Define the destination
Agree business outcomes, design principles, scope and constraints. Set measurable service, cost, risk and adoption targets against the current baseline.
02 / Create the blueprint
Transformation &
operating model design.
Turn discovery into a blueprint the business can build, operate and own.
We align business outcomes, organizational responsibilities and technology choices—then define how change will be delivered, governed and measured.
The future-state blueprint
Business outcomesValue · Service · Risk · Growth
Operating modelPeople, processes and accountability
ArchitectureData, platforms and integration
Transformation roadmapSequenced delivery with owners and acceptance gates
Governance & measurementDecisions, controls and evidence across every layer
Foundations
A Bitbryx Methodology
Build from evidence
A strong design starts with an agreed foundation.
Use the validated function inventory, dependency map and rationalization decisions from discovery to define the future state. Resolve the gaps between what the business wants and what people, processes and systems can support.
Design how it works
Shape the target operating model and architecture together. Clarify service ownership, workflow handoffs, data responsibilities and control requirements.
Sequence the change
Compare options and trade-offs. Prioritize delivery around value, dependencies, capacity and business continuity, with explicit decision and acceptance gates.
The target operating model
Seven dimensions. One working capability.
A platform change affects the organization around it. Each dimension must support the same business outcomes, with ownership and interfaces designed together.
01 / Strategy
Purpose, customer needs, value proposition, priorities and success measures guide every design choice.
02 / Structure
Service boundaries, teams, reporting relationships and cross-functional accountability.
03 / Process
End-to-end workflows, handoffs, exceptions, controls and service expectations.
04 / People
Roles, skills, capacity, training, adoption and the support needed to perform.
05 / Data
Ownership, definitions, quality, lineage, access and lifecycle responsibilities.
06 / Technology
Platforms, integration, automation, resilience and supportability.
07 / Governance
Decision rights, approval forums, escalation routes, controls and performance review.
From design to delivery
A roadmap with decisions built in.
Each delivery wave has a defined outcome, accountable owner and evidence needed to proceed. Timing follows the scale and dependencies of the engagement.
A / ALIGN
Agree the design
Assess options, resolve trade-offs and confirm the target model, architecture and business case.
Design acceptanceBusiness, technology and control owners agree the scope, measures and responsibilities.
B / PROVE
Validate a delivery wave
Define a pilot or first wave, test critical assumptions and plan conversion, reconciliation and continuity controls.
Delivery readinessDependencies, resources, risks and acceptance criteria are understood and assigned.
C / SEQUENCE
Plan rollout and ownership
Set rollout dependencies, adoption activities and operational handover requirements for subsequent waves.
Controlled progressionLater waves depend on verified results and readiness, with risks explicitly reviewed.
Outcomes
A blueprint ready to govern the build.
Target operating model
Service model, workflows, responsibilities, decision rights and governance arrangements.
Future-state architecture
Capabilities, platforms, data flows, interfaces and required controls.
Transformation roadmap
Prioritized waves, dependencies, accountable owners, resource needs and decision gates.
Outcome and adoption plan
Baseline measures, benefit owners, acceptance criteria, training and transition requirements.
Ready to govern the build
Design accepted.
Delivery accountable.
Move into conversion planning and assurance when the in-scope blueprint, ownership, sequencing and acceptance criteria are agreed, with material risks and dependencies recorded. AI requirements can inform the design; full AI Enablement follows completion and acceptance of the foundational work across the first four phases.
Explore 03 / Conversion planning and assurance →