One Size Does Not Fit All Using Size Analytics to Drive Sales Gale Weisenfeld VP, Planning / MIO...

One Size Does Not Fit All

Using Size Analytics to Drive Sales

Gale Weisenfeld

VP, Planning / MIO

Federated Department Stores

April 28, 2006

Agenda

Introduction– Company Overview– Business Challenge

Business Solution– Role of Technology– Implementation– Critical Success Factors

Collaboration– Change in the Supply Chain– CPFR

The Numbers Tell The Story– Business Example– Lessons Learned

Future Plans

About Federated Department Stores

One of the nation’s leading department store retailers Acquisition of May Company will create 800+ store

operation with projected retail sales in excess of $27 billion in 48 states, Guam, & Puerto Rico

Operates under the names of Macy’s, Bloomingdale’s, Macys.com, Bloomingdale’s By Mail

Support operation of Macy’s Merchandising Group is responsible for all aspects of Federated Private Label & management of FDS merchandising systems

Business Challenge

Accelerate Federated Department Stores

comp-store sales growth and increase the company’s profitability levels

Why Customers Don’t Buy

Have you ever gone shopping and found the perfect blouse / sweater / pants / shoes only to be told ‘sorry, we don’t have your size’

This is a missed sales opportunity of the worst kind when the customer is in our stores, wants to make a purchase, and can’t because we don’t have her size

While alternate product offerings at the style or color level might be substituted to complete a sale, this is seldom the case for size stockouts

Business Solution

Federated’s Size Selling Initiative was launched in 2002 to develop and implement solutions

that resolve the issue of size stockouts Drive regular price sales Reduce markdowns Improve margins Create a better shopping experience

Using Technology to Analyze Sales

Phase 1: Best Single Prepack Size Profiling Application (SPA) developed by Macy’s

Merchandising Group & Federated Systems Group Adjust Fashion Prepacks to better match customer

demand Track rate of sale on items to the size level

Size Measurement Calculations

Improve ‘match rate’ between orders & sales Analyze % of sales by size Analyze % of stock by size Objective: Determine how did we sell the product

when it first came in to our stores BEFORE we began to run out of sizes (Fresh Sales)

Calculating Match Rates

Variance = Stock % - Sales % Match Rate = 100% - Absolute Value of the Variance Example: 100% - 20% = 80% Match Rate

Size Sales % Stock % Variance %

S 12% 17% 5%

M 28% 33% 5%

L 38% 33% -5%

XL 22% 17% -5%

Total 100% 100% 20%

Applying Match Rates to Fashion Prepacks

Fashion Prepack quantity = 12 units

Size Original Prepack New Prepack

S 2 1

M 4 3

L 4 5

XL 2 3

Match Rate 80% 86%

Using Technology to Analyze Sales

Phase 2: Multi-Prepack Create location level clusters based on historical

sales patterns

Every store doesn’t need ‘the same 12 pack’ but how many prepacks is the ‘right number’– Every store isn’t an equal contributor to sales– Consider sales contribution by door cluster,

volume of program, & overall cost to supply chain when determining optimum number of prepacks

How many ways can you sort a 12 pack?

Prepack A

Prepack B

Prepack C

Prepack D

Prepack E

S 2 1 2 3 0

M 4 3 3 5 3

L 4 5 5 3 5

XL 2 3 2 1 4

Why 12?

Who was it that said 12 was the right number anyway?– 12 is an even number– As children, we learn to count by two’s– 12 hangars fits on a straight arm of a 4-way– ‘The box holds 12 pieces’

• Sometimes a slightly smaller (10 or 11) or slightly larger (13 or 14) prepack quantity can yield a significantly better match rate

Using Technology to Analyze Sales

Phase 3: ROI – Return on Investment Reporting

Questions we were asking ourselves– Did we make the right changes? – Do we have additional opportunities?– Are we making a difference?

• Evaluate sales performance against new prepacks

• Determine if further prepack refinement is necessary

Using Technology to Analyze Sales

ROI Reporting includes WAS / IS comparison to gauge ongoing impact of pack changes to key business metrics:– Regular Price Sales & Sell Thru by Size– Average Unit Retail by Size– Stockout at X % by Size– Markdowns by Size

By Location results are also available

System Development & Implementation

Phase 1: Best Single Prepack (S’02) Phase 2: Multi Prepack w/Location Clustering (S ’03) Phase 3: ROI Reporting (S’04)

Application currently deployed to approximately 100 users across all Federated divisions

Critical Success Factors

Incorporation of size analysis into the daily business process – Senior Sponsor (President, MMG)– Size analysis is not a special one-time project – Timing, coordination with market schedule– Increased workload before market meetings– Change Management culture change with

significant impact to business process – Clear definition of roles / responsibilities

Critical Success Factors

Collaboration– After gaining experience with Private Label and

having ‘wins’ to talk about, Federated is actively analyzing size selling for branded vendors and sharing our findings with our vendors

– Buying and allocating the right sizes is only the beginning of the process

• A genuine partnership between retailer and supplier is critical in order to maximize sales by size

Collaboration

Introducing Change to the Supply Chain – Vendors need to evaluate their ability to

implement change in the supply chain to support multi-prepack offerings

– Resistance & Obstacles to Change• ‘This is hard’

• ‘This is expensive’

• ‘I’m not the right person to make this happen’

• ‘Can my company execute this accurately?’

Collaboration

Achieving Change in the Supply Chain– Vendors are migrating to a multi-prepack business

model– Vendors offering multi-prepacks have made

modifications to reflect different / additional packs – If there is only a ‘national pack’ (best single

prepack), FDS is defining the pack Mutual Benefits

– Our vendors will share in the benefits of the work being done with size analytics via increased regular price sales and improved margins

CPFRCollaboration-Planning-Forecasting-Replenishment

CPFR diagrams & slides are courtesy of

Russ Brown, Russell CorporationFall 2005 AAFA ISC Presentation

CPFRCollaboration-Planning-Forecasting-Replenishment

CPFR involves more than you might think….

CPFR - - The cycle expanded

Where does CPFR fit in?

CPFR starts with a joint agreement

CPFR encompasses review and understanding of strategies & data on both sides of the

partnership

The forecast starts it all.Is size analytics part of this process?

CPFR - - Manage the exceptions

Identify and resolve exceptions to the forecasts– Orders– Receipts– Fill rates– Sales

What have we learned?

Our work with size analytics is ongoing Customers’ sizes are ever-changing Size Specs matter

– When is a large not a large?– Know your fit model

Things to consider– Vendor– Lifestyle– Price Point– Personality of the product– It’s not just about the numbers– Collaboration is key

Current Sizing Priorities

Collaboration with our market vendors– Now more than ever, as Macy’s becomes a

national department store, we need ‘right product, right place, right time, AND right size’

– The lead time to implement change in the supply chain is long, frequently 9-12 months. We need to work together to implement change faster.

Integration of size analytics into Federated merchandising systems in order to gain workload efficiencies– Ordering– Allocation

Discussion / Questions

Gale Weisenfeld

VP, Planning / MIO

Federated Department Stores

Email: gale.weisenfeld@macys.com