Leading Lender for Powersports Reduces Questions about Data by 40% with Documentation and Self-service

Founded in 2014, Octane^® (Octane Lending, Inc.) is a specialty lender, offering instant financing to consumers purchasing powersports vehicles like motorcycles, snowmobiles, personal watercraft, ATVs, and more.

Historically, data at Octane has been synonymous with financial reporting. Octane is a technology company and non-bank lender which derives significant revenue from loan securitizations, placing demands on accurate reporting, delivered under strict deadlines. With these reporting requirements, Octane’s data capabilities were robust, but were focused on mission-critical obligations, and not necessarily on traditional business intelligence.

Alex Bendix, Data Product Manager, joined Octane to ensure business intelligence got the focus it deserved, had the right team and technology to support it, and was well-adopted by data consumers that could make the most of it.

“We carved out a new team to focus on data needs that weren’t related to financial reporting,” Alex shared. “We’re focused on building the foundation for business intelligence, supporting anything from individual product managers doing ad hoc analysis, to dashboarding and reporting, basic forecasting, all the way out to predictive machine learning models that our data science team is building.”

Two separate data teams now exist at Octane, one focused on financial reporting, and the other on business intelligence, comprising Data Engineers, a Data Analyst, and a Product Manager and Engineering Manager guiding each team. And supporting these functions is a modern data stack beginning with AWS infrastructure, and including Athena, Redshift, Airflow, and Tableau.

Siloed Knowledge, Teams, and Tools

In part due to financial reporting preceding a formal data & analytics function, Octane’s data practitioners are often siloed, with different parts of the business employing their own analytics teams, and no single centralized analytics function.

“Data has been pivotal for us to be able to advance as a company for so many years. But teams were using data in different ways,” Alex explained. “There are different levels of scrutiny depending on the use case. Someone on our Finance team who’s producing reporting that will go to ratings agencies, or those purchasing in debt markets, are going to have very different needs from someone on our Sales team who’s looking to understand conversion metrics at different dealerships.”

While these functions may have been siloed, the data they used in their analysis was generally from the same sources, which could lead to divergent views over how to use shared data, and myriad ways of calculating and visualizing information. Without centralized documentation, and a common understanding of their data assets, a shared language for, and approach to, data could not exist.

The first step was coming up with documentation. That was the really, really difficult part. Pre-Covid, we were generally all in New York (and a lot smaller), so you could easily resolve data questions in person. Once the pandemic hit, you could no longer be in the same room as someone and say, ‘Hey, make sure that you’re looking at this data, not that data.’ But then, the next priority was making that information easily usable. We had all that information available in spreadsheets accessed by clicking through 5 pages on Octane’s intranet. So we recognized that the company was large enough that it needed to be an easy, frictionless experience to access that documentation in a unified way.”

With a shared understanding of their data growing within Octane, their next step was clear, to find a modern data catalog that could serve as a single, easily navigable home for their assets.

Choosing Atlan to Enable Self-service

For Octane’s needs, spanning compatibility with their modern data stack, enablement for a range of users from technical to non-technical, and empathy with their needs as a data team, Atlan proved to be the perfect fit.

“In terms of why Atlan stood out, I think it just does a lot of things. A lot of different tools are good at particular things like documentation, or their querying engine.I think the nice thing about Atlan was that it felt pretty intuitive in terms of how things were all looped together and it felt like there was a lot of opportunity to expand. Clearly the team that had built the product were data users, themselves, and it felt like there was a good understanding of what folks like us were actually experiencing on the ground,” Alex shared.

Realizing that Atlan needed an internal champion at Octane in order to be adopted, Alex drew on his Product Management background and began analyzing what his prospective users would need, building requirements for a self-service glossary valuable enough to be adopted consistently by data consumers.

“My strategy was that I wanted users to believe in the platform, and for Atlan to have significant credibility. And when it comes to documentation, if you search for a common, basic table, you should be able to see documentation. Every moment you go in there and don’t see what you need, you lose faith in this data marketplace,” Alex shared.

Beginning with teams of data consumers, Alex began asking what three to five tables are most important to their everyday work. Then, working back from those required tables to their internal owners, he ensured that subject matter experts were documenting their knowledge and sharing it in a simple-to-consume format.

“The really difficult part was motivating subject matter experts to actually put in all this information. A lot of it was just brute force where I said, ‘I will literally just sit on a Zoom call and you will just tell me this live, I will record it, and we’ll get it in Atlan.’ But the nice thing was, once we got the first couple of data dictionaries put together, it almost felt like a rumor where it was like, ‘Oh, I’ve heard that team did it. Okay fine, we’ll do it too.’ It created a culture of sharing and data documentation.”

And with the knowledge that his colleagues prefer to take the fastest and simplest path to completing their work, he formed a series of presentations, demos, and videos dubbed “Atlan University”, offering it directly to his colleagues that would get the most benefit, and approaching team leaders to encourage their teams to adopt it.

“In our first month we had fewer than five weekly active users, then it was 10 weekly active users. And for context, now in some months we have 50 – 60  monthly active users. Things have grown exponentially,” Alex explained. “I made it my personal mission to evangelize Atlan at every opportunity because I realized with one of these tools, people are only going to use it if their coworkers and colleagues are using it, and if it’s clear that it can make their lives easier. There was a real opportunity to be a lot more efficient.”

