Comprehensive Problem Inventory

The Systematic Catalog That Drives Everything Else

Why This Is Your Most Critical Deliverable

The brutal truth: Everything in Phase 2-4 depends on the quality of your problem inventory.

A mediocre problem inventory leads to:

  • ❌ Vague priorities that don’t drive decisions
  • ❌ Solutions that miss the actual pain points
  • ❌ Inability to measure success
  • ❌ Stakeholder disagreement about what matters
  • ❌ Implementation that solves symptoms, not root causes
  • ❌ Wasted budget on low-impact projects

A comprehensive problem inventory creates:

  • ✅ Shared language across departments
  • ✅ Data-driven prioritization
  • ✅ Clear success metrics
  • ✅ Organizational alignment
  • ✅ Defensible resource allocation
  • ✅ Foundation for ROI calculation

Your problem inventory isn’t documentation—it’s the strategic asset that determines whether this entire engagement succeeds or fails.

What “Comprehensive” Actually Means

A comprehensive problem inventory is:

Complete: Captures all significant operational problems surfaced through assessment and workshops, not just the ones you like or can easily solve

Structured: Organized in a way that reveals patterns, relationships, and priorities

Quantified: Every problem has data attached—frequency, scope, time cost, business impact

Traced: Root causes identified, not just symptoms

Contextualized: Shows how problems affect different stakeholders and interact with each other

Actionable: Specific enough that solutions can be designed and evaluated

Validated: Verified by people who experience the problems daily

Living: Updated as new information emerges

The Problem Inventory Architecture

Your inventory needs multiple layers and views. Think of it as a database, not a list.

Layer 1: The Master Problem Registry

This is your source of truth. Every problem gets a unique entry.

Entry Template:

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PROBLEM ID: P-001
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PROBLEM STATEMENT:
Monthly financial reporting requires 16 hours of manual data compilation 
across three disconnected systems, causing delayed visibility and 
occasional errors in executive dashboards.

CATEGORY: Data Fragmentation & Reporting
TAGS: #finance #reporting #data-quality #manual-process #cross-system

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DISCOVERY SOURCE
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Identified by: Finance Director (interview), 2 Finance Analysts (interviews), 
Operations Manager (interview), mentioned in Session 1 by 4 participants

First surfaced: Preliminary Assessment, Week 1
Validated: Workshop Session 1 & 2

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CURRENT STATE DESCRIPTION
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Detailed Process:
1. Friday 8am: Finance analyst exports sales data from Salesforce (30 min)
2. Friday 9am: Exports order fulfillment data from ERP system (45 min)
3. Friday 10am: Requests manual spreadsheet from warehouse manager (email, 
   response time varies 2-24 hours)
4. Friday afternoon: Manually reconciles three data sources in Excel (3 hours)
5. Identifies discrepancies, emails departments for clarification (1-2 hours)
6. Monday morning: Receives clarifications, makes corrections (1 hour)
7. Monday afternoon: Creates charts and summary for executive team (2 hours)
8. Tuesday: Executive team reviews, often requests additional cuts (1-3 hours 
   of rework)

Total elapsed time: 5 business days (Friday morning → Tuesday afternoon)
Total labor time: 16 hours (2 FTE days)

Current Workarounds:
- Warehouse manager keeps shadow spreadsheet because ERP export is unreliable
- Finance team maintains "translation dictionary" of product codes that differ 
  between systems
- Analysts start process Thursday afternoon when possible to beat deadline
- Executive team has learned to wait until Wednesday for "real" numbers

Pain Points:
- Time-consuming manual work every month
- High error rate due to manual transcription
- Delayed financial visibility (5 days old by time executives see it)
- Analyst frustration and burnout (described as "soul-crushing")
- Warehouse manager interrupt every Friday morning
- Inability to produce ad-hoc reports quickly

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FREQUENCY & SCOPE
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Frequency: Monthly (12 times per year)
Affected Departments: Finance (primary), Operations, Warehouse, Executive team
Affected Roles:
- 2 Finance Analysts (primary workload)
- 1 Warehouse Manager (data provider)
- 1 Operations Manager (clarification provider)
- 5-person Executive Team (delayed/questionable data consumers)

Geographic Scope: Company-wide (all locations consolidated)
When it happens: Last Friday of month → First Wednesday of following month

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QUANTIFIED IMPACT
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Time Cost:
- Finance Analysts: 16 hours/month × 12 months = 192 hours/year
- Warehouse Manager: 1 hour/month × 12 months = 12 hours/year  
- Operations Manager: 1 hour/month × 12 months = 12 hours/year
- Executive rework/waiting: ~2 hours/month × 12 months = 24 hours/year
- TOTAL: 240 hours/year

