Business Brief

Our client is a Fortune 500 sports brand and retailer that has operations spread across the country,
1. Geographies - Pan India – Different seasons
2. Accounts- 50+ Franchisee Accounts
3. Channels- Company Owned, Franchisee Owned, Digital, Multi-Brand Outlet, Factory Outlets
4. Retail Outlets – 700+
The client wants to create a big data setup that provides a single version of the truth for Sales, Merchandizing, and Finance teams. Specifically,

  • Provide hassle-free, real-time visibility to key performance indicators; or KPIs at various points of sale; allowing management and store owners to take immediate action. Once fully functional, the big-data solution should enable insights.
  • Create, analyze and maintain Sales Performance reports; recap and analyze actual sales results to plan, identify risks and opportunities to business and recommend strategies to achieve financial goals
  • Identify what promotions are working; how can they be tweaked for maximum impact?
  • Create the ability to spot trendy products; in a near real-time manner and ensure stocks are available in the right place
  • Communicate financial results, forecasts, and action plans to stores and cross-functional partners; serve as a resource in helping others learn from the best run stores
  • To create a repeatable process; so that the client can deploy this solution across multiple stores rapidly and cost effectively
Data Challenges

Issues Steps taken
Volume of Raw data comes from,
  • Franchisee/Partner data in both Push & Pull form- Emails, Portals, FTP
  • 2-3 million rows of data every week from varied sources
TEG team engages with the different stakeholders directly to access data and construct/append to the data warehouse on a regular basis
Incomplete/Incorrect/Corrupt Data from Franchisee
  • Store names mismatch
  • Blank SKUs
  • Item sales not matching bill level sales
  • Missing store data
  • <span”>Duplicate data etc.
Setup an extensive data review on raw data, processed data, and final reports
Captured business rules into data transformation engine
Migration of stores from Retail software to another causing data integrity issues
  • Missing stores data
  • Duplicate data
  • Blank barcodes
  • Master Franchise and TEG setup a special governance to provide visibility into the transition plan
  • Data from stores in transition were handled separately with additional checks to account for the discrepancy
  • Manual checks were also put in place
Data for the Outright stores not in ERP system
Data for the Outright stores not in ERP system A user workshop was conducted and the systems were configured by TEG team to extract data in the desired formats
Receiving data feeds in a timely manner, maintaining a weekly rhythm
Regular Follow-ups, Monthly Governance meetings with Master Franchise with timely escalations to management
Firewall Issues
Governance meetings with client
Solution Highlights

Our big data solution has the following features -

Reports Description
Product Analysis
Sales by category,gender, sourcing, silhouette, silo; Drill down for units sold and ASP
Seasonal Sell-Thru
Seasonal/overall 30/60/90 days sell-thru by gender,category,sourcing,product engine,top & bottom 10 Styles
End of Season Sales
Fresh/Discounted sales at the door level
Monthly/Yearly Sales
Value realized, units sold, ASP, stock-on-hand by product engine & by category, gender, productivity
Stock on hand
Inventory on a particular date at a size level
Sell-in vs.Sell-Thru
Comparison of the sales by Nike to store with the sales by stores to customers
Biz Parameter
Monthly/YTD Sales/Inventory analysis; Performance snapshot of the business for key parameters
Store wise SKU
SKU wise sales/stock for a particular store
Missing store by Date
Store wise dates that are missing in the tool
Initiatives Tracker
SKU wise 30/60/90 sell-thru for the initiative stores
Comparable Stores Analysis
Sales by product engine,category for comparable stores
SKU Replenishment
Replenishment required for inter-store movement at a SKU level
Weekly Sales Tracker
Weekly sales by region, store classification
Sales analysis Cube
Custom analysis in your own format with various metrics like value, units, inward, outward etc.
Stock Cube
Custom analysis for closing stock in your own format
Advanced Analytics Description
Store Size Optimizer
Identify the optimum size for a new store to maximize sales, across high street/mall locations
Sales Forecast Model
Predict the Sales in future based on the past trend/seasonality etc.

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