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BSS/OSS Academy

Strategy & Governance

Every part of the business will want AI, but without a shared process, each funds its own pilot. Money is spread thin, platforms are duplicated, risks go unchecked and nobody owns the outcome. A strategy and governance process fixes that. One committee decides which use cases are worth doing, every use case passes the same checks before money is spent, and each one is measured once it is live.

From business outcome to measurable value in four phases.
Business outcomes
  • Improved customer experience
  • Increased productivity
  • Reduced operational costs
  • Better decision-making
  • New revenue opportunities
  • Reduced business risk
Every phase serves these; its output is what it hands to the next.

4 → 1: Measure against the baseline set in phase 1

1
Phase 1

Strategy & use-case discovery

Start from the business outcome — revenue, cost, customer experience, risk — then find where AI could move it.

  • Agree the business outcomes and how they are measured today
  • Identify and prioritise the AI use cases that move them most
Output

Prioritised use cases, each tied to a target outcome

Design & business case

  1. Solution designArchitecture and approach
  2. Cost of executionBuild and run, year by year
  3. Benefits & ROITangible and intangible
  4. Business caseProceed · revise · stop
Process walkthrough

The four phases above as they run: phases 1 to 3 shared, then phase 4 on one of two delivery paths into one live service.

Phase 1 of 4

1.Strategy & use-case discovery

The steering committee agrees the business outcomes, then finds where AI could move them.

  • Business outcomes and baselines
  • Prioritised use-case portfolio
  • Target outcome per use case
  • Risk and compliance
  • Executive sponsorship
Investment & ROI
  • Rough investment estimate: build and run
  • Expected benefit and target ROI
Output

Prioritised use cases, each tied to a target outcome and measured today.

Phase 2 of 4

2.Financial assessment & solution design

Design the solution with the AI solution advisor, then test whether the outcome is worth what it costs.

  • Analyse the business problem
  • Recommend the AI approach
  • Define the solution architecture
  • Identify required technologies
  • Cost it and build the business case
Investment & ROI
  • Build and run cost for the design chosen
  • Outcome valued; ROI tested against the target
Output

A validated design with costs, ROI and a business case: proceed, revise or stop.

Phase 3 of 4

3.Readiness & delivery planning

Iterative

Can the organisation deliver and run the solution with what it already has, and how will it deliver it?

  • Existing AI and data platforms
  • Integration and applications
  • Data quality and access
  • Security, privacy and governance
  • Infrastructure and hosting
  • Skills and operating model
  • Organisational maturity
  • Delivery plan and operating model
Cost
  • Cost re-evaluated for delivery and run costs
Output

A delivery roadmap with resourcing, partners and a risk plan, and the delivery path it implies.

Decision point

Can existing, approved capabilities deliver this use case?

Decided from the readiness outcome — for this use case only, not for the whole organisation.

Yes → Path A · Reuse-firstNo, or only partly → Path B · Build / buy / adopt
Phase 4 of 4

A.Reuse-first

Path A

The capabilities exist, or need light extension.

  1. 1Pick the approved platforms
  2. 2Configure or extend
  3. 3Integrate, validate, deploy
Investment & ROI
  • Lower investment: platforms already paid for
  • Added run cost charged to the use case
Output

Solution live on trusted platforms.

Phase 4 of 4

B.Build / buy / adopt

Path B

Some capabilities are missing.

  1. 1Decide build, buy or adopt per gap
  2. 2Lay the foundations
  3. 3Build, integrate, deploy
Investment & ROI
  • Each gap costed: build, buy or adopt
  • Shared foundations funded once, reused later
Output

Solution live; new capabilities owned.

Phase 4 of 4

Implementation & Value Realisation

Live

The solution built, tested and deployed: a live service. Then the work after go-live begins.

  1. Built
  2. Tested
  3. Deployed
After go-live
  • Performance, quality and cost monitoring
  • Security, privacy and compliance
  • Support and operational ownership
  • Business value measurement
  • Continuous improvement and lifecycle

Including human oversight, incident handling, model evaluation and change control. Feedback loop to stage 1.

Run cost
  • Actual run cost tracked
Output

A live service, its value measured against the phase 1 baseline and reported.