What this part delivers, and why
Assess answers one question: given how this team works today, what should they fix first — and what are they not yet ready for? We score the operation, find the gaps, translate it for the boardroom, and hand the result straight into the build. Everything here is designed so a consultant can run it without reinventing the approach each time.
- 1 · Kickoff & scope — agree boundaries, access, stakeholders and success.
- 2 · Stakeholder interviews — learn how content really gets made and where it hurts.
- 3 · Content audit & inventory — quantify what exists and its health (ROT, structure, metadata).
- 4 · Maturity scoring — score the operation 1–5 across five criteria, with evidence.
- 5 · Gap & AI-readiness analysis — turn the score into specific, prioritised gaps.
- 6 · Findings & readout — translate for execs, set the entry point, draft the business case.
- 7 · Decision & handoff — secure the go-ahead and hand into Phase 2 · Build.
Kickoff & scope
Agree what's in and out of scope, secure data access, confirm the stakeholders, and define what a successful diagnosis looks like — so the next three weeks don't drift.
- Intros, goals and the "why now" (10m)
- Scope boundaries — which content domains, teams, sites, regions are in/out (25m)
- Success criteria — what the readout must answer for the sponsor (15m)
- Data & access needed — CMS exports, analytics, existing strategy docs (20m)
- Stakeholder map & interview shortlist (15m)
- Schedule, cadence and next steps (5m)
- Org chart & content team structure
- List of content properties / channels
- Any existing strategy or audit docs
- Scope statement (1 page)
- Stakeholder map + interview schedule
- Data-access checklist
The scope everyone agrees to in the room is always about double what the budget covers. Write it all down, then draw the line — and tell them where you've drawn it. What you cut becomes the obvious shape of Phase 2.
Stakeholder interviews
Understand how content actually gets made — not the org chart version. Surface pain points, tooling reality, governance gaps, and where AI is already creeping in unmanaged.
- Content / marketing leader (strategy & priorities)
- 2–3 content creators / editors (the real workflow)
- Ops / project manager (intake, workflow, bottlenecks)
- Martech / web / dev (the stack and what it can do)
- One downstream consumer — sales, product, or support
- Interview guide (template below)
- Stakeholder map from Step 1
- Interview notes
- Themes synthesis (pains, patterns, quotes)
Content audit & inventory
Quantify what exists and how healthy it is. A full inventory where feasible, plus a deep-dive on a representative sample to judge structure, metadata and reuse.
- Pull an inventory — CMS export or crawl; capture URL, type, owner, last-updated, traffic
- ROT classification — flag Redundant, Outdated, Trivial content for removal/consolidation
- Structure & metadata assessment — is content modelled, tagged, consistent?
- Reuse check — how much is copy-pasted vs genuinely single-sourced?
- Sample deep-dive — 15–25 representative items scored in detail
- CMS export / crawl access
- Analytics (traffic, engagement)
- Content inventory sheet
- ROT summary (% of estate)
- Structure & metadata findings
The content lead will swear the taxonomy is fine. Pull 20 pages at random and check the tags yourself — it usually isn't, and that gap is half your findings.
Don't promise a 100% inventory of a 50,000-page estate. Sample it. A defensible sample you actually finish beats a complete spreadsheet that stalls at row 800.
Illustrative ranges from a typical estate — animates into view as evidence for the findings.
Maturity scoring workshop
Score the operation 1–5 across five criteria, with evidence from the interviews and audit — not opinion. Capture the rationale and agree a realistic target level. (Uses the maturity scorecard in the Templates section.)
- Recap method & the five criteria (10m)
- Score each criterion collaboratively, citing evidence (75m)
- Agree current level + realistic 12-month target per criterion (25m)
- Translate the headline to the exec posture — Curious / Competent / Confident (10m)
- Interview themes (Step 2)
- Audit findings (Step 3)
- Maturity scorecard template
- Completed scorecard (current vs target)
- Scoring rationale & evidence
Score the room, then quietly score it again on your own a day later. Where your private number and the workshop number disagree is usually where the politics are — worth a private word with the sponsor before the readout.
Click a level (1–5) for each criterion. The radar and headline update live — a quick way to rehearse the workshop output.
Gap & AI-readiness analysis
Turn scores and audit into the specific, prioritised gaps — and the concrete reasons AI won't work yet. This is what makes the recommendation defensible.
- Map the gap per criterion (current → target) and what closing it requires
- Quantify content debt — ROT %, duplication, unstructured volume
- Run the AI-readiness checklist (structured? metadata? schema? machine-accessible?)
