When Emergence Capital was deciding whether to lead a Series A capital raise for knowledge-management company Guru in 2017, the private-equity firm had one pressing question on its mind: would Guru’s software attract sustained adoption?

Guru’s product is structured as a wiki; its users create a knowledge base over time. In Guru’s case, the content creators are the wiki user’s own employees; by sharing how they do things and answering questions from other employees, the company creates a how-to wiki that grows into a repository of internal operational information. The platform then uses bots and browser extensions to help companies share that internal knowledge base with employees.

The question was whether companies would pay a recurring subscription to build an internal wiki using the platform.  

“So many of these [wiki] products have really poor adoption,” Guru’s CEO, Rick Nucci, said in a SaaStr webcast. “What we were trying to answer, and what our future investor was trying to answer, was whether Guru was a product that had sustained adoption.”

To get the answer, the company made an instrumental resource decision.

“We effectively had to take some really critical engineering talent off of working on product, move them over to analytics, and build and prove out an answer to this important question,” Nucci said. “It was, I'll summarize by saying, a stressful situation.”

Lesson learned

Emergence ended up investing almost $9.5 million in the company, which has attracted high-profile customers like Spotify, Slack, Square and Shopify.

The central lesson from the exercise, Nucci said, is the hidden cost of misaligned analytics on a company’s ability to scale its operations efficiently. 

“I regret not taking the time to [centralize analytic operations] and have that single source of truth from a data perspective from the beginning,” he said. 

Atlassian, the widely used cloud collaboration platform, faced a similar problem, said Archana Agrawal, a former marketing head with the company and today CMO of Airtable, another cloud collaboration company. 

“When I started at Atlassian, we had fragmented analytics teams,” she said. Each team — marketing, product, sales, engineering — had its own data system, which impeded the company’s ability to scale efficiently. “We learned our lesson and ended up centralizing,” she said. “That was the right organization structure for us.”

In addition to centralizing the data analytics operation, the company designed it so that employees who were closest to the business on the operational side could make their own changes in what the data was measuring and how the results were formatted.

“What you want to enable is self-service data, so the folks closest to the business get to play with the data, explore it, communicate with and understand it, and evolve it as they need to,” she said. “What you want to avoid is creating multi-hub, rigid processes that end up taking forever to change when you need to move your metrics or change your dashboards.”

Employee engagement

A second lesson for Nucci in avoiding hidden costs to efficient scaling is getting employee buy-in on internal communications. 

A company can’t scale efficiently if employees don’t have a broad picture of what the company is doing, how they fit into that, and if they don’t have a place to go to get internal questions answered efficiently and consistently. 

“So much of what we do requires collaboration, so what we ask of every employee is to commit to an implied contract that if every one of us does two things, we’ll have the foundation for effective communication,” he said.  

The first part of the implied contract has to do with what Nucci calls asynchronous employee information sharing. Each employee is asked to commit to sharing what they know in a way that’s meaningful and actionable to other employees. The second part is a commitment by each employee to read and digest the information their colleagues share.

“When it’s working, everybody's making that commitment,” he said. “I’m going to share asynchronously various tactics, and I’m going to commit to reading what other people send me, and engage in that.”

The company launched the implied contract two quarters ago.

“I think it’s been a really effective way for all of us to look around at each other from an accountability standpoint and say, ‘We’re here for this,’” he said. 

By getting robust information sharing in place, it makes efficient scaling possible by making it unnecessary for a company to have to reinvent the wheel every time an employee is onboarded or must learn a process or system.