JD Sports Fashion Gains Near Real-Time SKU-Level Analysis, Runs Reports 18 Times Faster, Leverages Fact-Driven Merchandising to Outperform Competitors
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JD Sports Fashion Gains Near Real-Time SKU-Level Analysis, Runs Reports 18 Times Faster, Leverages Fact-Driven Merchandising to Outperform Competitors

  • Oracle Customer:  JD Sports Fashion Plc
    Location:  Bury, England
    Industry:  Retail
    Employees:  10,000
    Annual Revenue:  $1 to $5 Billion

JD Sports Fashion plc. is a leading retailer of branded sportswear and fashionwear with 900 stores and online business across a number of retail locations in the United Kingdom, Ireland, France, and Spain. The company owns many top brands, including Mckenzie, Carbrini, and The Duffer of St George, and sells many limited edition and exclusive designs from Adidas Originals and Nike. JD Sports is growing fast—organically and through acquisition—and revenue increased almost 20% in 2011.




A word from JD Sports Fashion Plc

  • "The combination of Oracle Business Intelligence Enterprise Edition, Oracle OLAP, and Oracle Exadata Database Machine gives us the insight and agility to continue outperforming competitors as we expand our footprint throughout Europe.” – Barry Loftus, Head of Business Intelligence and Application Development, JD Sports Fashion plc.

  • Maximize profitability in the competitive sports and fashionwear retail market by matching inventory to demand, identifying best sellers, tracking success of promotions, and being first to market in a fashion-driven business with typically short product lifespans
  • Enable 100 buyers, 120 merchandisers, business analysts, and country, regional, and branch managers to analyze up-to-date revenue, margin, like-for-like sales, running averages, and variance against plan for each of JD Sports’ 400,000 live stock-keeping units (SKUs) from any location
  • Scale analytical abilities to handle anticipated doubling of data volumes from 4 terabytes in 2012 to 8 terabytes in 2015 and growth in user numbers while increasing performance


  • Delivered weekly executive trading pack dashboards at 5:00 a.m. on Monday instead of by 3:00 p.m. or on Tuesday, which gave decision-makers total sales figures and stock levels for all brands, updated time-series calculations , and space and density analysis per store for each of JD Sports’ 10 divisions at the start of the week using Oracle Exadata Database Machine
  • Made dashboard data available to hundreds of users simultaneously with self-service drill-down using Oracle Business Intelligence Enterprise Edition
  • Provided merchandisers with response times of 15 seconds instead of two minutes when drilling into dashboards to update reports containing 40 KPIs, such as variance or year-to-date figures
  • Built new reports with changed parameters in under 30 seconds, a process that took up to 15 minutes using the legacy platform
  • Gained the ability to drill to SKU-level data in seconds, a process that was previously impossible due to lack of computing power, and optimized the ability of buyers and merchandisers to detect distribution voids and identify gap-filling opportunities
  • Created non-sellers report for each branch in 12 minutes instead of 30 minutes, which gave buyers and merchandisers the ability to identify least profitable items in near real-time and run promotions to incentive sales of poor performers or cancel supplier orders
  • Ran automated batch reports in 12 minutes instead of two hours, allowing teams to refresh critical transaction statistics per store, per item, or region whenever required
  • Built full OLAP cube in 150 minutes instead of five days, which enabled sales data to be refreshed rapidly to accommodate additional reporting dimensions, and added 100 new KPIs to the weekly trading pack without impact on processing time
  • Gave board members a consolidated view of all regions and divisions in multiple hierarchies from a single web page for the first time
  • Provided branch managers with daily sales and footfall figures and began rollout of in-store access to trading pack with drill-down access to each outlet’s performance data
  • Assimilated an additional 3 terabytes of data into the JD Sports data model in just one month following the acquisition of competitor retailer Blacks Leisure and tripled the number of business intelligence consumers with no impact on speed or availability
  • Purchased additional Oracle Exadata Database Machines for Oracle Retail and Oracle E-Business Suite environments to scale their performance to meet continued expansion activity and anticipated significant annual revenue.

Why Oracle

JD Sports chose Oracle Exadata Database Machine over IBM for its lower acquisition costs, dramatically higher performance, quicker time to value, and faster return on investment. The company ran proofs of concept for SQL reporting, OLAP reportingand batch processes on both platforms. JD Sports was able to build the OLAP cubefour times faster using Oracle Exadata Database Machine than with IBM x Series.

"Oracle Exadata beat IBM hands-down for performance in every category,” said Barry Loftus, head of business intelligence and application development, JD Sports Fashion plc.