Labor Cost (assuming loaded rates):
- Analysts: 192 hrs × $65/hr = $12,480
- Warehouse Mgr: 12 hrs × $75/hr = $900
- Operations Mgr: 12 hrs × $80/hr = $960
- Executives: 24 hrs × $150/hr = $3,600
- TOTAL: $17,940/year in direct labor cost

Error Rate & Rework:
- Errors occur in ~30% of monthly reports (3.6 reports/year)
- Average rework per error: 4 hours
- Annual rework cost: 3.6 × 4 hrs × $65/hr = $936

Opportunity Cost:
- Analysts could be doing higher-value financial analysis instead
- 192 hours = ~1 month of productive analyst work per year lost
- Estimated opportunity cost: $25,000/year in foregone insights

Business Impact:
- Delayed financial visibility (executives making decisions on 5-day-old data)
- Inability to respond quickly to board/investor requests for data
- Analyst burnout (cited as reason for last analyst departure)
- Executive team has low confidence in data accuracy

Compliance/Risk Impact:
- Medium risk: Errors in board reporting could affect credibility
- Low risk: No direct regulatory implications

Customer Impact:
- Indirect: Delayed financial visibility may slow strategic decisions

TOTAL QUANTIFIED ANNUAL COST: ~$44,000
(Direct labor + rework + opportunity cost, excluding strategic impact)

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ROOT CAUSE ANALYSIS
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Root Cause Category: Data Fragmentation + System Integration Gap

Contributing Factors:

TECHNOLOGY:
- Salesforce and ERP were implemented separately, no integration built
- Warehouse system is legacy software with limited export capabilities
- No centralized data warehouse or BI tool
- Excel is the only common denominator between systems

PROCESS:
- No standardized product coding across systems
- Warehouse manager became single point of failure for one data source
- No validation rules to catch errors early
- Process designed around technology limitations rather than business needs

DATA:
- Product codes differ between Salesforce (sales names) and ERP (SKU codes)
- Warehouse tracks by bin location, not by product hierarchy
- Missing data fields in legacy warehouse system
- No data quality checks at point of entry

ORGANIZATIONAL:
- Different systems owned by different departments (silos)
- No cross-functional governance of data architecture
- Historical underinvestment in data infrastructure
- "If it ain't broke don't fix it" mentality until analyst turnover forced attention

PEOPLE:
- Only 2 analysts know the full reconciliation process (knowledge concentration)
- New analysts take 3+ months to learn all the workarounds
- Warehouse manager resistant to system changes (near retirement)

Primary Root Cause:
Systems were implemented independently without integration strategy, creating 
data fragmentation that requires ongoing manual reconciliation.

Secondary Root Cause:
Lack of standardized data governance allowed different naming conventions and 
data structures to proliferate.

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CROSS-FUNCTIONAL DEPENDENCIES
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Upstream Dependencies (what must happen first):
- Sales team enters orders in Salesforce
- Operations processes orders in ERP
- Warehouse fulfills orders and updates bin locations

Downstream Dependencies (who is affected):
- Finance team → delayed close process
- Executive team → delayed strategic decisions
- Board/Investors → delayed financial reporting
- Department heads → delayed budget variance analysis

Related Problems:
- P-005: Sales forecasting requires similar manual data compilation
- P-012: Customer success team can't see real-time order status
- P-018: Operations can't easily reconcile inventory between systems
- P-023: IT team spends significant time on manual data export requests

Cascade Effect:
This problem contributes to or exacerbates 6 other identified problems across 
4 departments, suggesting it's a systemic leverage point.

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STAKEHOLDER PERSPECTIVES
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Finance Analysts:
"This is the worst part of my job. It's tedious, error-prone, and feels like 
a waste of my skills. I didn't get a finance degree to copy-paste data 
between spreadsheets."
Priority: CRITICAL (directly affects them weekly)

Finance Director:
"We've lived with this for years, but it's becoming unsustainable. We lost 
our best analyst partly because of burnout from this process. And I don't 
trust the numbers when we rush."
Priority: HIGH (team morale + data quality concern)

Warehouse Manager:
"I don't mind sending the spreadsheet, but I wish they'd just give me direct 
access to pull what they need instead of emailing me every month."
Priority: LOW (minor interruption)

CFO (Executive Sponsor):
"The 5-day lag is problematic. In fast-moving situations, I'm making decisions 
on stale data. And when board members ask follow-up questions, we can't pivot 
quickly."
Priority: HIGH (strategic decision-making impact)

CTO:
"We've known about this integration gap for years. It's a budget priority 
problem—we keep deferring it for sexier projects."
Priority: MEDIUM (technical debt concern)

Operations Manager:
"I get pulled into this every month to explain discrepancies. It's disruptive 
but not my biggest problem."
Priority: LOW (occasional interruption)

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WORKAROUND ANALYSIS
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Current Workarounds (and what they reveal):

