When engineering leaders can’t answer simple questions with confidence, trust erodes fast.
Questions like:
- Are our teams actually delivering better over time?
- Where is work getting stuck and why?
- Are our process changes and AI investments helping, or just adding noise?
At Wood Mackenzie, those questions mattered more as the organization scaled its data platform and engineering teams. Leadership needed a clearer, shared understanding of how work flowed across teams, not just snapshots from individual boards or opinions shaped by local context.
They turned to Appfire Flow to replace assumptions with evidence and create a trusted, organization-wide view of delivery.
The challenge: fragmented data, inconsistent answers, and growing risk
Wood Mackenzie’s data platform teams primarily work in Scrum. But as the organization grew, so did variation in how teams structured work, tracked progress, and interpreted metrics.
That created real problems for leadership.
A Director of Engineering needed:
- A reliable view across multiple teams contributing to shared platforms
- Insight into delivery trends over time, not isolated sprint reports
- Data they could trust when making prioritization and resourcing decisions
At the same time, the Head of Agile Product Delivery needed:
- Evidence that Scrum practices were improving outcomes, not just being followed
- A way to coach teams using shared, credible data
- Visibility into how different practices affected predictability and flow
Instead, they were navigating:
- Different board configurations and workflows
- Inconsistent metric definitions
- Manual reporting and one-off exports
- No clear way to aggregate insights across teams
That made it hard to answer even basic leadership questions with confidence.
As Simon Platt, product director at Wood Mackenzie, said, “it doesn't breed trust or confidence if you can't answer simple questions about what's going on in the teams effectively.”
Without a consistent source of truth, conversations stalled. Decisions relied on partial data or instinct. And as delivery complexity increased, so did risk.
What Wood Mackenzie needed from Flow
Wood Mackenzie wasn’t looking for more dashboards. They needed standardized, trustworthy insight that could scale with their organization.
Three requirements stood out.
One shared source of truth for delivery
Leadership needed a single place where:
- Data from Jira and engineering tools came together
- Metrics were calculated consistently across teams
- Everyone from engineers to executives could see the same picture
As Platt puts it, “Having somewhere central where you could see all of that information and use it was important to us.”
Appfire Flow gave them a unified view of how work actually moved across the data platform, making it easier to discuss progress, risks, and outcomes without debating the data itself.
Consistent metrics across diverse teams
Variation in ways of working is normal in mature engineering organizations. But without standardization, comparison and learning break down.
Flow normalized delivery metrics across teams, making it possible to:
- Spot bottlenecks in review, integration, or deployment stages
- See where work routinely stalled or piled up
- Identify teams with stronger flow patterns and learn from them
Instead of relying on anecdotal comparisons, leaders could now see trends and outliers clearly, grounded in shared definitions.
Credible answers to leadership questions
Most importantly, Appfire Flow helped Wood Mackenzie replace guesswork with clarity.
When stakeholders asked:
- How long does work actually take end-to-end?
- Are recent changes improving delivery or creating friction?
- Where should we focus next to reduce risk and improve predictability?
Leadership could answer with confidence (and show the data behind it).
What changed after adopting Appfire Flow
Once Appfire Flow was in place, conversations across engineering shifted in meaningful ways and became more constructive.
Clear visibility across the data platform
Instead of jumping between boards and reports, leaders gained a longitudinal view of delivery across teams.
That made it hard to answer even basic leadership questions with confidence.
With Appfire Flow, the team could see:
- How work flowed through the system over time
- Where delays consistently emerged
- Whether changes like WIP limits or refined definitions of done led to measurable improvement
That visibility made it easier to focus on system-level improvements instead of reacting to individual sprint outcomes.
As James Constable, director of engineering at Wood Mackenzie, said, “Flow's had a massive impact on developer ownership and accountability. We're really transparent in the way that we use Flow. All of the engineers have access to it. They can see their own metrics. They can see the metrics of the other team.”
Comparability without forcing uniformity
Appfire Flow didn’t require teams to work the same way. It gave leaders a way to understand differences without penalizing them.
By applying consistent logic to delivery metrics, leaders could:
- Compare trends fairly across teams
- Identify where additional support or coaching would help
- Separate healthy variation from systemic issues
For Agile leadership, this made coaching more effective and grounded in observable data, not opinion.
Scrum focused on outcomes, not ceremonies
With Appfire Flow, Scrum conversations shifted away from whether teams were “doing Scrum right” and toward whether delivery was actually improving.
Leaders could now see:
- How unplanned work affected sprint commitments
- Where work was blocked or bounced between teams
- Whether predictability improved sprint over sprint
Scrum became a means to better outcomes, not an end in itself.
The result: better conversations, stronger trust, and clearer decisions
Appfire Flow changed more than reporting. It changed how Wood Mackenzie talked about delivery.
For engineering leaders
- Greater confidence in delivery data
- Faster, clearer answers for stakeholders
- Fewer debates about whose numbers were right
Leadership discussions shifted from defending metrics to deciding what to do next.
For Agile delivery and coaching
- Coaching grounded in observable patterns
- Shared understanding across teams
- More productive retrospectives and improvement conversations
Data became a neutral, trusted starting point for change.
For teams
- Visibility into their own delivery patterns
- Clearer connection between daily work and broader outcomes
- A stronger sense of ownership and accountability
Because teams and leaders were looking at the same data, conversations felt more collaborative and constructive.
Building confidence in an increasingly complex engineering landscape
As engineering organizations scale and adopt AI-assisted development, the cost of flying blind increases. Wood Mackenzie’s experience shows that reports alone don’t provide trust and transparency: Teams need standardized insight and shared understanding.
By using Appfire Flow, they connected:
- How teams work day to day
- How work flows across the organization
- How confidently leadership can guide priorities and investments
Looking ahead, Platt said “We'll continue to use [Appfire Flow] as our trusted partner when it comes to a gold source of information and metrics, etc.”
That foundation makes it easier to navigate change, reduce risk, and improve delivery over time, even as the system grows more complex.
Want to see how Appfire Flow creates clarity across engineering teams?
Explore how Appfire Flow helps engineering leaders replace guesswork with trusted insight and make better decisions in the AI-augmented SDLC.
Experience Appfire Flow in actionAbout Wood Mackenzie:
Wood Mackenzie is a global leader in analytics, insights, and proprietary data across the energy and natural resources landscape. With more than 50 years of experience, the firm provides data, analytics, research, insight, events, and consulting services to help organizations understand interconnected markets and make strategic decisions. Wood Mackenzie employs more than 2,600 experts in over 30 locations worldwide and is owned by Veritas Capital.
