When delivery loses its predictability
Numerous software organisations ask versions of these four questions
Will we hit the date?
The board asks. The customer asks. The sales team asks. You answer with your gut. Engineering reality is somewhere else, and you find out at the next retrospective.
How much we can commit?
Teams over-commit. Capacity is "vibes." Working harder isn't shipping faster, and you can't tell whether team performance is improving or just feeling that way.
Can we trust our sources?
Reports exist. Insights are produced. But the org doesn't act on them. Forecasts are made in spreadsheets, monthly, by someone — and nobody trusts them.
Are we performing better?
Comparing to earlier Increments (PIs) - are we better in refining, developing and testing the scope, are we better scope focus, bugs reduction and fixing performance.
These aren't process problems. They're measurement problems. And measurement problems are solvable.
our approach
Predictable delivery rests on two pillars. We engineer both
Most organisations have one or the other. They have data, but they can't trust it. Or they have dashboards, but the org doesn't act on them. Agile Delivery Intelligence is the practice of engineering both halves so they work together
Trustworthy data
Engineered requirements, clean Jira foundation, and multi-level actionable analytics — so the numbers you look at are numbers you can defend in a board meeting.
Actionable decisions
ML-based forecasting and scenario simulation, integrated into the planning cycle — so the data becomes decisions you act on, weeks before the deadline.
Both halves. Installed in your stack. Owned by your team.
THE FRAMEWORK
Agile Delivery Intelligence — four areas where you benefit most
A working system installed inside your existing operational environment. We build, train, and hand over — no proprietary tooling, no consultant dependency.
Portfolio & Roadmap
How feasible is our product roadmap and what is next prio?
Demand intake & planning
What scope can we commit realistically next to?
Agile Delivery
Are we on track with current delivery, detect scope-at-risk
Release & customer feedback
Will scope be delivered in time & rolled out for customers.
Delivery intelligence models for data-driven decisions
HOW WE WORK
ENGAGEMENT MODEL
Our full framework is structured in four phases and several layers built in a modular way to meet exactly customer needs
Goals & Alignment
We start by understanding current processes, data, and gaps which hurt most and drafting to-be set-up with metering & decision points
- Understand most urgent issues
- Check current setup, processes, tools
- Align on priorities & target outcomes
- Fix scope, plan & commitment
- Define metrics, measurement points, planning horizons
- Identify data sources & gaps
Output: Project goals, timelines and objectives. Fixed scope.
Design & Foundation
We discover and engineer the data layer, clean, enhance, structure and validate data & models, building data flows for needed metrics and insights
- Demand & requirements engineering setup
- Jira foundation & cleanup: workflows, processes, governance
- Multi-level dashboards (Power BI, SAP SAC, Tableau, jira, AI-based solutions)
- Reports, scorecards, and executive views
- Integration into your existing BI tooling
Output: A live, trusted, clean data foundation needed for analytics and forecasting.
Build & Test
We build multi-level analytics by reports, dashboards across teams, levels, select & train forecast models for multi-horizon plans & simulations
- Data cleanup and validation
- Selection and training of forecast models
- Multi-horizon Capacity Simulation Model
- Scenario simulation for "what if?" planning
- Data driven capacity & scope planning
Output: Working analytical & forecasting system integrated into operational, planning and decision processes.
Enable & Improve
We integrate forecasts and insights into your planning rhythm, train your team to run the system, hand over ownership & improve on demand
- Integrate insights into processes: planning, refinement, prioritisation, delivery, testing
- Train teams and stakeholders to run the system
- Enablement & change management
- Monitor and improve continuously
- Measure impact & value
Output: Aligned operational & analytical tools handed-over to customer ready for further improvements.
WHAT THE FRAMEWORK PRODUCES
Tangible outcomes from recent engagements
Numbers below are from recent engagements at large & midsize companies.
frameworks we support