1. "Translation dictionary" of product codes
   → Reveals: No data governance, systems poorly integrated
   → Cost: Maintenance overhead, error-prone lookups

2. Starting process Thursday instead of Friday
   → Reveals: Deadline pressure, no slack in system
   → Cost: Encroaches on other work

3. Warehouse manager's shadow spreadsheet
   → Reveals: ERP export is unreliable or inadequate
   → Cost: Duplicate data entry, version control issues

4. Executive team waits until Wednesday for "real" numbers
   → Reveals: Trust issues with preliminary data
   → Cost: Delayed decision-making becomes normalized

5. Analysts maintain personal notes on edge cases
   → Reveals: Tribal knowledge, not documented process
   → Cost: Onboarding difficulty, single points of failure

Workaround Investment:
Cumulative time spent maintaining workarounds: ~20 hours/year
These workarounds have become embedded in organizational culture, making them 
harder to eliminate than the original problem.

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SOLUTION CONSIDERATIONS
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Potential Solution Categories:

1. SYSTEM INTEGRATION (High impact, high effort)
   - Build direct integration between Salesforce and ERP
   - Implement data warehouse with automated ETL pipelines
   - Replace legacy warehouse system with modern WMS that integrates
   Feasibility: HIGH (technology exists)
   Cost estimate: $50K-150K depending on approach
   Timeline: 3-6 months

2. PROCESS REDESIGN (Medium impact, low effort)
   - Standardize product coding across systems
   - Create validation rules at point of entry
   - Shift from monthly to weekly micro-reports (catch errors earlier)
   Feasibility: HIGH
   Cost estimate: $5K-10K (mostly time)
   Timeline: 1-2 months

3. AUTOMATION/AI (Medium-high impact, medium effort)
   - RPA bot to automate data extraction and reconciliation
   - AI-powered anomaly detection to flag discrepancies
   - Automated report generation with natural language summaries
   Feasibility: MEDIUM-HIGH (data quality issues may complicate)
   Cost estimate: $25K-50K
   Timeline: 2-3 months

4. TOOL ACQUISITION (Medium impact, medium effort)
   - Implement BI tool (Tableau, Power BI) with connectors to all systems
   - Buy pre-built integration middleware
   Feasibility: HIGH
   Cost estimate: $30K-60K (software + implementation)
   Timeline: 2-4 months

Recommended Approach:
Hybrid solution: Quick wins with process redesign (#2) while planning larger 
integration project (#1), with interim automation (#3) to reduce manual burden 
during implementation.

Prerequisites:
- Data governance framework (who owns standardization?)
- Budget approval ($80K-100K estimated total)
- IT resource allocation (integration work)
- Change management (new processes/tools)

Expected ROI:
- Time savings: 200+ hours/year (current 240 hrs → 20-30 hrs)
- Cost savings: $35K+/year in direct labor
- Quality improvements: Error rate reduction from 30% → <5%
- Strategic value: Real-time reporting, ad-hoc analysis capability
- Payback period: ~2-3 years depending on solution approach

AI Applicability Assessment: MEDIUM-HIGH
- Data extraction/transformation: Good AI fit
- Anomaly detection: Good AI fit  
- Report generation: Good AI fit
- Root cause (integration gap): Not AI problem, need actual integration
- Recommendation: Use AI for interim automation, but solve with integration

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PRIORITY ASSESSMENT
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Impact Score: 19/25
- Business Impact (5/5): Significant cost, quality issues, strategic delays
- Frequency (4/5): Monthly recurrence
- Scope (4/5): Affects 4 departments, executive visibility
- Cost (3/5): $44K/year quantified (mid-range)
- Risk (3/5): Moderate (analyst burnout, data quality, not critical systems)

Effort Score: 12/15 (inverse scoring: lower = harder)
- Technical Complexity (2/5): Requires integration work, multiple systems
- Organizational Complexity (3/5): Cross-departmental, some political challenges
- Time to Implement (2/5): 3-6 months for full solution
- Resource Requirements (2/5): Significant IT + budget resources
- Change Management (3/5): Process changes but clear benefits

Strategic Importance: HIGH
- Affects executive decision-making
- Analyst retention issue
- Foundation for other data-driven improvements
- Cited by CFO (executive sponsor) as priority

OVERALL PRIORITY RANKING: #2 of 47 identified problems
(High impact, moderate effort, strategic importance)

Recommendation: Include in Phase 1 implementation (Q1-Q2 2026)

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METADATA
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Created: [Date]
Last Updated: [Date]
Status: Validated
Validation Date: Session 2 (Workshop)
Owner: Finance Director
Priority: P1 (Top tier)

Related Documentation:
- Interview transcript: Finance Director (pages 3-7)
- Workshop Session 1 notes (problem cluster "Data Fragmentation")
- Workshop Session 2 quantification worksheet
- Sample monthly report with annotations
- Process flow diagram (attached)
- Cost calculation spreadsheet (attached)

Next Steps:
- [ ] Solution design workshop (Session 3)
- [ ] Vendor research for integration tools
- [ ] IT feasibility assessment
- [ ] Preliminary budget request preparation

Notes:
This problem has been referenced repeatedly across multiple interviews and 
workshop sessions, suggesting it's a genuine pain point, not just one person's 
complaint. The quantification is based on direct observation and time tracking 
over 2 months. Finance Director confirmed all numbers.

