Data & Systems Assessment
Purpose
This is the system of record for the sprint itself.
The Data & Systems Assessment is a living inventory of the organization's technology landscape. Anytime a system is mentioned in an interview, it is captured here.
This artifact underpins:
- Feasibility assessment
- Opportunity scoring
- Roadmap sequencing
- Credibility with IT and leadership
If this is incomplete, the sprint degrades quickly.
When This Happens
This is not a single step.
| Phase | Interaction |
|---|---|
| Pre-kickoff | Seeded via intake |
| Interviews | Continuously updated |
| Synthesis | Referenced constantly |
| Readout | Summarized, not replaced |
The inventory evolves as understanding improves.
What Gets Captured
Whenever a system comes up, record it.
| Category | Description |
|---|---|
| System name | ERP, CRM, DW, tool, spreadsheet |
| Primary function | What it's actually used for |
| Owning team | IT, Finance, Ops, etc |
| Downstream users | Who depends on it |
| Inputs | Source systems, manual entry |
| Outputs | Reports, files, APIs |
| Integration method | API, CDC, file, manual |
| Refresh cadence | Real-time, hourly, daily |
| Source of truth role | SoR, SoT, or neither |
| Known issues | Data quality, latency, trust |
| Constraints | Security, compliance, policy |
| AI relevance | Enables or blocks use cases |
If a field is unknown, leave it blank. Unknowns are signal.
Canonical System Inventory Table
This table is maintained centrally.
| System / Source | Data Type | Quality (1–5) | Integration Level | Owner | Notes |
|---|---|---|---|---|---|
| ERP A | Orders, GL, AP/AR | 4 | High | IT | Primary SoR for finance |
| Data Warehouse | Consolidated analytics | 3 | High | IT | Read-only, refreshed daily |
| CRM | Customers, pipeline | 2 | Low | Sales | Manual entry, duplicates |
| Excel (various) | Forecasts, adjustments | 1 | None | Finance | Shadow systems |
Quality: 1 = poor, 5 = excellent Integration: Low / Med / High
This table is the backbone of feasibility analysis.
Data Flow Mapping (High-Level)
Where helpful, capture flows visually or descriptively:
Source > Ingest > Transform > Store > Analyze > Act
Examples:
- ERP > CDC > DW > BI
- Portal > API > ERP
- Spreadsheet > Manual upload > BI
Precision matters more than polish.
Integration & Friction Signals
Flag especially:
| Signal | Why It Matters |
|---|---|
| Manual exports | Automation candidates |
| Multiple SoRs | Trust issues |
| Write-back restrictions | Limits AI actions |
| Long refresh cycles | Decision latency |
| Shadow spreadsheets | Governance gaps |
These often become top roadmap items.
Security & Governance Layer
Capture:
- What data can leave the environment
- Approved cloud zones
- Access control patterns
- Bot / service account policies
- Audit and logging requirements
This prevents unsafe recommendations later.
How This Feeds the Sprint
| Downstream Step | Dependency |
|---|---|
| Opportunity framing | What's possible |
| Scoring | Effort and risk |
| Deduplication | Shared enablers |
| Roadmap | Sequencing logic |
| Exec readout | Credibility with IT |
This artifact often becomes the most referenced appendix slide.
Maintenance Rules
- One shared owner
- Updated in real time
- No private copies
- Assumptions explicitly labeled
- Conflicts noted, not resolved here
This is a map of reality.
Next step is Opportunity Identification, where this landscape constrains and enables what gets proposed.