Elastic case study

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“Accelerating our close from 12 days to 5 didn’t happen overnight—it required building real trust in the platform. Now, the team has complete confidence that we’ll get the right numbers straight from production the first time, which really speaks to the power of our revenue engine.”

— Arvind Setty, Director, Revenue Accounting, Elastic 

Elastic case study

About

Elastic is a search AI company helping organizations find, understand, and act on data. Its business runs on a mix of term-license, support, and cloud consumption revenue, a combination that produces long, complex contracts and frequent amendments.

Industry:

Software and technology

01 

The Challenge

Before Zuora Revenue, Elastic relied on inefficient, spreadsheet-based revenue tracking. Every contract modification required new tabs and manual calculations, making review, audits and data analysis a major undertaking.

02

The Solution

With Zuora Revenue in place, Elastic can now automate its revenue recognition in compliance with ASC 606, flowing data directly from NetSuite. Instead of repeatedly modifying the custom transformation layer, the team uses built-in data-augmentation rules and other setups within Zuora Revenue, enabling faster, lower-risk adaptations. 

03 

The Benefits

  • Cut close time by more than half — from a 12-day process down to roughly 5 days today 
  • Reduced dependence on IT — the team has made minimal  changes to its transformation layer in three to four years, handling most updates through configuration instead where appropriate.
  • Built an audit trail for complex contracts — six- and seven-version contract modifications can now be explained version by version, directly in the system, regardless of retro or prospective contract modification.
  • Made downstream reporting easier — Clean data from Revenue made downstream revenue data syncs and reporting in BigQuery easier. ,
  • Made testing safer — a self-service sandbox refresh lets the team validate real-world edge cases before making changes in production

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“The biggest shift for our team isn’t just speed—it’s self-sufficiency. Using a sandbox that mirrors production, we can configure settings, validate edge cases, and run ‘what-if’ scenarios to find solutions independently. We no longer spend hours working across IT and cross-functional teams just to reload data and recreate test data and environments.”

Arvind Setty
Director, Revenue Accounting, Elastic

Arvind Setty, Director of Revenue Accounting, joined Elastic about four years ago, well after the company had gone live on Zuora Revenue, but not so long after that the old world was out of reach. Colleagues still describe it to him in detail: a revenue process built entirely on spreadsheets, where every contract amendment meant a new tab and every question about a legacy deal meant digging back through years of manual calculations. 

Answering a simple question about a long-running contract meant returning to the original files and reconstructing the history manually. 

“I still get nightmares of those spreadsheets,” Setty says, only half joking. Migrating that history into a live system was, by all accounts, as much work as implementing the new solution itself.

From reconstruction to real time

The clearest shift Setty’s team has seen since making the switch to Zuora is that revenue no longer lives in the past tense. Elastic’s transactions are current and flowing through Zuora Revenue at a controlled speed, rather than sitting in disconnected files waiting to be reconciled. That change alone dramatically transformed what the team’s month looks like, but it didn’t happen all at once.

When Zuora Revenue was initially implemented, Elastic’s close once ran two processes in parallel: a full close in a sandbox to validate the numbers, followed by the same work again in production, adding up to roughly 12 days. As the team’s confidence in the platform grew, it retired the duplicate sandbox step, and the close settled into the 8-to-9-day range. From there, Setty estimates the team has shaved off roughly a day per year since, landing at approximately 5 days today. “The confidence the team has that we’ll get the right numbers from production the first time speaks volumes about how much we’ve gotten comfortable with the product,” he says.

Self-sufficiency, by design

At the early stage of implementing Zuora Revenue, a process change meant holding for an opening in IT’s calendar, waiting on updates to a complex transformation layer, and then scheduling QA and deployment. Today, Elastic team first looks at what it can configure and validate in Zuora Revenue on its own in the Sandbox Environment  with the ultimate solution deployed in Production with a rigid IT control . 

In the last three or four years, the team has barely needed to touch its transformation layer. New products and SKUs get evaluated upstream first, then matched to existing capabilities before anyone has to consider bugging IT. “We are quite self-sufficient thanks to Zuora Revenue,” Setty says. 

Setty singles out one capability as particularly valuable: the ability to refresh a production instance into a sandbox and test against real data. In the event that the team does encounter a corner case, they can reproduce it, experiment safely, and get sign-off before anything touches production. “We can test directly in the sandbox, get completely comfortable with the solution, and secure sign-off before moving the fix to production. It makes the entire process seamless while automatically capturing all the necessary audit support.”

Elastic has also begun exploring and evaluating Zuora AI’s read capability in sandbox to speed up contract explanations.

An audit trail that holds up

Contract modifications are, in Setty’s words, one of the most complex parts of Elastic’s revenue process. Some contracts carry six or seven amended versions, each one a potential headache when it’s time to walk an auditor through what happened and why. Zuora Revenue’s contract-modification history gives the team a version-by-version record it can present directly, rather than reconstructing the story from old spreadsheets. Transaction price allocation, which Setty calls one of the most complex calculations the team manages, has stayed stable throughout, meaning it’s one less variable to explain during an audit.

Reporting that doesn’t wait for the close to finish

Elastic has also transformed how they handle reporting, automatically syncing data from Zuora Revenue to BigQuery. Now, teams can analyze revenue information throughout the close instead of waiting for all revenue processing to finish. Elastic has also reduced the volume of data handled in Zuora Revenue by routing high-volume monthly transactions that do not require revenue recognition there directly to NetSuite general ledger. The result is a smaller, more manageable reporting dataset and a more efficient close process.

Looking back, Setty keeps returning to the same point: the relief of not having to hold years of manual history in his head. “Just knowing that I don’t have to deal with endless spreadsheets,” he says, “I’m really glad.”

 

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