When agile delivery stops being transparent
As agile organizations scale, maintaining reliable delivery visibility, forecasting and planning becomes increasingly difficult. Companies creating product especially with multiple teams may face challenges in following areas:
- Performance metrics to be consistently tracked
- Inefficient resource allocation
- Jira exists, but not used for decision making
- Misaligned team efforts
- Work not tied to business goals
- Low reliable roadmap or release commitments
- Product decisions are reactive not predictive
- Management lacks real time single trustworthy insight into delivery health
- No early alerts if committments are at risk
- Lack of real-time transparency across teams, products, stakeholders
- Scope creep
- Uncontrolled backlog growth
- Poor progress tracking
- Low value work in progress
- Stakeholders do not know what to expect in next release
- Management reports dont reflect delivery reality
- Missed deadlines & not delivered features
- Lack of accurate delivery forecast
- Delivery commitments are not reliable
- Untracked defect fixes and rework
- Team performance variation
- Low estimation & planning accuracy
- Planning is not data-driven
- Teams overcommittment
- Unclear team capacity
- Delays and risks are recognized too late
our approach is
Agile Delivery Intelligence
Make agile delivery measurable
Actionable end-to-end metrics on all process stages, levels, roles making project traction easy and product decisions data-driven
Increase transparency & insights
Transparent, actionable, real-time insights on delivery on all levels, teams, horizons allow early risk recognition & smart resource allocation
Data-driven forecasts & planning
Data-driven forecasts (AI & ML-based) are a game changer for precise forecasts, confident planning and reliable committments
We set up metering, forecasting & planning of agile delivery
Our Services
Metrics & Intelligence setup
- Requirements analysis & definition for processes, reporting & metering
- Defining end-to-end metering strategy & KPI taxonomy
- Defining key metrics and measure points of agile development process (process efficiency, flow, output and outcome metrics)
- Validation of data model & how value is delivered
- Alignment with product / porfolio metrics / objectives
- Set-up of metering framework of collecting, processing & presenting
- Definition of critical agile reporting areas and audiences / updates
Transparency & Insights enablement (current and past releases)
- Data model setup/clean-up / analytical foundation
- Customizing of operational and analytical environment
- Creation of real-time actionable reports and dashboards giving insights into current delivery progress (jira, MS PowerBI, SAP SAC, tableau etc) e.g:
- Product portfolio & roadmap (increments, releases, etc)
- Next iteration dashboards (refinements, readiness, scope, etc)
- Current iteration tracking (scope, velocity, creep, risks, delays, waste)
- Multi-level reporting(teams, ARTs, planning horizons, effort)
- Bugs reporting
- Testing reporing (QA, UAT)
- Value delivery (features, value points
- Monitoring setup (backlog health-check)
Advanced Forecasts & Planning (future releases)
- Data cleaning & preparation for forecasting
- Develop, train & deploy ML-models for accurate prediction of key metrics enabling of precise forecasts and decision making far in advance
- Use ML-predictions and integrate it into agile processes like iteration planning, capacity or resource utilization planning, agile estimations, etc.
- Build accurate ML-forecasts of scope completion (roll-overs predictions) towards next release for stakeholder communication (clear committments)
- Achieving preciser roadmap planning due to combination of forecasts with adopted estimation techinques (T-shirt sizing, story points etc)
Tool selection & customizing
- Requirements assessment of operational and reporting tool evaluation
- Operational system clean-up and data preparation
- Customizing of real-time reports and dashboards in agile operational tools (jira atlassian, etc)
- Providing our own best practice report templates on inteltarget.com dashboards platform (from team up to ART and portfolio reportings)
- Development of tailored dashboards on inteltarget.com or customer platform
- Maintenance and ad-hoc reporting customizing (Microsoft Power BI, SAP SAC, tableau, plotly, own developments)
- Operationalization of reporting & derivation of actions
AGILE INSIGHTS AREAS
Discover some focus areas which bring you insight & transparency in product development cycle
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Teams velocity / Burn down - historical velocity charts: how fast teams deliver - are there any trends/patterns in delivery - velocity by work types: new features, bugs, maintenance, enablers, etc. - what is the ratio of work on scope/work on defects, operations/maintenance, waste? - trends, gauges (current velocity vs. average vs. maximum) - how many story points, features, bugs are delivered in certain period of time |
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Cumulated flow diagram(CFD) and readiness by phase: - to which % are teams ready for the next stage charts - cumulated flow diagram (CFD) - overview of scope completion by status - status of the features in scope - what is the number of added/outscoped features in release/increment (spill-overs) - what is the distribution of my features across workflow stages |
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Progress vs. time - visualization of scope progress across agile teams sprint by sprint - how fast are teams progressing on the increment scope - which teams are not on track and how far - which teams perform better / more efficient - how much scope has been completed vs. how much should have been completed by this time - what is the progress on features/epics/user stories (sprint by sprint) - what is the progress on iteration / release scope (sprint by sprint) |
