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Delivery Remediation & Turnaround | CRM & Data Angels.AI Consulting
Delivery Remediation & Turnaround

From Red to Green.
A Structured Path Back.

When a Salesforce engagement has gone off track — scope out of control, stakeholders losing confidence, delivery health in decline — we step in as Delivery Lead, Program Manager, and Lead Functional Solution Architect simultaneously. Every engagement is assessed individually. We tell you exactly what recovery looks like — and whether we are the right fit.

30–50%
of CRM Implementations
Fail to meet their intended objectives — almost never for technical reasons. The gap is leadership, governance, and functional design.
One
Senior Resource
Delivery Lead, Program Manager, and Lead Functional Solution Architect in one person — governance and functional direction held simultaneously, without adding complexity.
6
Structured Phases
From root cause diagnosis through post-remediation monitoring — a framework grounded in Salesforce delivery best practices and Center of Excellence standards.

1
Phase One

Assessment & Root Cause Analysis

Before anything can be fixed, the full picture has to be clear. This phase establishes what is broken, why, and what the baseline looks like.

1.1

Salesforce Org Health Check

A full audit of the current org — automation (Flows, Apex), data model, integrations, governor limits, security configuration, and user activity patterns. The goal is an objective picture of where the system stands, what is functioning as intended, and where technical risk is concentrated.

1.2

Root Cause Analysis

Identify specifically why the engagement is struggling. Common causes include poor data architecture, uncontrolled customization, lack of user adoption, broken or incorrectly mapped integrations, requirements that were never validated against business operations, and governance that was either absent or inconsistently enforced.

Root causes are documented with evidence — not surfaced as assumptions or attributed without data.

1.3

Stakeholder Gap Identification

Re-engage IT, business SMEs, and senior leaders to identify where the original business objectives and the system’s current functionality have diverged. Often this gap is the most consequential finding — and the most useful signal for scoping the recovery work.

1.4

Delivery Team Performance & Capacity Assessment

Review the delivery team’s performance, capacity, burn rate, and velocity to date. This is not about assigning blame — it is about understanding where the execution gaps are, what the current team can realistically sustain, and what additional support or structural change is needed.

1.5

Baseline and Target KPI Establishment

Define measurable baselines for Org Health, Technical Debt status, Delivery Execution performance, Customer CSAT, Adoption, and Release/Sprint health. Establish target KPIs against which recovery progress will be tracked throughout the engagement — so that “improved” has a specific, agreed definition.


2
Phase Two

Immediate Stabilization

Once the root causes are clear, the first priority is to stop the damage from compounding. This phase puts the right controls in place, halts uncontrolled work, and re-establishes the structural foundation the delivery needs to move forward cleanly.

From a best practice perspective, stabilization is critical to Salesforce delivery engagements when projects are at risk because it shifts the focus from merely “going live” to creating a sustainable, high-performing system. It serves as a necessary buffer to fix unexpected technical issues, align system behavior with user expectations, and prevent immediate technical debt.

2.1

Pause Non-Critical Development and Reprioritize

Stop work on low-priority or non-validated items. Redirect the team’s capacity toward the highest-impact issues identified in Phase 1. This is a deliberate triage decision, not a blanket freeze — the goal is focused recovery, not paralysis.

2.2

Implement Change Management Controls

Where possible, block direct modifications to the production org. All changes are routed through a controlled release process from this point forward. If production has been treated as a sandbox, that stops here.

2.3

Review and Validate the RAID Log

Assess the current RAID log (Risks, Assumptions, Issues, Dependencies) for completeness and accuracy. In troubled engagements, RAID logs are frequently outdated, incomplete, or not being actively maintained. This is rebuilt as a live governance artifact — not a document that gets filed and forgotten.

2.4

Enforce Proper Agile Cadence and SDLC Discipline

Review and reprioritize the backlog. If a proper Agile delivery process has not been followed, the following sequence must be completed before any story enters a sprint:

Required SDLC Sequence
Gather Requirements → Understand Business Need → User Story Grooming → Acceptance Criteria Definition → Analysis → Solution Design → Dev Sandbox → QA Sandbox → UAT in Stage Sandbox → Production
2.5

Sprint Planning for Release-Ready Stories Only

Only user stories that have completed the full sequence through Analysis (Definition of Done — requirements gathered, business need understood, story groomed, acceptance criteria defined and signed off) are eligible for sprint planning. Stories that have not cleared this bar stay in the backlog until they do.

⚠

AI Governance Note

If AI tools were used during discovery or requirements gathering without structured governance, many of the stories now in the backlog may contain hallucinated logic, assumed business rules, or requirements inferred from partial inputs rather than validated against the business. The sprint planning gate above must include review for AI-generated content — not just completeness of the Definition of Done.

See our AI Governance framework  ↗

2.6

Establish Center of Excellence and Release Governance

Set up — or re-establish — a Center of Excellence (CoE) or steering committee with the authority to review all upcoming changes, prioritize them by business value, and enforce Release Governance standards. This is the structural control that prevents scope drift, uncontrolled customization, and ad-hoc production changes from recurring.


NEW SERVICE  ·  Relevant to This Engagement

AI Governance for Salesforce Delivery

When AI is embedded into a delivery that’s now in remediation — generating user stories that were never properly groomed, producing requirements that were accepted without validation, drafting solution designs that were never pressure-tested against the business — the root cause isn’t just process drift. It’s ungoverned AI output that scaled the gaps faster than manual work ever could.

