Transforming 5 Years of Transactional Data into A Predictive Decision-Making Engine. 

This project demonstrates the intersection of Engineering System-Thinking and Business Intelligence. I treated the automotive sales pipeline like an integrated circuit identifying power losses (bottlenecks), optimizing current (delivery speed), and forecasting load (revenue). 

Data Architecture & Integrity 

Content: Before visualization, I performed a rigorous ETL (Extract, Transform, Load) process on the raw Nigerian car sales dataset: 

Cleaning: Standardized currency fields into Naira (₦) and cleaned over 8,000 transaction records for temporal accuracy. 

Localization: Geocoded sales data across all 16 Nigerian states to enable regional market analysis. 

Normalization: Adjusted brand and model naming conventions (Toyota, Honda, Benz, etc.) to ensure accurate aggregation.

Dynamic Benchmarking & Success Metrics

Content: Unlike static reports, this dashboard uses Dynamic DAX (Data Analysis Expressions) to calculate performance in real-time. 

The Growth Engine: I engineered a "Dynamic Target" measure that automatically calculates a 110% growth benchmark based on whatever year or period is selected. 

Formula Logic: DynamicTarget = SUM(revenue_naira) * 1.10

Benefit: This allows management to see instantly if a specific quarter met the "10% growth" objective without manual recalculation. 

Visual Breakdown

KPI Cards: Instant visibility into Total Revenue (₦104.26B), Sales Volume (8K units), and Delivery Efficiency (8.00 hours). 

Performance Gauge: A "Success Needle" that compares actual sales against the dynamic 10% growth target. 

Regional Treemap: Identifies Lagos (₦35.14B) and Oyo (₦5.36B) as the primary revenue drivers. 

Brand Analytics: A horizontal bar chart identifying which manufacturers dominate the Nigerian market. 

The Forecast, Predictive Outlook(Seeing Into the Future)

Content: Using Time-Series Forecasting, I extended the historical data into the future.

Timeline: Focused specifically on Q2 2026 (April–June) .

Methodology: Applied exponential smoothing with a 95% Confidence Interval to account for market volatility. 

Insight: The forecast predicts continued stability, allowing EnyRash Auto to plan inventory and staffing needs three months in advance.

Project Conclusion 

The EnyRash Auto Dashboard provides a single source of truth for the business. It reduces reporting time by 100% and provides the predictive clarity needed to maintain a competitive edge in the Nigerian automotive market.

For Project details visit the GitHub link below :

https://github.com/aknnusi-analytics/Sales-Performance-Analytics

     David Vineyard Operations Analysis

Project Title: David Vineyard Nigeria – Water Production & Sales Dashboard (Excel)

Tools Used: Microsoft Excel (Formulas, Pivot Tables, Charts, Dashboard Design)

Description:
Designed and developed a dynamic Excel dashboard to monitor and analyze the daily production and sales performance of David Vineyard Nigeria Ltd, a bottled and sachet water manufacturing company located in Ibadan, Nigeria.

Objectives:

• Track daily production volume by product type (Sachet, 50cl Bottle, 75cl Bottle, 150cl Bottle).

• Monitor material usage vs. finished product output.

• Evaluate operator productivity and efficiency.

• Analyze sales performance and profitability per product.

• Automate reporting using Pivot Tables and visualizations.
  
  

Key Features:

• Cleanly structured Excel table for 1,800+ records simulating factory operations.

• Added calculated fields for costs, revenue, and profit margin.

• Created multiple pivot tables for insights such as:

  • Total Units Produced by Product Type

  • Operator Output Comparison

  • Daily Production Trend

  • Sales Revenue vs. Cost of Production

• Interactive dashboard with charts (bar, column, line, pie) for visual reporting.

• Applied formatting for clarity: cell borders removed, chart colors coordinated, slicers added for dynamic filtering.

Impact:
This project demonstrates my ability to transform operational factory data into a professional, automated dashboard for performance tracking and decision-making without Power BI. It reflects my strong command of Excel for business reporting.

https://drive.google.com/file/d/1vagrsZMjCvOHibXEbR4T80t3G0MHoflk/view?usp=sharing

https://docs.google.com/spreadsheets/d/1FKwOWgPnFPXnGQKTiFR_niBUz_5r0f-T/edit?usp=sharing&ouid=103045904432040812457&rtpof=true&sd=true