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This Template Works Because…

It’s comprehensive but structured: Every dimension is covered, but it’s organized so you can quickly find what you need.

It’s quantified wherever possible: Numbers make prioritization defensible and ROI calculable.

It shows the full system: Not just the symptom, but root causes, dependencies, workarounds, and stakeholder perspectives.

It’s actionable: Enough detail to design solutions and estimate costs/timelines.

It’s validated: Sources are cited, so credibility is clear.

It’s living: Metadata tracks status and next steps.

Building Your Complete Inventory: The Process

Phase 1: Initial Population (During Preliminary Assessment)

From each interview:

Create a preliminary problem entry for every distinct problem mentioned. Use a lightweight version initially:

P-001: Monthly reporting takes 16 hours (Finance)
P-002: Customer onboarding delays cause churn (CS)
P-003: Warehouse can't find inventory locations (Ops)
...

By end of assessment: You’ll have 30-60 preliminary problems identified.

Don’t try to complete the full template yet. You don’t have enough data.

Phase 2: Validation & Enrichment (Workshop Session 1)

During problem identification exercises:

Cross-reference workshop findings with your preliminary list:

  • Which problems get mentioned multiple times? (High signal)
  • Which problems have quantifiable examples? (Good candidates)
  • Which problems are actually symptoms of deeper issues? (Refine)
  • Which problems are isolated complaints? (Deprioritize)

Update problem entries with:

  • Additional stakeholders who mentioned it
  • Specific examples from workshop stories
  • Frequency estimates
  • Preliminary impact assessment

Consolidate duplicates:

You might discover:

  • P-007: “Sales can’t find customer history”
  • P-019: “Customer success lacks visibility into past interactions”
  • P-031: “Support team doesn’t know what sales promised”

These are the same problem from different angles. Consolidate:

P-007: Cross-functional customer data fragmentation
- Sales can't see support tickets
- CS can't see sales notes  
- Support doesn't know sales commitments
- No single customer view

Phase 3: Quantification (Workshop Session 2)

This is where problems get real.

For each high-priority problem:

Time Cost Exercise:

“Everyone who deals with this problem, estimate: How much time do you spend on this per week/month?”

Collect estimates, average them (or triangulate if wildly different).

Business Impact Exercise:

“What happens if we don’t fix this? What’s the consequence?”

Map to:

  • Revenue impact (lost sales, delayed revenue recognition)
  • Cost impact (labor waste, rework, inefficiency)
  • Risk impact (compliance, security, reputation)
  • Strategic impact (missed opportunities, competitive disadvantage)
  • People impact (burnout, turnover, morale)

Error Rate Exercise:

“How often does this go wrong? What does wrong look like?”

Quantify:

  • Error frequency
  • Cost per error
  • Rework time
  • Customer impact

Update inventory entries with all quantification data.

Phase 4: Root Cause Analysis (Workshop Session 2 continued)

For each problem, fill out the fishbone:

  • Technology causes
  • Process causes
  • Data causes
  • People/organizational causes

Document these in the Root Cause Analysis section.

Identify problem clusters:

Problems that share root causes should be grouped. Fixing one root cause might resolve multiple surface problems.

Example cluster:

ROOT CAUSE: No integration between Salesforce and ERP

SURFACE PROBLEMS:
- P-001: Manual monthly reporting
- P-012: Can't see real-time order status
- P-018: Inventory reconciliation nightmare
- P-024: Duplicate data entry
- P-029: Sales forecasting inaccurate

Solving the root cause (integration) potentially resolves 5+ problems.

Phase 5: Solution Mapping (Workshop Session 3)

For each problem, document:

  • Potential solution approaches
  • Rough cost estimates
  • Implementation complexity
  • AI applicability
  • Prerequisites
  • Expected outcomes

Update the “Solution Considerations” section of inventory.

Phase 6: Prioritization Scoring (Workshop Session 4)

Apply prioritization framework to every problem.

Score each on:

  • Business impact (1-5)
  • Frequency (1-5)
  • Scope (1-5)
  • Cost if not solved (1-5)
  • Risk level (1-5)

And inverse score on:

  • Implementation difficulty (5 = easy, 1 = very hard)
  • Time to implement (5 = fast, 1 = slow)
  • Resource requirements (5 = minimal, 1 = massive)
  • Organizational complexity (5 = simple, 1 = politically fraught)

Calculate weighted total score.

