Project 04 · Excel · Business Intelligence

Adventure Works
MS-Excel Dashboard

Two interactive dashboards analysing $307M in sales across 4 years, 606 products, and 6 relational tables

ToolMicrosoft Excel (.xlsm) with macros
DatasetAdventure Works Database
Analysis Period2005 – 2008 (4 years)
Dashboards2 (Time Series + Sales Analysis)
Tables Modelled6 relational tables via Power Pivot
$307MTotal revenue (2005–2008)
$126MTotal profit generated
41.1%Overall profit margin
606Products analysed
39.4%Profit from 50+ customers
The project

Business Context

Adventure Works is a fictionalised manufacturing and retail company whose multi-year transactional data is widely used in BI training. The challenge here was not just to build charts, it was to model six relational tables in Power Pivot, write custom DAX measures for KPIs, automate dashboard interactivity with Excel macros, and surface actionable insights for four distinct stakeholder groups: executive leadership, marketing, finance, and product teams.

Dashboard 01

Time Series Analysis

Revenue, profit and transaction trends across years, quarters, and days of the week, with YoY comparisons and interactive year slicer

Dashboard 02

Sales Analysis

Product colour, top customers, gender split, and age demographics, drilling into where profit is actually concentrated across 606 products

Live dashboard

The Dashboard

Built entirely in Excel with Power Pivot data modelling, DAX measures, VBA macros, and interactive slicers. The dark theme, donut chart, and KPI tiles with YoY change indicators were all built from scratch.

Adventure Works Sales Analysis Dashboard, Excel
Adventure Works Sales Analysis Dashboard · Microsoft Excel · Macro-enabled (.xlsm) View on GitHub ↗
Findings

What the Data Revealed

Dashboard 01, Time Series

$307.09M total revenue, $126.29M profit at a 41.1% margin across 2005–2008. Revenue and profit both on a consistent upward trajectory over the four years.

Q2 was the strongest quarter, contributing 31% of total profit ($39.30M). Q3 was the weakest at only 19%, indicating a significant mid-year seasonal dip.

2007 delivered the highest single-year profit. 2007 and 2008 tied for highest revenue at $102M each, while 2008 recorded the most individual transactions, indicating a growing but slightly lower-margin customer base.

Wednesday–Friday drove 43.8% of total profit, the prime selling window. Weekdays combined accounted for 79% of total profit vs 21% for weekends.

Dashboard 02, Sales Analysis

The top 4 products contributed 20% of total profit across a 606-product catalogue, a classic long-tail distribution where a tiny fraction of products carries disproportionate weight.

Black, red, and silver products combined drove 75% of total profit. Black was the single highest-performing colour. Colour is a meaningful proxy for product tier and customer preference.

Top 5 customers contributed only 0.28% of total profit, revenue is broadly distributed across the customer base. No single customer concentration risk exists.

Customers aged 50+ contributed 39.4% of total profit, the single most valuable demographic segment. Gender split was near-equal (50.4% female, 49.6% male).

Analysis

4 Charts. 4 Business Questions.

Chart 01
Annual Revenue & Profit (2005–2008)
How did revenue and profit trend year-on-year, and which year was the peak?
Finding: Both revenue and profit grew consistently from 2005 to 2007, with 2007 delivering the highest profit of any single year. Revenue plateaued in 2008 at the same $102M level as 2007, but transaction volume continued growing, suggesting a slight pricing or mix shift. The 41.1% average margin held remarkably stable across all four years, indicating strong cost control.
Chart 02
Quarterly Profit Distribution (% of Total)
Which quarter is the revenue engine, and where is the seasonal opportunity?
!
Finding: Q2 dominates with 31% of total profit ($39.30M), driven by spring purchasing activity. Q3 is the weakest at 19%, a 12 percentage point gap between the best and worst quarters. This Q3 underperformance is the single largest lever for improving annual revenue consistency. Targeted mid-year promotions could materially reduce this volatility.
Chart 03
Profit by Product Colour
Does product colour predict profitability, and should supply decisions reflect colour performance?
Finding: Black, red, and silver products combined account for 75% of total profit across the catalogue. Black alone is the single most profitable colour. This is not merely aesthetic, it reflects which product lines (bikes, accessories) are highest margin. Supply chain and product development decisions should weight toward these three colours when expanding the catalogue.
Chart 04
Profit by Customer Age Group
Which age segment drives profit, and where should loyalty and upsell investment go?
Finding: Customers aged 50+ contribute 39.4% of total profit, by far the most valuable demographic cohort. This segment likely skews toward premium product lines and higher-value orders. The near-equal gender split (50.4% F / 49.6% M) means gender is not a meaningful targeting variable, but age most definitely is. Loyalty programmes, premium tier offerings, and upsell campaigns should be designed with the 50+ segment as the primary audience.
Technical depth