AI doesn’t correct the gaps in your requirements. It scales them — deeper and further into the build than traditional delivery failures typically reach. For Salesforce AEs, SEs, and CSMs: this is already happening in the accounts you carry.

119%
Agentforce agent growth H1 2025 — governance determines who captures this responsibly
93%
of IT leaders plan to deploy autonomous AI agents within two years (Salesforce 2025 Report)
Read: AI Is Already Inside Your Salesforce Delivery. Governance Cannot Wait.  ↗
3
Phase Three

Remediation & Optimization

With stabilization in place, the team addresses the underlying technical and functional issues that caused delivery to fail. This phase works closely with the SI delivery team and is scoped to what the specific engagement actually requires — not every item will apply to every account.

ⓘ  Applicability note: The items below represent the range of remediation work that may be needed. Each is assessed individually based on the root cause findings from Phase 1. Not all will apply to every engagement.
3.1

Data Cleanup and Standardization

Remediate data quality issues — remove duplicates, audit completeness, enforce consistent data entry rules, and restore user trust in the data. Users who don’t trust the data will not trust the system. This is foundational to adoption.

3.2

Technical Debt Remediation

Identify, document, and refactor problematic implementations — excessive or conflicting validation rules, broken Process Builder automations, and any other “quick-and-dirty” solutions that have accumulated. Convert applicable automations to Flow in alignment with Salesforce’s current platform direction and best practices.

3.3

Integration Re-Architecture

Simplify or rebuild failed or unreliable integrations with third-party systems (ERP, Marketing, external data sources) to ensure consistent, trustworthy data flow. Broken integrations compound data quality issues and undermine user confidence faster than almost any other failure mode.

3.4

User Experience Streamlining

Reconfigure page layouts, record pages, and UI elements to match the actual day-to-day workflows of the users who will use the system. Solutions designed without this alignment — however technically correct — create friction that prevents adoption. Good UX in Salesforce is functional alignment, not aesthetic design.


4
Phase Four

Testing & Release Management

Nothing moves to production without validation. This phase covers the full testing and release process — with end users involved throughout, not brought in at the last moment.

4.1

User Acceptance Testing (UAT)

Involve end users in thorough UAT that validates fixes and enhancements against real-world scenarios — not synthetic test cases written by the delivery team. UAT is where user trust gets rebuilt through demonstrated, verifiable system behavior. The testing strategy is developed and managed as a structured process, not a free-form walkthrough.

4.2

Governed Go-Live

Go-live is a milestone the team should approach with confidence — not brace for. The deployment plan, release readiness criteria, rollback procedures, and stakeholder communication are all defined and confirmed before any production deployment occurs. Go-live is a decision, not a deadline.

4.3

Regression Testing

Validate that previously functioning areas of the org have not been affected by remediation changes. In complex orgs, regression testing is not optional — an undetected regression surfaced post-go-live compounds the very trust problems the remediation is trying to resolve.

4.4

Hypercare

An intensified support period immediately following go-live — with elevated responsiveness, active issue monitoring, and rapid resolution protocols. The hypercare window is defined before go-live, not invented reactively when problems emerge.


5
Phase Five

Change Management, Training & Adoption

A technically remediated system that users don’t trust, understand, or engage with is not a successful recovery. This phase addresses the people side of the turnaround — the part most remediation efforts either skip entirely or treat as a final afterthought.

5.1

User Community Communication

Communicate relevant status updates and changes to the user community in a way that is appropriate for the audience and the moment. In a recovery context, transparency is not just good practice — it is how user trust gets rebuilt. Users who have been left in the dark during a struggling implementation do not give second chances easily.

5.2

Train the Trainer and Targeted Training

Conduct tailored training sessions focused on what has changed, why it was changed, and how it reflects how users actually work. Train the Trainer is prioritized to build internal enablement capacity — so that adoption support does not remain dependent on the consulting engagement. Training is treated as an ongoing practice, not a one-time handoff event.


6
Phase Six

Post-Remediation Support

Remediation doesn’t end at go-live. The post-recovery period is when the structural improvements are validated, the team transitions to a sustainable operating model, and the account health data confirms the engagement is genuinely back on track.

6.1

Support Model Definition

Define a clear post-go-live support structure — whether that is an internal admin, a partner-led model, or a hybrid arrangement — before the engagement closes. This includes escalation paths, SLA expectations, and a backlog refinement process for ongoing enhancement requests. Gaps in the support model are where hard-won recovery gains quietly erode.

6.2

Real-Time System Health Monitoring

Use monitoring to track system performance, data integrity, integration reliability, and adoption rates in the period following remediation. The goal is not to manage indefinitely from the outside — it is to confirm that the system is behaving as expected and that any emerging issues are caught early rather than allowed to compound.

6.3

KPI Reporting Against Recovery Milestones

Track and report against the KPI baselines and targets established in Phase 1.5. This provides the evidence base for confirming that the remediation has delivered its intended outcomes — across Org Health, Technical Debt alignment, Delivery Execution, Customer CSAT, Adoption, and Release Health. Recovery is not declared until the numbers support it.

Have an Account in Trouble?

We Assess Before We Scope.
Always.

Tell us about the engagement. We will tell you honestly what recovery looks like, whether CRM & Data Angels.AI is the right fit, and what involvement would actually require.

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