← All case studies Case Study № 03 · Healthcare SaaS 20% → 100%+ throughput
Case Study № 03

Multi-team org: 20% to 100%+ in 6 months.

A Major SaaS Provider in the Healthcare Space · 2 Distributed Dev Teams
Avg Before
20%
Avg After
100%+
Timeline
6 mo
Teams
2
Output
§ 01 — The Situation

Two teams, two time zones, one broken system.

An engineering organization at a major healthcare SaaS provider with 2 dev teams — one based in India and the other distributed across North America — was struggling with delivery. Sprint completion rates were in the 20–40% range, with some sprints dipping below 20%. The organization needed a complete reset of how they planned and executed work across time zones and cultures.

Sprint completion in the 20–40% range, with some sprints dipping below 20%.
Two distributed teams: one based in India, one distributed across North America, with no shared planning framework.
No per-team capacity planning. Sprints were sized without accounting for actual available dev days.
Cross-team dependencies were undiscovered until mid-sprint, causing serial blockers.
Stories were oversized and lacked clear acceptance criteria, making completion a moving target.
§ 02 — What Changed

Incremental changes. Let the results speak.

Starting in mid-2022, new practices were introduced across the organization. Rather than a top-down mandate, the approach was to implement changes incrementally and let the results speak for themselves:

One.
Per-team capacity planning
Each team planned sprints based on their actual available dev days, accounting for time zones, holidays, and support load.
Two.
Cross-team coordination
Dependencies between teams were identified and planned for up front, eliminating mid-sprint blockers.
Three.
Proper story scoping
Teaching teams what a well-sized story looks like, with clear acceptance criteria, deliverable within a sprint, and structured as vertical slices through the stack.
Four.
Transparent metrics
Velocity and completion rates were visible to everyone, creating healthy accountability.
§ 03 — The Results

Steady progress. Then sustained excellence.

Progress was steady rather than instant. Within 6 months, teams were consistently hitting 70–100%+ of their sprint commitments. By mid-2023, several sprints exceeded 130% of commitment — teams had built enough predictability to pull in additional work when they finished early.

Sprint Completion
20% 100%+ sustained

Teams went from completing barely a fifth of their sprint commitments to consistently finishing at or above 100%. By mid-2023, several sprints hit 130%+ — teams pulling in additional work because they'd built the predictability to know when they had room.

Predictable sprints led to predictable releases. Over 52 weeks, the teams executed 61 deployments with zero outages and only one rollback. When teams deliver right-sized, well-tested work, deployments stop being scary.

Deployment Confidence
61 deployments. Zero outages.

Over a full year of predictable delivery: 61 deployments, 0 outages, and only 1 rollback. Right-sized, well-tested work makes releases routine rather than risky.

The compounding effect was powerful. As teams became more predictable, cross-team coordination became easier.
§ 04 — Key Takeaway

Plan based on capacity. Scope stories properly. Hold the system accountable.

Scaling these practices across multiple distributed teams requires patience and consistency. Each team adopted at their own pace, but the framework was the same: plan based on capacity, scope stories properly, track what matters, and hold the system accountable, not the people.

The compounding effect was powerful. As teams became more predictable, cross-team coordination became easier, which further improved delivery across the organization.

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