Volume

Volume

Data Challenges / Solution

Business Brief

Our client is a Fortune 500 sports brand and retailer that has operations spread across the country

Geographies

Pan India – Different Seasons

Accounts

50+ Franchisee Accounts

Channels

Company Owned, Franchisee Owned, Digital, Multi-Brand Outlet, Factory Outlets

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 real-time visibility to key performance indicators

Once fully functional, the big-data solution should enable insights allowing management and store owners to take immediate action on KPIs at various points of sale.

Create the ability to spot trendy products

In a near real-time manner and ensure stocks are available in the right place.

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.

Communicate financial results, forecasts

Help others learn best practices from the best run stores

Identify what promotions are working

How can they be tweaked for maximum impact?

To create a repeatable process

Enable client to deploy this solution across multiple stores rapidly and cost effectively.

DATA CHALLENGES

issues

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

Steps taken

TEG team engages with the different stakeholders directly to access data and construct/append to the data warehouse on a regular basis

issues

Incomplete/Incorrect/Corrupt Data from Franchisee

  • Store names mismatch
  • Blank SKUs
  • Item sales not matching bill level sales
  • Missing store data
  • Duplicate data etc.

Steps taken

Setup an extensive data review on raw data, processed data, and final reports Captured business rules into data transformation engine

issues

Migration of stores from Retail software to another causing data integrity issues

  • Missing stores data
  • Duplicate data
  • Blank barcodes

Steps taken

  • 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

issues

Data for the Outright stores not in ERP system

  • Multiple vendors with different ERP systems
  • Difficult coordination across stakeholders

Steps taken

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

issues

Receiving data feeds in a timely manner, maintaining a weekly rhythm

  • Manual data feeds, not automated
  • 30% was not received on time

Steps taken

Regular Follow-ups, Monthly Governance meetings with Master Franchise with timely escalations to management

issues

Firewall Issues

  • Firewall rules blocked applications
  • Restricted IP access

Steps taken

Governance meetings with client

solution highlights

Our big data solution has the following features –

Reports

Product Analysis

Seasonal Sell-Thru

End of Season Sales

Monthly/Yearly Sales

Stock on hand

Sell-in vs.Sell-Thru

Biz Parameter

Store wise SKU

Missing store by Date

Initiatives Tracker

Comparable Stores Analysis

SKU Replenishment

Weekly Sales Tracker

Sales analysis Cube

Stock Cube

Advanced Analytics

Store Size Optimizer

Sales Forecast Model

Description

Sales by category,gender, sourcing, silhouette, silo; Drill down for units sold and ASP

Seasonal/overall 30/60/90 days sell-thru by gender,category,sourcing,product engine,top & bottom 10 Styles

Fresh/Discounted sales at the door level

Value realized, units sold, ASP, stock-on-hand by product engine & by category, gender, productivity

Inventory on a particular date at a size level

Comparison of the sales by Nike to store with the sales by stores to customers

Monthly/YTD Sales/Inventory analysis; Performance snapshot of the business for key parameters

SKU wise sales/stock for a particular store

Store wise dates that are missing in the tool

SKU wise 30/60/90 sell-thru for the initiative stores

Sales by product engine,category for comparable stores

Replenishment required for inter-store movement at a SKU level

Weekly sales by region, store classification

Custom analysis in your own format with various metrics like value, units, inward, outward etc.

Custom analysis for closing stock in your own format

Description

Identify the optimum size for a new store to maximize sales, across high street/mall locations

Predict the Sales in future based on the past trend/seasonality etc.