Data Analysis Procedure

Vendor Spend Analysis & Dashboard Creation

Version 2.0 - Enhanced Procedure

Last Updated:

Document Owner: Analytics Team Lead

Next Review: Quarterly

Executive Summary

This procedure establishes a standardized methodology for analyzing client vendor spend data to create actionable business intelligence dashboards. The process transforms raw procurement data into strategic insights that drive business development opportunities and client value creation.

Key Deliverables

5
Category Levels
90%+
Spend Categorized
12
Quality Gates
5
Dashboard Tabs
📊

Data Quality Assessment

Comprehensive validation and cleansing procedures ensure data integrity and accuracy.

🏷️

Advanced Categorization

5-level taxonomy classification with industry-specific standards and vendor normalization.

📈

Interactive Dashboard

Power BI dashboard with geographic analysis, spend bands, and supplier intelligence.

🎯

Strategic Recommendations

Actionable insights and business development opportunities identification.

Prerequisites & Setup

Required resources and project initialization

Required Personnel

1-2 Days
  • Analytics Team Lead (Project Owner)
  • Data Analyst (Primary)
  • Business Development Representative
  • Quality Assurance Reviewer
  • Senior Analyst (Approval Authority)

Software & Tools

  • Microsoft Excel (latest version)
  • Power BI Pro license
  • Access to Versatex SharePoint
  • VPN access for secure data handling
  • Fuzzy matching tools (PowerBI/R/Python)

Data Security Requirements

  • Encrypted folder structure created
  • Access permissions configured
  • Data retention policy reviewed
  • Compliance requirements verified
  • Backup procedures established

Data Collection & Initial Assessment

Template distribution and data validation

Data Request & Template Distribution

3-5 Days

Process Overview:

  1. Send Data Mapping Template via secure channel
  2. Schedule kickoff call to review requirements
  3. Provide data security instructions
  4. Establish primary client contact
  5. Set data delivery deadline (5-7 business days)

Required Data Fields

  • Transaction ID/Invoice Number
  • Supplier Name and ID
  • Spend Amount (Currency specified)
  • Transaction Date
  • Category/GL Code
  • Description (Product/Service)
  • Purchase Order Number
  • Department/Cost Center
  • Location/Site
  • Payment Terms
  • Contract Reference (if applicable)

    • Initial Validation Checklist

    1-2 Days
  • All requested files received
  • File formats are readable (.xlsx, .csv, .txt)
  • Data covers minimum 12 consecutive months
  • File sizes indicate complete data sets
  • No obvious corruption or truncation
  • Initial field mapping feasible
  • Senior Analyst consulted on spend calculation field

    • Data Quality Assessment

    Completeness analysis and integrity validation

    Completeness Analysis

    2-3 Days

    Key Metrics to Calculate:

    • Total Spend: SUM(Spend Amount)
    • Transaction Count: COUNT(Transaction ID)
    • Unique Suppliers: COUNT DISTINCT(Supplier Name)
    • Data Completeness: (Non-null values / Total values) × 100

    Data Integrity Validation

    Date Validation:

    • Identify dates outside reasonable range (1980-current)
    • Flag future dates beyond current date
    • Check for consistent date formats

    Spend Amount Validation:

    • Remove non-numeric entries
    • Identify outliers using Z-score > 3
    • Flag negative values for review (retain in dataset)
    • Validate currency consistency

    Client Consultation Required

    1-2 Days
    • Clarify ambiguous field names
    • Address missing required fields
    • Validate identified outliers
    • Confirm calculation methodologies
    • Obtain Senior Analyst approval on spend field selection

    Data Cleansing & Standardization

    File management and vendor normalization

    Pre-Cleansing File Management

    1 Day
    • Create cleansed, uncategorized data file
    • Copy dataset into working copy
    • Create index column in column "A" for sort-back capability
    • Record baseline metrics (rows, suppliers, spend)

    Vendor Normalization Process

    2-3 Days

    Automated Normalization:

    • Apply fuzzy matching (PowerBI/R/Python)
    • Leverage Vendor ID when available
    • Generate automated match suggestions

    Manual Verification:

    • Review all automated changes
    • Sort alphabetically for efficient review
    • Preserve maximum detail (e.g., "Pepsi Co" over "Pepsi")
    • Research business suffix additions carefully

    Data Standardization

    • Remove duplicates (Excel: Data → Remove Duplicates)
    • Standardize currency formats
    • Apply consistent date formatting (YYYY-MM-DD)
    • Clean description fields
    • Retain negative spend (categorize as returns/credits)
    • Obtain client sign-off on final spend total

    Categorization Framework

    5-level taxonomy classification and progress tracking

    Progress Tracking Setup

    1 Day
    • Create automated tracking system (Excel/PowerBI)
    • Add columns for Categories 1-5
    • Track % spend categorized
    • Track % transactions categorized
    • Track % suppliers categorized

    Initial Categorization (All 5 Levels)

    7-10 Days

    Goal: Complete categorization to all 5 taxonomy levels

    Exception: Direct spend (medical services/equipment for hospitals) - Level 1 only

    Taxonomy Selection:

    • Open appropriate industry taxonomy from SharePoint
    • Identify useful categorization variables
    • Consider additional fields (unit price, quantity, etc.)