Saving 200 Hours per Month in Data Engineer Effort

A successful rollout of Atlan, robust documentation, and buy-in from subject matter experts and data consumers alike, meant that Alex and his team were ready to measure the impact that self-service made on Octane.

Alex kept a close eye on a key internal metric: The volume of questions and answers in an internal Slack channel for data support. Data consumers from all over Octane would place their questions about data into the channel, where data engineers would be responsible for answering them. While some questions were relevant, oftentimes these requests were simple, ranging from basic information about metrics, to the nature of existing dashboards, or why a spreadsheet didn’t look quite right.

But by making their data assets searchable in Atlan, appending rich context and documentation to those assets, and enabling self-service for data consumers, the number of messages reduced by 40% in just three months, saving the team 200 hours per month.

“You used to have people asking questions like, ‘Hey, where do I find an application? Where do I find someone’s name?’ And with Atlan, all you need to do is search someone’s name, it’s done,” Alex shared. “A lot of the needs were very simple questions, and people not knowing how to self-serve. It was really gratifying to have that north star metric of the number of times we were asked questions in public channels. Atlan reduced it really, really significantly.”

Each engineer was answering questions 10 to 20% of their time. And then you multiply that over a certain number of employees across the team, that’s hundreds of hours per month that you’re losing in terms of productivity. Being able to have everyone be a little bit more focused led to a lot more time spent on the things that actually move the needle. And for us, that’s setting the foundation for business intelligence at the company. Helping those data scientists, helping those analysts, helping those PMs who are trying to get more data savvy.”

Quantification: Data Engineering’s Secret Sauce

Key to Alex’s success in evangelizing for Atlan with leadership and consumers alike is his steadfast commitment to quantification. With the potential impact of his team’s work measured from the start, Alex is able to simply and quickly justify the effort of his programs, and offer compelling reasoning for users to adopt Atlan.

“For me, quantification is usually just that you’re driving more revenue or reducing costs. And if you’re reducing costs, it’s an obvious direct cost, or an indirect cost, like time saved. It’s pretty straightforward to look at time saved by figuring out the number of people affected by something, how many hours you’re saving a week, and to come up with a blended people cost,” Alex explained.

With that blended people cost in place, Alex then identifies the average user affected by the improvements he aims to implement, simply multiplying the time saved by their efforts by what the full compensation of that user or users might be.

“My advice is to be willing to work with ambiguity and come up with estimates. It’s better to come up with an estimate, have someone challenge it, then refine it, than it is to say nothing at all,” Alex shared. “Then, make sure you’re screaming that from the rooftops as much as possible. That’s either grassroots in individual conversations with people, and that’s also in large presentations or with leadership. Take every opportunity to talk about all those metrics you came up with. You need to be your own biggest advocate.”

Fast-growing Data Literacy

With so many of Octane’s data consumers becoming more savvy due to Atlan and the context Alex and his team equipped the platform with, unexpected benefits continue to arise.

“We had at least ten people that had never touched data before using Atlan. They had to work with other people and ask ‘Hey, can you get this data for me?’ And as a result of Atlan, they felt empowered to query data, themselves,” Alex shared. “That might not sound like that big of a deal to someone who’s super data fluent, but for a lot of people who have convinced themselves they’re not technical, that’s a huge confidence booster. Atlan allowed people that are quantitatively inclined or analytically inclined and be able to extract data for their own analytical projects.”

While Octane once had a chasm of data literacy between its technical teams and its data consumers, Atlan is giving Alex’s colleagues that may be analytically inclined, but not technical experts, the tools they need to apply data themselves. 

“I feel like working with a lot of folks at Octane that were analytically inclined, but didn’t necessarily have the particular tools to do that was really, really exciting. I think that that creates a better culture of respect within the teams. There’s a much deeper understanding when folks like product managers, or people in leadership, feel a lot more comfortable going in and pulling the data themselves. There’s just more empathy when people have a better idea of what their coworkers are doing.”

Octane and Atlan: Growing in Parallel

Even having hundreds of hours of effort responding to data requests, and opening up data to users who have never used it before, Alex and his team’s ambitions for Atlan remain ambitious, with a focus on driving more value with key users, and building a world-class team of technical experts.

“We’re at the point where we have as many as 70 monthly active users. That’s not 100% of people who use data at Octane, but that’s pretty close,” Alex shared. “Now, we’ve switched from a penetration viewpoint to a usage volume expansion within the user base that we’ve penetrated.”

While a small number of users at Octane might not use Atlan, as their data needs are low and infrequent, Alex refers to a “middle group” of users that do have needs for data, and use it in varying degrees. With Atlan established as Octane’s catalog of record, their data engineering team is hard at work increasing the number of users that are aware Atlan can help, and are using it actively.

And beyond the obvious benefit yielded by their data consumers, Alex is excited for his team to grow in capability and vision, alongside their newfound partnership with Atlan.

“I’m excited for Octane and Atlan to grow in parallel. Atlan is continuing to build out new features and they’re getting both increasingly broad and increasingly specific. It’s great to see the company just continue to offer more and more functionality that we can work with. And I’m excited for us to move up that adoption curve ourselves and start to have even more and more advanced teachers of Atlan. I want our most advanced users to be on par with any of the most advanced users from any other company. And I think doing that would really be an indicator that we are persisting in this data-driven culture.”

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