Effective inventory management is essential for any business, and we are pleased to share how we leveraged NetSuite data and Power BI to develop this actionable Inventory Analytics Dashboard.

Key Insights Delivered:

• Inventory Value: $4.44M tracked dynamically across all warehouses and products.

• Quantity On Hand: Real-time updates ensure accurate stock visibility (537,953 units).

• Landed Costs Analysis: Comprehensive breakdown of costs per unit and by warehouse, helping to identify cost-saving opportunities.

• Product Cost Trends: Visualizing historical cost trends to assist in budgeting and forecasting.

How This Was Achieved:

1. Data Extraction: Using NetSuite's advanced saved searches and SuiteAnalytics, we extracted detailed inventory data, including unit values, purchase prices, and landed costs.

2. Data Transformation: The extracted data was cleaned and transformed into a structured format using Power Query in Power BI.

3. Dynamic Reporting: Visuals such as donut charts, line graphs, and tables were built to provide clear and actionable insights into inventory performance.

4. Real-Time Updates: Scheduled refreshes were integrated between NetSuite and Power BI to ensure the data remains up-to-date at all times.

Business Impact:

• Improved Decision-Making: Warehouse-level insights into landed costs highlight areas for potential cost reduction.

• Streamlined Inventory Management: Real-time data helps avoid overstock or understock situations.

• Enhanced Forecasting: Historical trends empower finance teams to plan future budgets with greater confidence.

Key Insights Delivered

1. Total Gross MRR: $10.50M tracked dynamically across all customers and subscription plans.

2. Total Gross ARR: $126.02M annualized revenue provides a clear picture of long-term recurring revenue potential.

3. New Customers: Real-time tracking of 32.83K new customers ensures visibility into growth.

4. Churn Impact: Churn MRR ($519.71K) and Churn ARR ($6.24M) insights help identify revenue risks and retention opportunities.

5. Revenue Trends: Visualized Gross MRR, ARR, new bookings, and churn trends over time to highlight performance spikes and dips.

How This Was Achieved

1. Data Extraction: Leveraged ERP systems like NetSuite and MineCloud to extract subscription and customer data, including revenue details, churn, and upsell/downsell activity.

2. Data Transformation: Cleaned and transformed data using Power BI’s Power Query, aligning key metrics like MRR and ARR across monthly and quarterly views.

3. Dynamic Reporting: Built interactive dashboards with charts (line and bar graphs) and tables to present revenue trends, customer acquisition, and churn metrics.

4. Automated Refreshes: Integrated data pipelines to refresh reports dynamically, ensuring stakeholders have access to real-time updates.

5. Templates for Scalability: Created customizable dashboard templates to scale reporting for different landscaping companies.

Business Impact

1. Optimized Revenue Streams: Insights into churn and upsell trends enable strategic focus on high-growth areas and customer retention.

2. Enhanced Decision-Making: Real-time updates on Gross MRR and ARR provide a consolidated view of financial health for timely interventions.

3. Streamlined Operations: Dynamic reporting templates reduce manual effort, improving scalability across multiple clients.

4. Improved Retention Strategies: By analyzing churn MRR and ARR, businesses can identify at-risk customers and implement targeted retention plans.

5. Future Readiness: Trend analysis empowers businesses to forecast revenues and allocate resources effectively for upcoming quarters.

Key Insights Delivered

1. Total Projects: 9,727 projects tracked dynamically across various phases and risk levels.

2. Project Cost: Total project cost of £2,544M analyzed and compared against the budgeted cost of £2,767M to monitor variances.

3. Projects On Track: 3,205 projects are progressing as planned, ensuring a steady workflow.

4. Projects At Risk: 3,329 projects categorized as high-risk, requiring immediate attention and corrective measures.

5. Budget Variance: High variance of 4,831.05%, highlighting potential cost overruns and areas for financial control.

6. Phase and Risk Analysis: Projects distributed across planning, execution, testing, and closure phases, with risk levels ranging from low to high.

How This Was Achieved

1. Data Extraction: Retrieved project performance, financials, and progress data from ERP systems and project management tools.

2. Data Transformation: Cleaned and prepared data using Power BI's Power Query to align metrics such as cost, risk levels, and phase progress.

3. Dynamic Reporting: Developed visual dashboards including bar charts, treemaps, and Gantt-style progress tracking to present project health, budget adherence, and phase distribution.

4. Real-Time Updates: Integrated scheduled data refreshes to ensure accuracy in reporting and quick decision-making.

5. Custom Risk Analysis: Incorporated filters for phase and risk levels to provide actionable insights into areas requiring intervention.

Business Impact

1. Improved Cost Management: Clear visibility into budget vs. actual costs helps stakeholders address overruns proactively.

2. Risk Mitigation: Identification of high-risk projects enables teams to reallocate resources and prioritize critical areas.

3. Streamlined Project Progress: Phase-wise tracking supports better planning and execution to minimize delays.

4. Enhanced Decision-Making: Consolidated insights across all projects allow leadership to make data-driven decisions.

5. Future-Ready Planning: Budget variances and risk-level insights empower organizations to improve forecasting and resource allocation.