    Categorization Process:

    • Start with highest spend suppliers
    • Research suppliers via Google when needed
    • Use dashes in remaining levels for partial categorization
    • Leave blank if data insufficient
    • Retain negative spend in dataset

    Quality Validation & Visualization

    2-3 Days
    • Research suppliers with ≥0.1% of total spend
    • Create Level 1-2 category bar charts
    • Highlight in-scope categories (Facilities, Professional Services)
    • Apply Versatex branding to PowerPoint slides
    • Submit to leadership for review

    Dashboard Development

    Power BI dashboard creation and optimization

    Dashboard Architecture

    7-10 Days
    📊

    Tab 1: Executive Summary

    • Key spend metrics and KPIs
    • Top 10 suppliers by spend
    • Spend trend analysis
    • Opportunity identification
    🗺️

    Tab 2: Geographic Analysis

    • Interactive map visualization
    • Spend by region/location
    • Supplier geographic distribution
    • Regional opportunities
    🏷️

    Tab 3: Category Deep Dive

    • Interactive category hierarchy
    • Drill-down capabilities
    • Category spend analysis
    • Benchmark comparisons
    🔍

    Tab 4: Supplier Intelligence

    • Supplier performance metrics
    • Commonality analysis
    • Risk assessment indicators
    • Consolidation opportunities
    💰

    Tab 5: Spend Analytics

    • Spend band analysis (10-12 bands)
    • Transaction distribution
    • Seasonal trend analysis
    • Payment terms analysis

    Interactive Features

    • Date range selectors
    • Category filters
    • Supplier search functionality
    • Export capabilities
    • Drill-through functionality
    • Mobile-friendly layouts

    Testing & Validation

    1-2 Days
    • Data accuracy verification
    • Calculation validation
    • User experience testing
    • Performance benchmarking
    • Client feedback incorporation

    Delivery & Implementation

    Dashboard publishing and client handover

    Dashboard Publishing

    1-2 Days
    • Publish to Power BI Service
    • Configure access permissions
    • Set up automated data refresh
    • Create user documentation
    • Provide training materials

    Client Handover Package

    • Interactive Power BI dashboard
    • User guide and training materials
    • Data dictionary and methodology
    • Executive summary presentation
    • Raw categorized data file
    • Project documentation

    Training & Support

    Training Session Agenda:

    • Dashboard navigation overview
    • Key insights walkthrough
    • Interactive features demonstration
    • Q&A session
    • Support contact information provided

    Quality Management

    Review gates and success metrics

    Quality Review Gates

    Gate 1: Data Quality Complete

    • Data validation passed
    • Client consultation completed
    • Cleansing approach approved

    Gate 2: Initial Categorization In Progress

    • Category assignments validated
    • Client feedback incorporated
    • Visualization approved

    Gate 3: Full Categorization Pending

    • 90%+ spend categorized
    • Quality assurance review passed
    • Taxonomy approved

    Gate 4: Dashboard Complete Pending

    • All features functional
    • Testing completed
    • Client acceptance obtained

    Success Metrics

    >95%
    Data Completeness
    >90%
    Categorization Coverage
    >4.5/5
    Client Satisfaction
    ±10%
    Timeline Adherence

    Risk Management

    Common risks and mitigation strategies

    🚨 Data Quality Issues

    Risk: Incomplete or inaccurate source data

    Mitigation: Robust validation protocols, early client engagement

    Escalation: Analytics Team Lead → Department Manager

    ⏰ Timeline Delays

    Risk: Extended client response times

    Mitigation: Clear communication protocols, alternative workstreams

    Escalation: Business Development → Senior Leadership

    💻 Technical Challenges

    Risk: Complex data structures or system limitations

    Mitigation: Early technical assessment, fallback options

    Escalation: Senior Analyst → IT Department

    📈 Scope Creep

    Risk: Additional requirements during execution

    Mitigation: Clear scope documentation, change control process

    Escalation: Project Manager → Senior Leadership

    Escalation Procedures

    Level 1: Analytics Team Lead

    Day-to-day issues, client communication, resource allocation

    Level 2: Department Manager

    Timeline delays, resource conflicts, quality issues

    Level 3: Senior Leadership

    Strategic decisions, major scope changes, client escalations

    Appendices

    Supporting documents and templates

    📋 Appendix A: Data Mapping Template

    Standard template for client data collection with all required fields and formatting guidelines.

    Download Template

    🏷️ Appendix B: Industry Taxonomy References

    Comprehensive taxonomy libraries for healthcare, education, manufacturing, and other verticals.

    Access Taxonomies

    📊 Appendix C: Power BI Template

    Pre-configured dashboard template with standard visualizations and branding elements.

    Download Template

    ✅ Appendix D: Quality Checklists

    Detailed quality assurance procedures and validation checklists for each project phase.

    Download Checklists

    📧 Appendix E: Communication Templates

    Email templates, status reports, and client communication forms for consistent messaging.

    Download Templates

    🔧 Appendix F: Technical Resources

    Scripts, code snippets, and technical guides for vendor normalization and data processing.

    Access Resources

    Document Management

    All appendix documents are version-controlled and regularly updated. Click on any category above to browse available files.

    Document Status:

    • 📄 Data Mapping Template: Updated - v2.1 (Jan 2025)
    • 🏷️ Taxonomy Files: Current - Last reviewed Dec 2024
    • 📊 Power BI Template: Review Due - v1.8 (Nov 2024)
    • ✅ Quality Checklists: Updated - v3.0 (Jan 2025)
    • 📧 Communication Templates: Current - v2.3 (Dec 2024)
    • 🔧 Technical Resources: Updates Available - Multiple versions

    🔄 Update Notifications:

    Recent Updates:

    • ✨ Added vendor normalization Python script (Jan 15, 2025)
    • 📝 Updated quality checklists with new validation rules (Jan 10, 2025)
    • 🎨 Refreshed Power BI template with latest Versatex branding (Jan 5, 2025)

    Subscribe to updates: Contact Defoxx Analytics Team to receive automatic notifications when templates are updated.