Delivery Capability Baseline 2026 Establishing Objective Performance for Transformation Execution

At a Glance

Banks need a 2026 delivery capability baseline by assessing governance, skills, tooling, data, risk controls, and vendor dependencies, quantifying gaps against target outcomes to prioritize investments and enable predictable, compliant transformation execution.

Why delivery capability baselining is now a governance requirement

In large transformation portfolios, delivery performance is often assumed rather than evidenced. By 2026, that assumption is increasingly costly. Banks are managing concurrent modernization and regulatory commitments while delivery models shift toward product operating models, continuous delivery patterns, and tighter operational resilience expectations. A delivery capability baseline establishes an objective starting point for how the organization delivers change, providing a controlled reference for comparing performance over time and for separating genuine capability improvement from temporary throughput spikes.

The baseline is not a maturity label. It is a measured description of delivery behavior across the end-to-end delivery system, from intake and prioritization through build, release, adoption, and operational stabilization. Executives use it to govern trade offs that routinely surface in scaled change, including speed versus control evidence, innovation capacity versus run obligations, and local team optimization versus enterprise flow efficiency.

The transformation lifecycle and what the baseline must enable

Discovery and baseline assessment

This phase establishes the fact base. The output should include a baseline register defining how performance is measured, the scope of delivery units included, and the constraints that materially shape outcomes such as architecture dependencies, risk gates, environment stability, and third-party release coordination. Where banks use capability maps, the baseline should link delivery capabilities to accountable owners and to the specific delivery outcomes leaders intend to change.

Target capability definition

Targets should be expressed in observable operating behaviors rather than abstract ambitions. For example, a target state for delivery governance might specify how priority decisions are made, how risk gates are evidenced in the toolchain, how production readiness is validated, and what qualifies as releasable increment. Targets that are not grounded in baseline measurements typically degrade into inconsistent adoption across domains.

Pilot implementation

Pilots are only decision useful when they are comparable to the baseline. That requires consistent measurement definitions and a clear statement of what is being varied in the pilot such as team topology, funding model, release governance, test automation coverage, or operational readiness standards. Without this, improvements observed in pilots are not attributable and cannot be replicated with confidence.

Scaled rollout and capability building

Scaling requires that baseline measures become part of normal governance and not a one time diagnostic. The baseline should therefore include refresh rules and freeze points aligned to annual planning, major program gates, and regulatory reporting cycles. Capability building should be structured as measurable changes in system behavior such as reduced lead time, improved release reliability, and fewer late stage control defects.

Why baselining matters for executive decisions

Objective measurement that reduces decision risk

Transformation governance fails when leaders rely on narrative progress. A delivery capability baseline anchors decision making in comparable measures across business and technology domains, enabling leadership to identify where constraints are structural and where they are behavioral. This is particularly important when delivery performance is being pressured by parallel regulatory commitments or by modernization dependencies that produce hidden bottlenecks.

Business case development that survives scrutiny

Baselines make value cases credible by linking improvement hypotheses to measurable starting conditions. When leaders can show the current cost of delay, the current defect escape rate, the current change failure rate, and the current operational overhead of rework, they can justify investment in engineering enablement, automation, or operating model change without overstating benefits.

Prioritization and sequencing across constrained capacity

Delivery capacity is always finite. A baseline clarifies where capacity is truly being consumed, including unplanned work, incident recovery, control remediation, environment instability, and third-party coordination. That transparency is essential for sequencing change safely and for deciding which improvements must precede acceleration.

Baseline metrics that make delivery capability measurable

Delivery capability baselining is strongest when metrics are balanced across outcomes, throughput, and operational stability. Executives typically require three categories of measures, each defined with consistent calculation rules and segmentation so results remain comparable across domains.

Business metrics

• Value realization timing time from funding approval to measurable benefit in production
• Adoption and utilization uptake of delivered capability by intended users and journeys
• Cost to change unit cost of delivering a releasable increment including rework and control remediation
• Risk adjusted outcomes delivered change measured alongside control exceptions, audit findings, and customer harm indicators

Development metrics

• Lead time for change time from commitment to production availability
• Deployment frequency rate of production releases by product or service
• Change failure rate proportion of releases causing incidents, rollbacks, or urgent fixes
• Quality indicators defect escape rate, test automation coverage by critical path, and build stability

Operating metrics

• Availability of delivery platforms environment uptime, pipeline reliability, and toolchain performance
• Operational readiness evidence production readiness checks completed, runbook quality, and monitoring coverage
• Flow efficiency ratio of active work time to total elapsed time across the delivery stream

These categories should be governed as a baseline set. Isolated metric optimization is a common failure mode, for example improving deployment frequency while change failure rates rise, or reducing lead time by weakening evidence and increasing supervisory exposure.