Rank all problems by score.

This creates your prioritized roadmap foundation.

The Inventory Database: Structural Views

Your master inventory should support multiple views for different purposes.

View 1: By Department

Shows all problems affecting each department, useful for:

  • Departmental briefings
  • Resource allocation discussions
  • Understanding departmental pain points
FINANCE DEPARTMENT PROBLEMS:

High Priority:
- P-001: Manual monthly reporting (16 hrs/month)
- P-005: Sales forecasting requires manual compilation (8 hrs/month)
- P-027: Invoice discrepancies require manual research (6 hrs/month)

Medium Priority:
- P-033: Budget variance reports are week delayed (3 hrs/month)
- P-041: Expense report approvals bottleneck at month-end (4 hrs/month)

Low Priority:
- P-047: Petty cash reconciliation tedious (1 hr/month)

Total Finance Time Waste: 38 hours/month = $29,640/year

View 2: By Problem Category

Shows patterns across the organization, useful for:

  • Identifying systemic issues
  • Planning infrastructure investments
  • Understanding capability gaps
CATEGORY: Data Fragmentation & Integration

Problems in this category: 12

Total quantified annual cost: $187,000
Affected departments: All departments (company-wide)

Key problems:
- P-001: Salesforce/ERP integration gap (Finance)
- P-012: Customer data scattered across 4 systems (CS)
- P-018: Inventory data not synchronized (Operations)
- P-023: No central customer view (Sales, CS, Support)
- [etc.]

Root cause pattern: Systems implemented independently without integration 
strategy over 10+ years

Systemic solution: 
- Implement data warehouse
- Build integration layer
- Establish data governance
- Estimated investment: $250K
- Estimated annual savings: $150K+
- Payback: ~1.7 years

Categories might include:

  • Data fragmentation
  • Manual/repetitive processes
  • Communication & handoff failures
  • Knowledge management gaps
  • Tool inadequacy
  • Process complexity
  • Quality control failures
  • Customer experience issues

View 3: By Root Cause

Shows which root causes drive the most problems, useful for:

  • Finding leverage points
  • Strategic planning
  • Avoiding symptom-chasing
ROOT CAUSE: No Integration Between Salesforce and ERP

Directly causes or contributes to: 8 problems
- P-001: Manual reporting
- P-005: Sales forecasting issues
- P-012: Order status invisibility
- P-018: Inventory reconciliation
- P-024: Duplicate data entry
- P-029: Inaccurate pipeline visibility
- P-035: Customer delivery date uncertainty
- P-042: Commission calculation delays

Combined annual cost: $94,000

Systemic solution: Build Salesforce-ERP integration
- Cost: $75K-100K
- Payback: ~1 year
- Solves 8 problems with one initiative

This is a HIGH LEVERAGE opportunity.

View 4: By Priority Tier

Shows the implementation roadmap, useful for:

  • Executive presentations
  • Budget requests
  • Program planning
TIER 1 PRIORITIES (Implement Q1-Q2 2026)
Total problems: 7
Combined annual cost: $312,000
Combined implementation cost: $450K
Expected ROI: Payback in 1.5 years

P-001: Manual monthly reporting
P-007: Cross-functional customer data fragmentation  
P-012: Order status invisibility
P-015: Customer onboarding delays
P-019: Support ticket routing failures
P-023: Sales pipeline inaccuracy
P-028: Vendor invoice processing backlog

TIER 2 PRIORITIES (Implement Q3-Q4 2026)
[etc.]

View 5: By Solution Type

Shows how solutions cluster, useful for:

  • Team planning (who works on what)
  • Budget categorization
  • Identifying quick wins vs. strategic projects
SOLUTION CATEGORY: Process Redesign (No/minimal tech required)

Problems solvable with process redesign: 8
Combined annual cost: $67,000
Implementation cost: Mostly time (~200 hours consulting)
Timeline: Can implement in parallel, 1-3 months each

Examples:
- P-033: Budget variance report delays
  → Redesign workflow, eliminate approval bottleneck
  
- P-041: Month-end expense approval jam
  → Implement rolling approval process, don't batch at month-end
  
- P-038: Customer onboarding steps unclear
  → Document and standardize process, create checklist

These are QUICK WINS - high ROI, low cost, fast implementation.

