Data Analytics Solution for Advanced Sales Analysis across 12,000 Stores

Data Analytics Solution for Advanced Sales Analysis across 12,000 Stores
SKUs Tracked

150+

SKUs Tracked

Retail Chains Covered

12

Retail Chains Covered

Stores Monitored

12,000+

Stores Monitored

Automated Data Processing

4x

Automated Data Processing

Background The Client Challenge

Our client is a multinational consumer goods corporation operating across more than 180 markets with over 800 million customers and 55,000 employees worldwide. One of the company's national branches was responsible for distributing 150+ SKUs through a marketing channel comprising 12 large retail chains and 12,000 stores.

To perform effective sales analysis, the branch had to collect data from retailers in multiple files and formats a time consuming process that significantly reduced analyst productivity and failed to provide a holistic view of sales performance. The key challenges included:

  • Sales data arriving from 12 retail chains in inconsistent file formats with no automated consolidation process
  • No unified view of sales-in, sales-out, and stock data across all 12,000 stores and 150+ SKUs
  • Analysts unable to identify sales trends, compare SKU or store performance, or estimate growth potential without extensive manual effort
  • No automated KPI calculation metrics such as sales growth by store or period required manual computation and were prone to errors
  • No self service analytics capability for the sales and marketing teams every analysis request required significant manual data handling

The company partnered with Versich bringing 10+ years of expertise in data analytics and BI services to design and build a unified data analytics solution that would process and consolidate all retail sales data and deliver advanced sales analysis capabilities across the full store network.

Our Solution

Web Client

Web Client

  • A web based tool installed on the application server (IIS) enabling sales and operations users to upload, view, and edit sales data files submitted by retail partners
  • Roll back functionality allowing users to revert previously uploaded files when errors are identified
  • Upload log visibility users can review the full history of all file uploads and identify any processing issues
  • Manual trigger to initiate the processing of data from the Data Warehouse into OLAP cubes when required outside of the scheduled refresh cycle

Data Warehouse

Data Warehouse

  • A centralised MS SQL Server database storing all retail sales data submitted by the 12 retail chain partners serving as the single source of truth for all downstream analytics
  • Three core data categories stored and structured for analytical processing: sales-in (quantity of products sold to a store), sales-out (quantity of products sold from a store), and stock (quantity of products currently stocked in each store)
  • Data validation and quality checks applied during ingestion to ensure consistency and accuracy across all 12,000 store records and 150+ SKUs
  • Structured data preparation layer transforming raw retailer submissions into a clean, analytics ready format for processing by the Analysis Services engine

Analysis Services

Analysis Services

  • An MS SQL Server Analysis Services (SSAS) engine aggregating monthly and weekly sales data from the Data Warehouse into a multidimensional OLAP cube model
  • OLAP cube structured across multiple dimensions including time periods, the retail chain store hierarchy, and SKU categories enabling fast, flexible analytical queries across the full dataset
  • Automated calculation of sophisticated KPIs including sales growth for a specific store or SKU during any selected time period removing the need for manual metric computation
  • Aggregated analytical output transmitted to the front-end reporting application (Power Pivot for MS Excel) enabling sales and marketing analysts to run advanced self-service analysis directly from Excel
  • Scheduled data refresh cycles configured to keep all OLAP cube data current with the option for manual refresh initiation via the Web Client when needed
  • Sales trend analysis, SKU performance comparison, store-level benchmarking, and growth potential estimation all enabled through the OLAP cube and front-end analytical interface

Business Impact

Unified Sales Data Across All 12,000 Stores

Unified Sales Data Across All 12,000 Stores

All sales data from 12 retail chain partners previously collected in inconsistent file formats with no unified view is now consolidated into a single MS SQL Server data warehouse, providing one reliable source of truth for all 12,000 store records and 150+ SKUs.

Automated KPI Calculation and Sales Insights

Automated KPI Calculation and Sales Insights

Sophisticated KPIs including sales growth by store, SKU, and time period are now calculated automatically by the OLAP engine, replacing manual spreadsheet computation and enabling the sales team to identify top performing stores and products instantly.

Self Service Analysis for Sales and Marketing Teams

Self Service Analysis for Sales and Marketing Teams

Sales and marketing analysts can now run advanced self-service analysis directly from Power Pivot for MS Excel querying sales-in, sales-out, and stock data across any combination of store, SKU, retail chain, and time period without IT involvement.

Foundation for Optimised Sales and Marketing Strategy

Foundation for Optimised Sales and Marketing Strategy

With full visibility into sales trends, store performance, and SKU growth potential, the company's leadership can now make faster, evidence-based decisions on sales strategy, marketing investment, and retail partner management.

REVIEWS

What Clients Say About Us

5.0
Full starFull starFull starFull starFull star

We hired Versich to rebuild our analytics stack after an internal project stalled. They came in, assessed the situation quickly, and delivered production-ready Power BI dashboards within weeks. Their DAX knowledge and data modelling skills are exceptional.

Marcus Webb

CTO
5.0
Full starFull starFull starFull starFull star

Versich understood our finance workflows from day one. They built dashboards that connected directly to our ERP and gave our leadership team real-time visibility into cash flow, margins, and budget vs actuals. The quality of the work and the speed of delivery were both outstanding

Priya Nair

Finance Director
5.0
Full starFull starFull starFull starFull star

Before Versich, our reporting was scattered across spreadsheets with no single source of truth. They built us a Power BI environment that connects our warehouse, finance, and sales data in one place. Our operations team now makes decisions in hours instead of days

Daniel Okonkwo

Head of Operations