Procurement Data Visualization

Government Entity

Project Overview

As part of a digital transformation program for a leading UAE client, we designed a procurement portal integrated with Microsoft Dynamics 365 and Power Apps. Midway through the project, stakeholders requested an additional data visualization dashboard to support strategic decision-making.
The dashboard was built to:
  • Streamline vendor management processes.
  • Provide real-time visibility into procurement activities and supplier performance.
  • Reduce reporting delays and improve decision-making speed.
A key challenge was achieving seamless integration across platforms while maintaining efficiency in existing workflows. To address this, we designed role-specific dashboards for Procurement Managers and the Procurement Director, each featuring tailored KPIs aligned with international procurement standards.
UX Objective: Deliver a dashboard that is intuitive, data-rich, and aligned with procurement workflows, enabling real-time insights and collaborative decision-making.

Team & Roles

Contributor Role Responsibilities
Parithimal Saravanan UX Architect / Product Owner Led user research, journey mapping, and dashboard design. Ensured alignment with user mental models and business logic.
Andrew Nicholas James Subject Matter Expert Defined product vision, prioritized features, and ensured strategic alignment.
Prasanna Medam Power Bi Developer Translated UX designs into functional dashboards, implemented logic, and optimized usability.

Between February and June 2025, I produced all major UX deliverables and presented to the client. I collaborated closely with a Product Manager and a Power BI Developer to ensure the final solution was both user-centric and technically sound.

The Challenge

Procurement teams were heavily dependent on Excel for tracking KPIs, which introduced several operational inefficiencies:

  • Delayed decision-making Slow feedback loops stalled progress and momentum.
  • Lack of accountability No clear ownership led to unresolved issues.
  • Missed insights Valuable input got lost in scattered channels.
  • Disjointed workflows Teams operated in silos, causing inefficiencies.
  • Manual data handling Time wasted on repetitive, error-prone tasks.
  • Limited visibility Stakeholders lacked a clear view of feedback status.

From a UX standpoint, the absence of a centralized, role-aware dashboard created friction in decision-making and data exploration. The challenge was to design a solution that offered:

  • Role-based access tailored to procurement functions
  • Intuitive data exploration for complex datasets
  • Real-time insights to support agile and informed decisions

Discovery & Research

Stakeholder Interviews & Key Insights

To uncover the root challenges in feedback management, I conducted interviews with a diverse group of stakeholders — including buyers, managers, department heads, project managers, and analysts. The goal was to understand:

  • Current feedback collection methods.
  • Pain points in the existing process.
  • Desired outcomes from a digital solution.
Key Findings

The interviews revealed several recurring issues:

  • Cognitive overload from manual KPI tracking led to frequent errors.
  • Poor data discoverability due to the absence of a centralized dashboard.
  • Workflow friction caused by lack of integration between tools and teams.
Experience Goals

These insights shaped our strategic direction. The solution needed to:

  • Enable collaboration across departments.
  • Automate repetitive tasks to reduce manual effort.
  • Ensure data integrity through structured input and traceability.

Mapping Procurement Workflows

To ensure the platform addressed key procurement needs, I mapped out the following critical workflows:

  • Spend Analysis Empowered users to explore purchasing trends and identify cost optimization opportunities.
  • Process Metrics Tracked procurement efficiency through cycle times, compliance rates, and bottlenecks.
  • Cost Saving Initiatives Enabled visibility into negotiated savings and realized benefits.
  • Real Cost vs. Statement of Work (SoW) Highlighted discrepancies between projected and actual spend to improve forecasting accuracy.

UX Insights Informed by Business Logic

We aligned UX decisions with the detailed business logic captured in the dashboard specifications.

Spend by Category (Top 80%)

This chart identifies the top categories contributing to 80% of procurement spend, enabling Pareto analysis and strategic focus.

  • Purpose: Pareto analysis for strategic focus
  • Logic: Identify categories contributing to 80% of total spend using invoiced amounts.
  • UX Design: Visualized Pareto analysis with drill-down capability.
  • Interaction: Clicking a category navigates to detailed breakdown (sub-categories, suppliers, projects).
  • Example: If total spend is AED 100,000, display categories contributing AED 80,000.
Data Creation Scenarios Test Case Scenarios
  • Create sample categories with varied spend values (e.g., AED 20K–100K).
  • Ensure total spend above AED 100K to test 80% threshold logic.
  • Select a date range and verify that categories contributing to ~80% of spend are displayed.
  • Validate cumulative spend logic and category sorting.
  • Click “View All” to confirm full category breakdown.
Upcoming Contract Expiry

Contracts nearing expiry area color-coded to indicate urgency:

  • Red <3 months
  • Orange 4 to 6 months
  • Purple >6 months



  • Purpose: Visual urgency indicators
  • Logic: Highlight contracts nearing expiry using color-coded bars.
  • UX Design: Visualurgency indicators (red/orange/purple) based on months to expiry.
  • Interaction: Drill-down to contract details by month.
  • Example: Contracts expiring <3 months shown in red; 4-6 months in orange.
Data Creation Scenarios Test Case Scenarios
  • Create contracts with varied end dates
  • Include expired and active contracts to test filtering logic.
  • Sekect a date range adn verify contract expiry color coding:
    • Red: <3 months
    • Orange: 4to 6 months
    • Purple: >6 months
  • Confirm sorting by expiry date.
Service Delivery Overrun

This bar chart tracks delays between committed and actual delivery dates for purchase orders, helping teams monitor supplier performance and address fulfilment inefficiencies.