- Prioritise gaps by impact × effort
- Completed scorecard
- Audit + ROT data
- Gap analysis matrix (prioritised)
- AI-readiness scorecard
Example profile. The widest bars are the priority gaps — biggest distance to close, ranked next by impact × effort.
Findings & readout
Package the diagnosis into a clear story for the sponsor: where you are, the gap, the prioritised plan, and the entry point into the pipeline and roadmap — with an outline business case.
- Build the findings deck (current state → gaps → recommendation)
- Map the score to the pipeline entry point and roadmap phase (see hub's diagnosis-to-plan table)
- Draft the business case — cost of inaction, expected outcomes, effort
- Run the readout session; capture reactions and adjust
- Scorecard, gap matrix, AI-readiness
- Findings & recommendations readout
- Prioritised entry point
- Outline business case
Never drop a maturity score of "2" on a proud team cold. Lead with what's genuinely working, then the gap. A score that lands as an insult gets argued with, not acted on.
Decision & handoff
Convert the readout into a decision and a scoped next phase, so momentum carries straight into Build.
- Confirm go / no-go and sponsor commitment
- Agree the scope & budget of Phase 2 · Build
- Hand over all artifacts; book the Build kickoff
- Signed-off readout
- Approved recommendations
- Phase 2 scope & kickoff booked
RACI & effort summary
Who does what across the part. R Responsible · A Accountable · C Consulted · I Informed.
| Activity | Sponsor | Content lead | Martech / Ops | Lead consultant | Analyst |
|---|---|---|---|---|---|
| Kickoff & scope | A | C | C | R | I |
| Interviews | I | C | C | R | C |
| Content audit | I | C | C | A | R |
| Maturity scoring | C | C | C | R | C |
| Gap analysis | I | I | I | R | R |
| Readout | A | C | I | R | C |
| Decision & handoff | A | C | I | R | I |
| Week | Focus | Consultant days |
|---|---|---|
| Week 1 | Kickoff, scope, start interviews | ~3 |
| Week 2 | Finish interviews, content audit | ~4 |
| Week 3 | Maturity scoring, gap & AI-readiness | ~3.5 |
| Week 4 | Findings, readout, decision | ~3 |
The artifacts you use and leave behind
Three core templates are spelled out below; the full set produced in this part is indexed at the end.
Content Ops Maturity — score 1–5 per criterion
| Criterion | Level 1 · Chaotic | Level 3 · Scaling | Level 5 · Thriving | Score |
|---|---|---|---|---|
| Content vision | No shared strategy; ad-hoc requests | Strategy exists, loosely followed | Clear, governed, audience-led vision | __/5 |
| Model & taxonomy | Freeform pages; no model | Some structure & tags, inconsistent | Formal content model + governed taxonomy | __/5 |
| Governance | None; everyone does their own thing | Guidelines exist, patchy enforcement | Clear policy, standards, decision rights | __/5 |
| Measurement | Output only (how much we made) | Some performance tracking | System measured; tied to outcomes | __/5 |
| Reuse | Copy-paste everywhere | Occasional reuse, manual | Single-source, structured reuse | __/5 |
Average the five for the headline level. Capture evidence beside each score. Repeat the exercise each quarter to track movement.
45-minute interview — question set
- Walk me through how a typical piece of content gets made, start to finish.
- Where does it slow down or break? What's the most frustrating part?
- How do you decide what to make, and who signs it off?
- What tools do you use? What do they do well / badly?
- How is content tagged, organised and reused (if at all)?
- How do you know if content worked? What do you measure?
- Where is AI already being used — officially or unofficially?
- If you could fix one thing about how content works here, what would it be?
Can this content actually feed AI?
Tick each gate you can honestly clear today. The tally below gives a live readiness verdict.
- Content is broken into structured, labelled fields — not freeform blobs
- A consistent taxonomy & metadata are applied across the estate
- Schema / semantic markup is in place on key content
- Content is accessible as data via API (or a headless layer)
- Content is current — a clear review/freshness cadence exists
- Brand & editorial rules are documented (ideally machine-readable)
- Governance covers AI use — disclosure, approval, provenance
- Source content is accurate enough to ground AI without amplifying errors
Entry & exit gates
The quality bar that says this part is genuinely ready to start, and genuinely finished.
- Executive sponsor named and bought in
- Scope agreed and access to content/analytics granted
- 5–8 interviewees identified and booked
- Maturity scored 1–5 with evidence, current vs target
- Prioritised gaps + AI-readiness documented
- Entry point into pipeline & roadmap agreed
- Readout delivered; go / no-go decision made