Solution categories:

  • Process redesign
  • System integration
  • Automation/AI
  • Tool replacement
  • Training/knowledge management
  • Organizational change

View 6: Cross-Functional Impact Map

Shows how problems ripple across departments, useful for:

  • Building coalitions
  • Demonstrating systemic nature
  • Justifying cross-functional solutions
PROBLEM: P-001 (Manual monthly reporting)

PRIMARY IMPACT:
- Finance: 16 hrs/month direct labor

SECONDARY IMPACT:
- Operations: 1 hr/month providing data
- Warehouse: 1 hr/month providing data
- Executive team: Delayed visibility, lower confidence in data

TERTIARY IMPACT:
- Board/Investors: Delayed financial information
- All departments: Budget variance analysis delayed
- Strategy team: Can't quickly respond to ad-hoc data requests

OPPORTUNITY:
Solving this one problem improves experience for 6 different stakeholder groups.
Cross-functional support for solution is likely high.

Inventory Quality Control: What Good Looks Like

Quality Criteria

✅ Good Problem Statement: “Monthly financial reporting requires 16 hours of manual data compilation across three disconnected systems, causing delayed visibility and occasional errors in executive dashboards.”

Specific, quantified, describes impact, identifies root cause category.

❌ Bad Problem Statement: “Reporting takes too long.”

Vague, no quantification, no context, no actionable information.

✅ Good Quantification: “Occurs monthly (12x/year). Affects 2 Finance Analysts (16 hrs each = 32 total hrs/month). Annual cost: $24,960 in direct labor. Error rate: 30% of reports require rework (avg 4 hrs). Total annual cost including opportunity cost: ~$44K.”

Multiple dimensions, specific numbers, sources cited.

❌ Bad Quantification: “This is a big problem that wastes a lot of time.”

No numbers, no dimensions, pure assertion.

✅ Good Root Cause: “Systems were implemented independently without integration strategy. Salesforce uses sales product names, ERP uses internal SKU codes, warehouse system uses bin locations. No translation layer exists. Manual reconciliation required.”

Specific, technical, explains the mechanism of failure.

❌ Bad Root Cause: “The systems don’t work well together.”

Surface-level, doesn’t explain why, can’t design solution from this.

✅ Good Stakeholder Perspective: “Finance Analysts: ‘This is the worst part of my job. It’s tedious, error-prone, and feels like a waste of my skills. I didn’t get a finance degree to copy-paste data between spreadsheets.’ Priority: CRITICAL (affects them weekly).”

Specific quote, emotional resonance, clear priority level.

❌ Bad Stakeholder Perspective: “Finance team doesn’t like this.”

Generic, no depth, doesn’t help understand real impact.

✅ Good Solution Consideration: “Hybrid approach: Quick win with process redesign (standardize product codes, 1-2 months, $5K) while planning integration project (Salesforce-ERP connector, 3-6 months, $75K). Interim RPA bot for data extraction (2 months, $25K). Expected total ROI: 2-year payback.”

Multiple options, timeline, cost, realistic approach.

❌ Bad Solution Consideration: “Use AI to fix it.”

Magic wand thinking, no specificity, not actionable.

Validation Checklist

For each problem in inventory, verify:

Completeness:

  • [ ] Problem statement is clear and specific
  • [ ] Discovery source is documented
  • [ ] Current state process is described in detail
  • [ ] Frequency and scope are quantified
  • [ ] Impact is quantified (time, cost, business effect)
  • [ ] Root cause analysis is complete
  • [ ] Cross-functional dependencies are mapped
  • [ ] Multiple stakeholder perspectives are captured
  • [ ] Workarounds are documented
  • [ ] Solution considerations are outlined
  • [ ] Priority score is calculated

Accuracy:

  • [ ] Quantification is based on real data (not guesses)
  • [ ] Sources are cited for all claims
  • [ ] Stakeholder quotes are accurate
  • [ ] Cost calculations are verified
  • [ ] Process descriptions match reality (not idealized)

Actionability:

  • [ ] Problem is specific enough to design solution
  • [ ] Success metrics are clear
  • [ ] Root causes point to intervention points
  • [ ] Solution approaches are realistic

Validation:

  • [ ] Problem was confirmed by multiple sources
  • [ ] Workshop participants validated it
  • [ ] Affected stakeholders reviewed it
  • [ ] Numbers were triangulated or verified

Common Inventory Mistakes and How to Fix Them

Mistake #1: Accepting Vague Problem Statements

What it looks like:

  • “Communication could be better”
  • “The system is slow”
  • “We need more visibility”
  • “Processes are inefficient”

Why it’s a problem: You can’t design solutions, prioritize, or measure success with vague problems.

How to fix it:

Use the 5W1H framework to force specificity:

Who experiences this problem? What specifically happens (or doesn’t happen)? When does it occur? Where in the process does it break down? Why is this a problem (what’s the impact)? How does it currently get resolved (workarounds)?

Transform:

  • ❌ “Communication could be better”
  • ✅ “Customer Success doesn’t receive notification when Sales closes deals, resulting in 3-5 day delay in onboarding kickoff, causing customer frustration and ~15% of new customers contacting support asking ‘what’s next?'”