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Agile compass shows direction: - progress by every prioritized epic/theme - which direction has advanced more in the last period - how much has to be done in each direction - do teams deliver what they commit, what is their predictability / sprint success ratio (committed vs. delivered) - what is the progress on iteration / release scope (sprint by sprint)? |
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ML-based delivery forecasting - tracking of scope delivery - forecasting current delivery for every team - will the scope delivered in time - which part of scope is on risk to be not delivered - how much time in addition is needed for scope completion - multiple forecasting models are trained - what is the forecast on iteration scope delivery given the average and forecasted velocity |
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Data driven capacity planning - automatic capacity forecast (ML-models) - workload and scope simulations (for story points, capacity, sprints needed, etc.) - which teams are overloaded with scope and which still have capacity - how many sprints needed to complete the scope - what amount of work teams will be capable to deliver in the next iteration? - what is team capacity for the next sprint/iteration? |
360 degree transparency with Agile Balanced Scorecard
REQUIREMENTS & DEMAND PIPELINE
We assist you in establishing transparency & tracking of scope progress, roadmap and single requirements along exploration, elicitation, refinement, development, QA and deployment. Overview of committed and delivered business value. You benefit from transparency on arrival rates, backlog throughput etc.
We assist you in establishing transparency & tracking of scope progress, roadmap and single requirements along exploration, elicitation, refinement, development, QA and deployment. Overview of committed and delivered business value. You benefit from transparency on arrival rates, backlog throughput etc.
DEVELOPMENT & DELIVERY
We measure, track and forecast metrics of teams operational performance (velocity, throughput, committed vs. delivered story points, scope working %, etc) to keep development on track and make precise predictions. Stability over time makes product development predictable and allows to detect issues on early stages.
We measure, track and forecast metrics of teams operational performance (velocity, throughput, committed vs. delivered story points, scope working %, etc) to keep development on track and make precise predictions. Stability over time makes product development predictable and allows to detect issues on early stages.
QA, TESTING & BUGS
You benefit from early checks of the product by receiving a complete overview on bugs/defects handling per team, capability, feature in operations as well as in QA, defining and applying metrics like resolution rate, defect severity, time, detection rate, test effectiveness & coverage, open/closed rates, etc)
You benefit from early checks of the product by receiving a complete overview on bugs/defects handling per team, capability, feature in operations as well as in QA, defining and applying metrics like resolution rate, defect severity, time, detection rate, test effectiveness & coverage, open/closed rates, etc)
CUSTOMER VALUE & FEEDBACK
Collection and tracking of one of the most important agile metrics: customer voice metrics like Customer Satisfaction (CSAT), Net promoter score (NPS), at every customer touchpoint to convert feedback into backlog features. Derivation of main customer satisfiers/dissatisfiers and tracking of key facets like product & service quality, improvements & responsiveness, value for money, easy of use etc.
Collection and tracking of one of the most important agile metrics: customer voice metrics like Customer Satisfaction (CSAT), Net promoter score (NPS), at every customer touchpoint to convert feedback into backlog features. Derivation of main customer satisfiers/dissatisfiers and tracking of key facets like product & service quality, improvements & responsiveness, value for money, easy of use etc.
Delivery intelligence models for data-driven decisions
ENGAGEMENT MODEL
Define objectives & metrics (2-3w)
We assist you in initial process analysis, key metrics and KPI definition, data preparation, clean-up and collection process
- Analyze process, audiences, stakeholders
- Define reporting levels, structures, cadences
- Define of measurement points & metrics
- Define metrics tresholds, tolerances, actions
- Analyze & prepare data sources
Measure, visualize & explore (3-4w)
We build reports & dashboards on various levels, aggregations, planning horizons (sprints, releases), topic structures etc.
- Building reports, scorecards, dashboards
- Set-up & customize analytical tools
- Measure team dynamics (velocity, throughputs, etc)
- Measure scope delivery and bias
- Integrate analytics into operations
ML-based predictions & plan (3-4w)*
Preparation & setup of ML-based predictions and their integration into forecasts & planning processes enabling to react far in advance
- Data clean-up and modelling
- Training of forecast models
- Predict burn-down rates, velocity, etc
- Integrating forecasts into processes
- Data driven capacity & scope planning
Enable, support & improve (on demand)
Stakeholder enablement and adoption, action derivation, support and continuous improvement and adjustments
- Ensure adoption & improve usability
- Testing feedback & Training
- Enablement & change management
- Monitor and improve continuously
- Measure impact & value
frameworks we support
technologies, tools & assets we work with
