Overview

Bill.com fixed how it measured delivery. Then lead time fell 27%.

Team
less than 1000 developers
Stakeholder
Deputy CIO
Process
Software delivery

Highlights

  • Lead time down 27%, with cycle time consistency up 63% across teams
  • Rework down 15%, returning capacity to the roadmap
  • Untested tasks down 80%
  • Every team on the same definitions for sprints, cycle time, and done, with no change to how teams plan or run sprints

Situation

Bill.com (NYSE: BILL) runs a financial operations platform used by nearly 480,000 businesses. Its engineering and product organization numbers about 2,200 people, and several hundred of them work inside the software delivery lifecycle.

As the organization scaled, the tooling around delivery did not keep pace. Sprints ran inconsistently from team to team, bottlenecks stayed hidden, and reporting stayed manual and fragmented.

Challenge

Leadership needed answers to four questions:

  • Where do app dev resources actually go across teams?
  • Which teams ship clean, tested code, and which do not?
  • Why do sprint durations and cycle times swing from team to team?
  • How much delivery capacity is rework quietly consuming?

In a fintech market with fast-moving competitors and thin margins, poor visibility into delivery cost real money and real time.

Solution

Bloomfilter gave Bill.com's IT and engineering leaders one shared view of delivery across every team. It read the systems teams already ran, and it surfaced problems that had been hidden inside the SDLC. Sprint durations varied from team to team, QA mapping had gaps, and bulk status changes were quietly skewing the numbers.

The work ran in four steps. Each step used the foundation the one before it laid.

PhaseFocusWhat it delivers
01Metric standardizationEvery team on the same definitions for sprints, cycle time, and done.
02Reporting integrityQA mapping gaps and bulk status changes corrected so the numbers reflect the work.
03Bottleneck visibilityHidden delays and inconsistent sprint durations surfaced across teams.
04Proof of valueApp dev spend and capacity tied to shipped, tested outcomes.

Outcome

Delivery numbers leadership can trust

Before any metric could be improved, it had to mean the same thing everywhere. Teams defined sprints, cycle time, and done in their own ways. Bulk status changes moved work in batches, and gaps in QA mapping made tested and untested work hard to tell apart.

Bloomfilter put every team on shared definitions, then corrected the reporting inaccuracies underneath them. Status reports stopped being assembled by hand from numbers nobody fully trusted. Leadership now reads delivery health across every team from one consistent record.

Hidden delays and rework, surfaced and cut

With clean data, the bottlenecks showed up team by team, along with the sprint-to-sprint swings that had made planning hard. Teams could see where work stalled and where it came back for rework, and then they could fix it.

MeasureChange
Lead time−27%
Cycle time consistency+63%
Rework−15%
Untested tasks−80%

Less rework and fewer untested tasks meant more of each sprint went to new work. Those gains came from seeing the delivery process clearly, not from adding people.

App dev spend, traced to what shipped

The last step tied cost to outcome. Leadership can trace app dev spend and capacity to shipped, tested work, team by team. That replaced estimates of engineering effectiveness with evidence.

With Bloomfilter, we now understand the true cost and effectiveness of all of our engineering teams.

Steve Januario, Deputy CIO, Bill.com

What the platform changed

Bill.com's delivery reporting went from assembled by hand to read from one record. The gains in lead time, consistency, and rework followed from fixing the measurement first. For an engineering organization of Bill.com's size, that is the difference between promising efficiency and proving it.

27%

Reduction in lead time

63%

Increase in cycle time consistency

About the data

Based on Bloomfilter's deployment at Bill.com across teams inside its software delivery lifecycle.

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