Mistake #2: Confusing Symptoms with Root Causes

What it looks like:

  • Problem: “Reports are always late”
  • Root cause: “People are slow”

Why it’s a problem: You’ll design solutions that don’t actually fix anything.

How to fix it:

Use Five Whys religiously:

Problem: Reports are late
Why? → People can't finish them on time
Why? → Data isn't available when needed
Why? → Systems don't export data automatically
Why? → Systems weren't integrated when implemented
Why? → No enterprise architecture planning historically

Root cause: Lack of integration strategy during system implementations

The real problem isn’t “people are slow”—it’s systems architecture.

Mistake #3: Missing the Cross-Functional Ripple Effects

What it looks like:

  • P-001: “Finance reporting takes too long” (documented)
  • Missed: How this affects Operations, Sales, Executive team, Board

Why it’s a problem: You underestimate impact, miss coalition-building opportunities, and can’t justify solutions.

How to fix it:

For every problem, map the cascade:

Primary victim: Finance (16 hrs/month)
   ↓
Secondary victims: Operations, Warehouse (interruption)
   ↓
Tertiary victims: Executive team (delayed decisions)
   ↓
Quaternary victims: Board (delayed visibility)
   ↓
Organizational impact: Strategic agility reduced

Ask: “Who else does this affect, even indirectly?”

Mistake #4: Quantifying Only Direct Labor Cost

What it looks like:

  • Problem costs $10K/year (time × hourly rate)
  • Missed: Error cost, opportunity cost, strategic cost, morale cost

Why it’s a problem: You massively underestimate true cost and can’t justify investment.

How to fix it:

Use the Total Cost Framework:

Direct Labor Cost: Time spent × loaded hourly rate

Error & Rework Cost: Error frequency × rework time × loaded rate

Opportunity Cost: What else could these people be doing with that time? What’s the value of that foregone work?

Risk Cost: What’s the potential cost of compliance failure, customer churn, security breach, etc.?

Morale & Turnover Cost: How does this contribute to burnout? What’s the cost of losing people?

Strategic Cost: How does this slow decision-making or limit organizational capability?

Example transformation:

❌ Incomplete: “Manual reporting costs $20K/year in analyst time.”

✅ Complete: “Manual reporting costs $20K/year in direct labor, $2K/year in error rework, $25K/year in opportunity cost (analysts could do higher-value forecasting), $15K/year in estimated analyst turnover contribution (last analyst cited this as burnout factor), plus unmeasured strategic cost of 5-day delayed financial visibility. Total estimated cost: $62K+/year.”

Now the $75K integration project looks like a no-brainer instead of a questionable expense.

Mistake #5: Treating All Problems as Equal

What it looks like:

  • Flat list of 47 problems
  • No differentiation
  • No prioritization
  • Paralysis

Why it’s a problem: You can’t implement 47 solutions simultaneously. Without prioritization, political battles ensue or nothing happens.

How to fix it:

Implement tiered prioritization:

P0 – Critical (Fix immediately):

  • Compliance risk
  • Security vulnerability
  • Customer churn driver
  • Revenue blocker

P1 – High Priority (Fix within 6 months):

  • Significant cost/waste
  • Employee burnout driver
  • Strategic limitation
  • High-impact, solvable

P2 – Medium Priority (Fix within 12 months):

  • Moderate cost/waste
  • Quality of life issues
  • Process improvements

P3 – Low Priority (Fix if resources permit):

  • Nice-to-have improvements
  • Edge case issues
  • Minor inefficiencies

P4 – Backlog (Documented but deferred):

  • Very low impact
  • Not worth solving now
  • May resolve naturally

Make prioritization transparent and defensible with scoring methodology.

Mistake #6: Ignoring Workarounds

What it looks like:

  • Documenting official process
  • Missing the 6 workarounds people actually use

Why it’s a problem: You don’t understand real behavior, and your solution might break functional workarounds.

How to fix it:

Actively hunt for workarounds:

“Walk me through how you actually do this, not how the manual says you should.”

“What shortcuts do experienced people use?”

“What would break if we enforced the official process?”

Document every workaround with:

  • What the workaround is
  • Why it exists (what does it solve?)
  • What it costs (time, errors, fragility)
  • What it reveals about the underlying problem

Workarounds are treasure maps to root causes.

Mistake #7: Solutions Before Problems

What it looks like:

  • “We should use AI for X”
  • “Let’s implement Y tool”
  • Solution brainstorming before problem understanding

Why it’s a problem: Solution-first thinking leads to tools looking for problems, not problems finding solutions.

How to fix it:

Strict phase discipline:

Phase 1-2: Problem definition and quantification

  • No solutions discussed
  • Pure problem understanding
  • Root cause analysis

Phase 3: Solution design

  • Now you can brainstorm solutions
  • Multiple approaches considered
  • AI is one tool in the toolkit, not the answer to everything

Mantra: “Fall in love with the problem, not the solution.”