Capability baselining artifacts that keep measurement defensible

To prevent baseline drift and to enable repeatable reporting, delivery baselining should produce a controlled artifact pack that can be audited and refreshed. A practical minimum set includes:

• Capability map linkage mapping delivery capabilities to accountable owners, delivery units, and measurable outcomes
• Delivery system topology product and platform boundaries, team topology, and dependency hotspots
• Governance decision register prioritization rules, risk gates, approval thresholds, and escalation paths
• Measurement definitions metric formulas, segmentation rules, data sources, and known limitations
• Baseline freeze points and refresh triggers when the baseline is treated as the reference and what changes force recalibration

Establishing a transformation baseline for delivery capability

Delivery capability is one of the most consequential baselines in transformation governance because it determines whether the organization can execute change at the speed leadership expects without accumulating operational risk. When delivery systems are under stress, banks typically see the same symptoms: late discovery of control defects, rising rework, unstable environments, and increasing dependency friction across domains.

Positioning delivery baselining as an executive governance discipline requires a structured assessment of enabling factors that make baseline measures sustainable, including operating model clarity, tooling and automation readiness, evidence discipline in release governance, and ownership strength for end-to-end flow outcomes. Used in that context, the DUNNIXER Digital Maturity Assessment supports leadership in evaluating readiness to scale, identifying sequencing risk created by capability gaps, and increasing decision confidence that measured improvements reflect durable system behavior rather than temporary effort.

References

• https://www.tmforum.org/open-digital-architecture/capability-framework/
• https://www.agilicist.com/delivery-transformation
• https://scaleupmethodology.com/scaling/scaling-startups/continuous-delivery/agile-delivery/
• https://isg-one.com/articles/agile-transformation-the-five-steps-to-building-an-agile-delivery-model#:~:text=Governance%20is%20established%20to%20address,from%20IT%20and%20the%20business.
• https://www.scottmadden.com/insight/five-keys-successful-shared-services-transformation/#:~:text=Our%20recommended%20approach%20for%20developing,on%20the%20shared%20services%20implementation.
• https://www.tmforum.org/open-digital-architecture/capability-framework/#:~:text=The%20capability%20map%20can%20be,%2C%20processes%2C%20etc.).
• https://www.migso-pcubed.com/blog/project-management-delivery/improving-delivery-capability-with-p3m3/#:~:text=all%20be%20included.-,2.,capability%20level%20has%20been%20achieved.
• https://internationaljournalcorner.com/index.php/ijird_ojs/article/download/135327/94453/325877#:~:text=A%20baseline%20is%20like%20a,are%20not%20the%20primary%20emphasis.
• https://www.agilicist.com/casestudies
• https://businessarchitectureassociates.com/wp-content/uploads/2020/10/5deecd9698d1d5cef8c9c313ea7b9316.pdf
• https://scaleupmethodology.com/scaling/scaling-startups/continuous-delivery/agile-delivery/#:~:text=How%20do%20we%20measure%20the,most%20significantly%20impact%20business%20outcomes.
• https://www.blue.works/en/unlocking-success-with-sap-business-transformation-suite/#:~:text=This%20centralized%20approach%20keeps%20each%20phase%20of,execution%2C%20every%20process%20aligns%20with%20organizational%20objectives.
• https://help.blindata.io/data-ops-platform/data-product-devops-management/#:~:text=A%20Data%20Product%20follows%20a%20structured%20lifecycle%2C,ensure%20a%20seamless%20transition%20between%20different%20phases.
• https://www.myshyft.com/blog/roi-tracking-framework/#:~:text=A%20well%2Ddesigned%20ROI%20tracking%20framework%20provides%20structure,maintained%20throughout%20the%20implementation%20lifecycle%20and%20beyond.
• https://www.strategyladders.com/business-strategy-consulting/#:~:text=The%20Typical%20Engagement%20Process%20Deep%20Dive%20&,(2%2D4%20Weeks):%20Intensive%20information%20gathering.%20This%20includes:
• https://culturepartners.com/insights/mastering-change-management-key-strategies-and-common-pitfalls/#:~:text=Measuring%20the%20success%20of%20change%20management%20initiatives,organizational%20performance%E2%80%94provide%20a%20comprehensive%20framework%20for%20evaluation.
• https://milestone.tech/salesforce/what-are-the-key-takeaways-of-salesforce-devops-in-2022/#:~:text=These%20metrics%20include%20change%20lead%20time%2C%20deployment,and%20plans%20to%20increase%20the%20deployment%20frequency.
• https://www.daytona.io/dotfiles/how-to-quantify-and-improve-developer-velocity#:~:text=Quantifying%20Developer%20Velocity%20Many%20organizations%20measure%20velocity,teams%20progress%20work%20from%20start%20to%20finish.
• https://devactivity.com/posts/using-quality-metrics-to-improve-software-development-productivity-and-quality/#:~:text=The%20use%20of%20quality%20metrics%20in%20the,processes%20and%20the%20quality%20of%20their%20code.