Excel Techniques Used

Power Pivot
Modelled 6 relational tables (FactInternetSales, DimProduct, DimCustomer, DimDate, DimGeography, DimSalesTerritory) with defined relationships, no VLOOKUP chains needed
DAX Formulas
Custom KPI measures: YoY revenue change %, profit margin %, quarter contribution %, and running totals, all calculated dynamically against slicer selections
Excel Macros (VBA)
Dashboard automation, macro-driven navigation between dashboard views, dynamic chart refresh on slicer change, and KPI tile colour-coding based on performance thresholds
Pivot Tables & Slicers
Multiple connected pivot tables driving all dashboard charts simultaneously. Year, quarter, country, and product colour slicers filter all visuals in real time
🔗
Data Modelling
Star schema design with FactInternetSales as the central fact table and 5 dimension tables. Relationships defined on SalesOrderNumber, ProductKey, CustomerKey, DateKey
Advanced Chart Design
Donut charts with centre labels, combination bar/line charts, KPI tiles with conditional delta arrows, custom dark theme applied consistently across all chart elements
IF
Conditional Logic
IF / IFS functions for age band grouping, performance tier classification, and weekend vs weekday segmentation, feeding directly into pivot tables
🎨
Dashboard Design
Professional dark theme with teal/grey/white palette, custom icon set, dynamic YoY change indicators with colour-coded arrows, and country filter panel
So what?

Business Recommendations

01

Capitalise on Q2 with increased marketing investment

Q2 contributes 31% of annual profit, nearly 1.6× the weakest quarter. Marketing and promotional budgets should be front-loaded into Q1/Q2 to maximise returns during the natural peak. Spring campaigns, early-bird promotions, and partner co-marketing should all be timed to the Q2 buying window.

→ Marketing & Executive Leadership
02

Develop targeted Q3 promotions to close the seasonal gap

The 12-percentage-point gap between Q2 (31%) and Q3 (19%) represents the largest single revenue optimisation opportunity. A structured mid-year promotion, flash sales, bundle offers, or loyalty reward activations, targeting the high-value 50+ segment specifically in July and August could meaningfully narrow this gap.

→ Marketing & Finance
03

Schedule campaign launches and product drops on Wednesday–Friday

Wednesday–Friday drives 43.8% of total profit. This is not coincidence, it reflects mid-to-late-week purchase decision behaviour. Product launches, email campaigns, paid media pushes, and time-limited promotions should all be timed to land on Wednesday or Thursday to capture the peak engagement window.

→ Marketing & Product
04

Prioritise black, red, and silver product lines in supply and development

These three colours drive 75% of total profit from a 606-product catalogue. This concentration is a signal about which product categories and price tiers are resonating. New product development should be evaluated against the traits of these high-performing lines, and supply chain allocation should reflect their disproportionate revenue contribution.

→ Product & Supply Chain
05

Build a dedicated loyalty programme for the 50+ age segment

Customers aged 50+ generate 39.4% of profit from what is likely a smaller share of total customer count, making them the highest lifetime-value cohort. A tiered loyalty programme with premium product access, early release offers, and personalised service would formalise this relationship and reduce churn in the most profitable demographic segment.

→ CRM & Marketing