2. Profit Erosion
Leveraging Data Analytics and Strategic Programs to Enhance Operational Effectiveness

3. Ernie Deyle Senior Director, APP Safety & Enterprise Resiliency
Sears Holdings Management Corporation

4. Data Analytics – 4 cornerstones
Data Analytics, what does that mean?
Retail = data rich…but slow in churn, relevancy & thus usability
Data Analytics provides ACTIONABLE information in a TIMELY manner to the end user and/or executive to make INFORMED decisions to DRIVE performance & MAINTAIN the performance once it is achieved
Data Analytics, when used properly isolates & quantifies conflict with in the enterprise
Process = human actions (customers, associates, vendors)
Platform = systems that drive/assist in the process
Protocols = the policies and procedures governing the platform/systems and the processes

5. Data Analytics – 4 cornerstones
Data Analytics, targets behavior that impacts performance
Initial actions or lack of action that creates reportable data
Supporting behavior that interact with initial actions
Leading indicators are the DNA data sets that impact P&L Measure-ables
Data Analytics, the Measure-ables the DNA data
Lowest common denominator
Example hierarchy data pivots - item, category, supplier, major/minor department, terminal, cashier, manager, store, district, region, area, company
Example time pivot – day, week, period/month, quarter, rolling 12 weeks YTD v same pivot for LY (last year)
PTS (% of sales), Frequency ratios, Average Values, Distribution ratios (see case studies)

6. Case study 1 cs1 – national retailer
Promo coupon $10 off $25 to drive DPC – dollar per customer
$3.08 capture margin v before $4.39
Control group with similar purchase pattern – 10% off top valued item
$4.10 captured margin v before $4.06

7. Case study 2 cs2 – national retailer
private label launch with expanded department mix
private label impact on performance contribution models
sales improved (2.13% v 2.02%)
DPC improved ($4.91 v 4.43)
IPC improved (1.18 items v .90 items)
margin improved (35.14% v 27.24%)
MPIS improved ($1.46 v 1.35)

8. Lonndon Seely Senior Director, Specialty APP
Sears Holdings Management Corporation

9. MARGIN OUTLIER PROGRAM
Identify and Mitigate Profit Erosion at POS – WHY? LP to APP
Conduct Smart Investigations-Fraud? Operational?
Change behavior through policy, training, and assigning accountability

10. SALES REDUCING ACTIVITIES
Price Overrides
Percentage Off Coupons and Discounts
Dollar Off Coupons and Discounts
Refunds
Created the margin outlier stores and program details
FOCUS

11. REFINE EXCEPTION REPORT
EXCEPTION REPORT CYCLE
LOCATE DATA
LEARN THE BUSINESS
VALIDATE DATA
PROTOTYPE REPORT
FEEDBACK
INVESTIGATE
RESOLVE CASE(S)
REFINE EXCEPTION REPORT

12. RESULTS
Margin Improvement of $74.6 Million in fiscal year 2015 Q1
$5.18MM Q2
$15.89MM Q3
$23.42MM Q4
$30.12MM

13. Jennifer Zervas
Loss Prevention Analyst
At Home

14. Transitioning Brands Became At Home in 2014 100 locations in 2015
Garden Ridge started as a single store in 1979
58 locations in 2012
Technology dinosaur
Became At Home in 2014
100 locations in 2015
Incorporating metrics & sharing with stores

15. Evaluating the Business
Retail 20/20 reporting August 2015
Discounts
Initial 6-week avg. 2.5% of sales/store
Incorrect processing
Manager’s Overrides
5.06% sales
Estimated average $1.9 M in labor per year

16. Discounts Military E-mail Capture New Customer
gifted without ID verification
Capture
Incentivize return traffic
Awarded twice
New Customer
Printed for existing customers at the store

17. Correct and Monitor Significant impact within 4 weeks
Margin improvement of over 3.5 Million in 26 weeks
Projected to 7.75 million by anniversary date

18. Manager Labor Operate Smart & Scrappy
Manager’s Overrides accounted for 5.06% of all transactions
Change: raise threshold from $100 to $150 for refunds without a receipt
Change affected < 10 transactions per store per day

19. Labor Impact
All Manager’s Overrides reduced by 1%, stemmed from 10% reduction in overrides for non-receipted refunds
Gave managers back an estimated 31 minutes/day in each store
Projected re-allocation of $545,525/year, or a 28% adjustment

20. Summary
Large or small – Data Analytics can be scaled to impact profit erosion
Suggested targets: Price Overrides, Discounts/Coupons, Refunds, Manager Labor, exclusive products
Establish a baseline of data, to learn the business, and validate your findings
When systems are sophisticated – use a control group to test a program change so results are measured in the same economic environment
Or, impact a small percentage of transactions and monitor for change over time