Data Catalog · FAIR Maturity · Pharma R&D

A 90-Day Maturity Assessment for
Pharmaceutical R&D Data Catalogs

A practical playbook for leaders who need a defensible baseline, one shipped quick win, and a 12-month roadmap before the first quarterly review.

May 2026 ~24 min read Ali Shahmohammadi, Ph.D. 13 references
Read Article FAIR Maturity Indicators
90
Days to baseline, quick win, and roadmap
30
Days for inventory and triage
30
Days for FAIR maturity measurement
30
Days for roadmap and shipped quick win
Table of Contents
  1. 01Why 90 Days Works
  2. 02Methodology Spine: FAIR Maturity Indicators
  3. 03The 90-Day Shape
  4. 04Days 1–30: Inventory and Triage
  5. 05Days 31–60: Measure Maturity
  6. 06Days 61–90: Roadmap and Quick Win
  7. 07Anti-Patterns to Avoid
  8. 08After Day 90
  9. 09Closing Thought
01 — Framing

Why "First 90 Days" Beats "Boil the Ocean"

The organization plans and funds on quarterly cadence, so your assessment must deliver on quarterly cadence.

A comprehensive enterprise discovery can always consume nine months. Most pharma R&D sponsors cannot wait nine months to make portfolio decisions. The 90-day frame turns assessment into decision support instead of open-ended research.

The core signal is not speed for its own sake. The signal is the ability to translate limited leadership attention into defendable evidence and fundable next actions.

02 — Method

Methodology: FAIR Maturity as the Spine

Use existing community-governed frameworks instead of inventing custom rubrics.

Measurement

FAIR Maturity Indicators

Automatable, reproducible checks move maturity discussion from opinion to evidence.

Portfolio Scoring

Pistoia FAIR Maturity Matrix

Pharma-tested rollup instrument for asset and portfolio-level maturity views.

Execution Recipes

FAIR Cookbook

Operational guidance to convert gap findings into concrete treatments.

Rule: every maturity score should trace to a test result or a structured steward interview, not a subjective rating workshop.

03 — Shape

The 90-Day Shape

Three 30-day phases, each with one sponsor-facing deliverable and one explicit hand-off.

Days 1–30

Inventory & Triage

Portfolio heat map, stewardship map, and 10–20% priority subset.

Days 31–60

Measure Maturity

FAIR scorecard by asset and dimension, plus ranked gap register.

Days 61–90

Roadmap & Quick Win

12-month dependency-sequenced roadmap and one shipped treatment.

04 — Phase 1

Days 1–30: Inventory and Triage

Build a working register across discovery, translational, clinical, regulatory, safety, and CMC domains.

Capture minimum metadata for each asset: owner, system, primary use, downstream consumers, and regulatory binding. Then map the decision reality: system owner, data owner, and funder are usually different people.

Deliver a heat map that surfaces trade-offs. The heat map is the first sponsor artifact and determines which assets enter Phase 2 measurement scope.

05 — Phase 2

Days 31–60: Measure Maturity

Run automation where possible, then add structured steward interviews for what automation cannot capture.

Automation

FAIR Evaluator pass

Generate objective maturity signals for resolvable assets and identify weakest sub-principles at scale.

Human Signal

Structured steward interviews

Capture license clarity, provenance detail, and community-standard conformance gaps in a fixed template.

Regulatory Overlay

Binding-aware scoring

Layer CDISC, IDMP, MedDRA, RxNorm, UNII and GxP relevance to prioritize fundable treatments.

Output

Scorecard + Gap Register

Per-asset scores, per-dimension portfolio metrics, and ranked remediation backlog with cost bands.

06 — Phase 3

Days 61–90: Roadmap and Quick Win

Sequence by dependency, not by largest score gap, and ship one treatment before Day 90 closes.

Start with enablers: persistent identifiers, controlled vocabularies, and provenance substrate. Then scale catalog ingestion and conformance treatment. This order compounds value and avoids local optimizations that do not travel.

Quick wins should be treatment artifacts, not dashboards. A promoted priority asset, remediated ontology criticals, or a live identifier resolver all qualify.

Deliverable standard: by Day 90, the sponsor should have a scorecard, gap register, roadmap, quick-win artifact, and governance recommendation.

07 — Risks

Anti-Patterns That Sink 90-Day Assessments

Most failures come from scope and operating mistakes, not from framework choice.

Boil-the-ocean scope

Trying to score every asset before shipping anything guarantees a Day-90 miss.

Tool-first sequencing

Selecting catalog tooling before gap definition creates licenses without content strategy.

Dashboard theater

Visualizing maturity without shipping treatment does not improve maturity.

08 — Continuation

After Day 90: How the Architecture Sequence Begins

The 90-day assessment is the input to product mastering, semantic layer rollout, agentic curation, and ISO/IEC 23894 operationalization.

The maturity baseline determines sequencing across your next architecture phases. What changes after Day 90 is not the need for assessment; it is the shift from diagnosis to compounding treatment.

Closing Thought

Diagnose in 30. Measure in 30. Ship in 30.

The value of a 90-day playbook is discipline: every claim traceable, every score reproducible, every roadmap line linked to evidence, and one concrete treatment shipped before the first quarterly review.

Diagnose in 30. Measure in 30. Ship in 30. Then the architecture.

Back to Portfolio Related: ISO/IEC 23894 in Pharma R&D Related: Agentic Data Governance
References

13 References

Core sources include FAIR maturity frameworks, ontology governance, pharma quality risk guidance, and catalog operating standards.

  1. 1Watkins, M. The First 90 Days. HBR Press. hbr.org
  2. 2Wilkinson et al. FAIR maturity framework (2019). nature.com
  3. 3FAIR Cookbook resource. faircookbook.elixir-europe.org
  4. 4Pistoia FAIR Maturity Matrix. pistoiaalliance.github.io
  5. 5OBO Foundry principles and operations. obofoundry.org
  6. 6OOPS ontology pitfall scanner. oops.linkeddata.es
  7. 7FAIR Guiding Principles (2016). doi.org
  8. 8CDISC foundational standards. cdisc.org
  9. 9W3C PROV-O and OpenLineage resources. w3.org
  10. 10ICH Q9(R1) and EMA scientific guideline. ema.europa.eu
  11. 11FDA draft guidance on AI in regulatory decisions (Jan 2025). fda.gov
  12. 12ISPE GAMP 5 (2nd ed.). ispe.org
  13. 13EDM Council DCAM framework. edmcouncil.org