The Inventory as Living Document

Your problem inventory doesn’t end at Session 4. It evolves.

During Implementation

Update problem entries as you learn:

P-001: Manual monthly reporting

[Original entry from discovery]

UPDATE (Implementation Week 4):
During integration implementation, discovered additional complexity:
- Salesforce has 3 custom fields not in ERP
- Historical data migration will require data cleanup (estimated +40 hours)
- Warehouse manager retiring in 2 months, creating urgency for knowledge transfer

Implications:
- Timeline extended by 2 weeks
- Budget increased by $8K for data cleanup
- Added knowledge transfer workstream

[Updated entry reflecting reality]

As New Problems Emerge

Add new entries when discovered:

P-048: [New problem discovered during P-001 implementation]

Problem: API rate limits in Salesforce causing integration throttling

Source: Discovered during implementation of P-001 solution
Impact: Integration runs can only execute 2x/day, not real-time as planned
Requires: Upgraded Salesforce tier or batching strategy
Cost: $15K/year for upgraded tier OR compromise on real-time requirement

Decision needed: How do we handle this?

Your inventory becomes the organizational memory of operational problems.

Quarterly Review Cycle

Every quarter, review inventory:

Problems solved:

  • Move to “Resolved” status
  • Document actual vs. expected outcomes
  • Calculate realized ROI
  • Capture lessons learned

Problems in progress:

  • Update status
  • Document blockers
  • Adjust timelines/budgets if needed

Problems not yet addressed:

  • Re-validate priority (has impact changed?)
  • Update cost estimates (inflation, scope creep)
  • Assess whether still relevant

New problems:

  • Add to inventory
  • Score and prioritize
  • Decide whether to tackle now or defer

Presenting the Problem Inventory

Different audiences need different views.

For Executive Sponsor (Before Phase 2 Kickoff)

Present:

  • Top 10 problems by quantified impact
  • Problem categories and patterns
  • Cross-functional nature of issues
  • Total cost of identified problems
  • Roadmap preview

Format: 10-slide deck + appendix with full inventory

Goal: Get buy-in for workshop process and implementation budget

For Workshop Participants (Session 1)

Present:

  • Problem themes from assessment
  • Rough categorization
  • Examples (not exhaustive list)

Format: Verbal summary + whiteboard

Goal: Prime conversation, validate that you heard them correctly

For Implementation Teams (Post-Session 4)

Present:

  • Full problem entries for their assigned projects
  • Dependencies and prerequisites
  • Success metrics
  • Related problems that might be affected

Format: Detailed problem briefs (using full template)

Goal: Give implementers complete context for solution design

For Executive Leadership (Final Presentation)

Present:

  • Prioritized problem list (Tier 1, 2, 3)
  • Total quantified cost by tier
  • Recommended solutions and investments
  • Expected ROI and timelines

Format: Executive summary + supporting detail

Goal: Secure approval and resources

Technology Considerations

Depending on inventory size and complexity, consider tooling:

For Small Inventories (< 25 problems):

Structured Google Doc or Notion page:

  • Searchable
  • Taggable
  • Shareable
  • Free

For Medium Inventories (25-75 problems):

Airtable or Smartsheet:

  • Database structure
  • Multiple views (by department, category, priority)
  • Collaboration features
  • Status tracking

For Large Inventories (75+ problems):

Project management tool (Jira, Asana, Monday):

  • Complex workflows
  • Dependencies tracking
  • Integration with implementation work
  • Reporting capabilities

Or build custom database (Excel/Google Sheets with structure):

  • Full control
  • Custom reporting
  • Pivot tables for analysis
  • Low cost

The Meta-Principle: Inventory Quality Determines Engagement Quality

A comprehensive, well-structured problem inventory is the strategic asset that makes everything else possible.

It’s the difference between:

  • ❌ Vague “we should improve things” → ✅ Data-driven roadmap with ROI projections
  • ❌ Political debates about priorities → ✅ Objective scoring and defensible decisions
  • ❌ Solutions that miss the mark → ✅ Solutions that address root causes
  • ❌ Initiatives that stall → ✅ Clear ownership and success metrics

Invest heavily in inventory quality. Everything downstream depends on it.

When an executive asks “Why are we spending $100K on this?”, you point to the inventory:

“Because we quantified that this problem cluster costs us $180K/year, affects 4 departments, and is driving analyst turnover. Here’s the data. Here are the sources. Here’s the ROI calculation. This is defensible.”

That’s the power of a comprehensive problem inventory.

What aspects of problem inventory creation are you most concerned about? Quantification methodology? Getting honest input? Avoiding analysis paralysis? Managing scope creep? Handling problems that cross organizational boundaries?