  • Purpose: Monitor supplier performance
  • Logic: Calculate delivery days using committed and actual dates.
  • UX Design: Supplier level overrun indicators
  • Interaction: Drill-down to Po level delivery details
  • Example: Supplier X has e POs with delivery overruns of 5-10 days.
Data Creation Scenarios Test Case Scenarios
  • Create POs with varied delivery timelines.
  • Include multiple deliveries per PO to test latest date logic.
  • Calculate overrun days using committed vs actual delivery dates.
  • Validate on-time vs delayed delivery logic.
  • Test drill-down by supplier.
Single Source vs Competitive

This comparative chart segments procurement spend based on sourcing type—orders with RFPs are marked as competitive, while those without are single source—helping teams assess procurement transparency and sourcing strategy effectiveness.

  • Purpose: Assess sourcing strategy effectiveness
  • Logic: Segregate spend based on presence of RFP number.
  • UX Design: Tabs for Category and Supplier views, with tooltips and callouts.
  • Interaction: Hovering reveals sourcing type and spend breakdown.
  • Example: Display “Single Source” spend for orders without RFP and “Competitive” for those with RFP.
Data Creation Scenarios: Test Case Scenarios
  • Create orders with and without RFP numbers.
  • Assign categories and suppliers to test both tabs.
  • Validate segregation of orders with and without RFP numbers.
  • Confirm correct categorization under “Single Source” and “Competitive”.
  • Test tab switching between Category and Supplier views.

Design & Prototypes

Using the business logic as a foundation, I created:

  • Low-fidelity wireframes to explore visual hierarchy and storytelling.
  • High-fidelity mock-ups for stakeholder validation.
  • Dummy Excel datasets to simulate real data and test interactions.

Each visualization was designed to reflect the logic and metrics outlined in the Excel file, ensuring data accuracy, user comprehension, and task relevance.

Implementation Support

To ensure a smooth transition from design to implementation, we adopted a UX-driven enablement strategy that bridged the gap between design intent and technical execution—especially important as the Power BI developer was new to the Power Apps data architecture.

Dummy Dataset Creation

To accelerate development and validate the dashboard logic early, I created a dummy Excel dataset simulating procurement data such as:

  • Supplier profiles
  • Category and sub-category classifications
  • Project attributes
  • Budget and spend values

This allowed the developer to build and test dashboard components without waiting for backend integration. It also enabled early validation of:

  • Data visualization logic
  • Interaction patterns
  • Layout responsiveness
Data Mapping & Schema Definition

To reduce ambiguity and ensure consistency, I documented the data schema and mapped each metric to its corresponding D365 table and column. For example:

  • Spend by Category ProductCategories.ParentProductCategoryName, PurchaseOrderLinesV2.Spend mAED.
  • Actual Spend VendorInvoiceLines.NetAmount.
  • Budget BudgetControlStatisticsByDimensions.TotalRevisedBudget

This mapping ensured that the developer could confidently align visuals with backend data structures.

Validation & QA
  • Dummy data testing allowed us to validate visual logic and user flows before live data was available.
  • Bug tracking was done using Excel-based QA logs, where issues like incorrect values, missing legends, and drill-through errors were reviewed and resolved.
  • Stakeholder demos using simulated data helped gather feedback early and refine the dashboard iteratively.

This collaborative, modular approach minimized rework, de-risked integration challenges, and ensured that the final dashboard was both technically robust and user validated.

Data Validation Process

Tools Purpose Why Benefits
Microsoft Excel Simuate realistic procurement data before backend integration. Created mock datasets for employees, suppliers, categories, contracts, and budgets to test dashboard logic and output Enabled early usability testing and visual QA without waiting for live data.
D365 Schema + Excel Docs Ensure each chart pulls data from the correct tables and columns.

Mapped metrics like:

  • Spend by Category → ProductCategories.ParentProductCategoryName
  • Actual Spend → VendorInvoiceLines.NetAmount
  • Budget → BudgetControlStatisticsByDimensions.TotalRevisedBudget
 Maintained semantic consistency and reduced integration errors.
Internal QA Tracker Bug review and issue tracking

Reviewed charts for:

  • Incorrect values
  • Missing legends
  • Drill-through navigation errors
 Ensured visual and functional accuracy.
Power BI Desktop Validate interaction logic and visual responsiveness. Tested logics, slicers, drilldowns, and export-to-Excel features using dummy data. Iterative design reviews and stakeholder demos.
Microsoft Outlook + Teams + PPT Validate UX decisions with end users and business owners. Conducted walkthroughs of high-fidelity mock-ups and interactive Power BI reports. Aligned UX with stakeholder expectations.

Impact & Results

The final dashboard delivered:

  • Centralized insights replacing fragmented Excel workflows.
  • Role-based views supporting buyers and managers.
  • Improved decision-making through visual clarity and data integrity.
  • High stakeholder satisfaction due to timely delivery and collaborative design.

This case study demonstrates how UX strategy, business logic, and technical feasibility can converge to deliver a meaningful, impactful solution.

Final Design