level of resistance to adopting new technologies and shifting ways of working within pharma and biotech companies. There’s a widespread feeling that change may have a regulatory impact so even with the best business case or product, people are hesitant to change.
As I’m building out our RevOps function, change management is a huge piece of it. It’s the most important soft skill—communicating effectively, reinforcement from the top and bottom, and consistently making the case to everyone you’re working with. Otherwise, we could have the best tool in the market, but if we’re not innovating and refining our internal processes, we’re not accelerating revenue. It’s a fun challenge but not an easy one.
What are the biggest challenges RevOps folks are facing right now?
It’s definitely scope creep. The nature of ‘operations’ is functional, so it’s too easy for a company to assign all things operations to the RevOps team. At Science Exchange, we are deliberate in having RevOps support operational needs for the revenue-generating team rather than be responsible for all things operations.
You have to constantly pressure-test the work you’re doing and question whether you’re spending your time in support of revenue. It’s a matter of protecting your time and capacity to do great work.
What are the hallmarks of a data-driven company?
Data-driven companies are building strategies and decision-making based on data at all levels of the organization. It’s a cultural mindset that an organization adopts and advocates for.
It starts with a high-level data framework—what are our company’s objectives? We have outcomes we want to achieve every quarter and every year—what data do we need to track and measure to meet our growth objectives? Then we execute—we need to build and train a team of people who are data-oriented. Otherwise, the mission falls flat and we can’t bring those insights to the forefront.
Managing data is not a skill reserved for people who have studied it. Data-driven company culture will encourage people to upskill, track, and report metrics in every function, and make decisions informed by good data. Companies that do all that are rare, but we’re always working towards it.
So, how do you balance data management and change management?
You have to start with a good foundation. Nailing your data governance and adherence to data capture is key. You can’t draw insights out of messy or inaccurate inputs.
But there’s always an opportunity for experimentation. I think if you want to try something that is not supported by the data yet, that’s good. As long as you have the data to set an objective, you can be creative with how you achieve your objective and then measure if it worked. Not all of the things you try have to be based on data, but you have to measure what’s working and what isn’t.
You also need patience. Many of us in RevOps struggle with this—we try something and two months later, we don’t think it’s working. But think about it—Is your sales cycle longer than two months? If not, you should probably wait to make another change until you’ve seen a full sales cycle. You have to be intentional about change—informed by data—and give it time to come to bear. That’s the balancing act of RevOps.
What are you reading and listening to these days?
I’m currently attending a RevOps Summer School. It’s hosted by Rosalyn Santa Elena. It’s been a cool opportunity to learn, not only from RevOps leaders but alongside sales and marketing peers. It has given me a lot of exposure to all things operations and helped me improve.
I’ve also been listening to the newly launched RevOps podcast. I listened to an episode on building a RevOps team from scratch. Do you start with a leader who has done it before? What skill sets do we look for? How do we prioritize those skill sets based on what the business needs? It’s a cool first-hand perspective.
“You also need patience. Many of us in RevOps struggle with this—we try something and two months later, we don’t think it’s working. But think about it—Is your sales cycle longer than two months?”
Lastly, what’s exciting you about the RevOps movement right now?
I’m learning something new every day. I’m seeing a shift in the conversations from merely defining RevOps to showing how we provide measurable value and grow within the function to solve complex operational problems. As more companies—even non-SaaS companies—start prioritizing RevOps, we’re going to get interesting case studies on how they have adapted the standard RevOps structure and responsibilities to accelerate revenue.
We’re asking more complex questions and the answers aren’t clear yet. I think that’s the most exciting part. We’re writing RevOps history right now.
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Want to keep up with Lauren? Connect with her on LinkedIn.
