Why Your Data Doesn’t Make Sense: 5 Things I Learned From Narrator Co-Founder Cedric Dussud

Nathan Collier
Estimated read time: 5 minutes, 40 seconds

2013. It’s Cedric Dussud’s first week on the job as the new engineering director at WeWork.

WeWork hasn’t yet become the beast of a company that changed the corporate world. It’s only managing a half-dozen offices in New York at the time.

But it’s growing fast.

That first week, Cedric got called into CEO Adam Neumann’s office. 

“So it’s him, and our head of our department, and me,” Cedric told me. “And Adam basically says, ‘Hey, I need you to build us a billing system. And I need it in three months.’”

So that’s what Cedric and his team did. And his main responsibility during the following five years was to scale WeWork’s billing system as the company grew from eight locations to 400.

In the process, Cedric learned a thing or two about managing data. 

In fact, Cedric and Ahmed Elsamadisi, the senior data engineer at WeWork at the time, learned so much about what it took to scale a data operation that they devised a whole new system to make it easier.

Together, they founded Narrator, a data platform that makes it easier for companies to run business intelligence without a large data team.

Cedric sat down with me recently to explain the key lessons he learned about data at WeWork — and how those lessons became the foundation that powers Narrator today. 

There were a lot of lessons that stood out to me, including:

  • Why metrics often don’t add up.
  • What happens when there’s not a single source of truth.
  • Why you should be skeptical about internal data.
  • When you need a data scientist to help you (and when you don’t).

You can watch the full interview or read a few of my main takeaways from our chat below.

5 Lessons From Cedric’s Experience

I learned a lot listening to Cedric’s story. Here are five of my biggest takeaways from the interview: 

1. Data Formulas Are Subtly Unique

Data science has a key difference from software engineering.

In software engineering, when you work on an existing system, you can build on what past coders have done before you.

But with data, any time you create something new, you can’t just copy the code — and because of that, the definitions often have subtle variations across reports. 

Cedric used the example of a CEO asking for a quarterly sales report broken down by region.

“You generally have to start over and write new SQL for it,” Cedric explained. 

“You kind of hope that if someone else made a quarterly report for sales, that you can then figure out how to reuse that to break it down by region, and maybe copy their logic. But if you don’t see their logic, you’ll make your own, and then your logic is going to be subtly different.”

When you’re using these reports to run your business, small differences add up quickly.

“You end up with just dozens of subtly different things across the company,” Cedric told us. “And it is actually a fairly common thing for the CEO to come in and say, ‘Why are these numbers not matching? What’s going on?’”

2. There Is No Single Source of Truth

Platforms with built-in analytics can tell you a lot, but they can’t tell you anything about data flowing through other systems in your business.

Cedric used the example of online ads. 

A platform will give you reports on the number of ads run, the cost, etc. The platform might even try to estimate how many people saw an ad before making a sale. But if you’re running ads on multiple platforms, then there’s not a single platform with all the necessary information to give you a complete answer, because they don’t have access to each other.

“If you were to sum up all the orders that Facebook thought it was responsible for, plus all the ones Google thought it was responsible for, and so on, it would sum up to far above 100% of your total orders,” Cedric explained. “That’s a case where you can’t rely on those numbers. You have to realize the source of truth actually doesn’t exist in any of them. It actually exists with all them combined.”

3. Be Skeptical About Your Metrics

Cedric recommends that you not trust a platform’s analytics unless you know exactly where the numbers are coming from and how they’re calculated.

In other words, you need to dig deep enough that you fully understand and trust the numbers you’re working with as you make business decisions. 

“It is always worse to overdo data than it is to underdo it,” he explained.  “If you’re thinking, I’m not doing it right, you’re going to engage your brain a lot and really second guess what you’re up to; whereas if you’ve gotten some fancy system that answers every question for you, you’ll be like, Cool, I’m doing data.”

4. Bring in a Data Analyst When Your Data Is Spread Across Multiple Systems

You don’t need a huge team of analysts in the beginning. In fact, getting too deep into your data can be a distraction:

“When you’re a small company, and you’ve got your mind wrapped around how everything is going, you usually understand your metrics,” he explained. And in that situation, you don’t need an analyst — not yet, anyway.

But when your tech stack starts to grow, that’s when the numbers start to become untrustworthy for founders and CEOs.

“When you get to a point where data starts to get spread across multiple places, that’s when you start to lose your ability to understand what’s going on.”

That’s when it’s time to hire an analyst or build out a more in-depth data strategy — someone who can help you fully trust the numbers again.

5. Focus Efforts on Projects That Will Attract New Customers

Even though Cedric built the billing system that runs a global business like WeWork, he does not recommend that SaaS founders should do the same.

It took months of full-time work for Cedric to bring a first version of WeWork’s billing system into production, an effort that — in his opinion — is not worth the investment for small SaaS and software companies.

“Work on marketing; work on understanding the customer and on new features — things that will bring you new customers,” he explained. “Don’t work on building your own billing system.”

Note: In addition to out-of-the-box dashboards, FastSpring maintains robust API and webhooks documentation so our customers can dig into their own financial data. Want to know more about what all our platform can do? Set up a demo or try it out for yourself.

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