6/7/2012

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Delivering Supply Chain Results through

Integrated Demand Sensing and Shaping

Capability

Kimberly-Clark Corporation

June 14, 2012 Scott DeGroot

A Global Health and Hygiene Leader

56,000-plus employees worldwide

$20.85 Billion in Net Sales in 2011

Well-known global brands HUGGIES® KLEENEX® SCOTT®

KOTEX® PULL-UPS® DEPEND®

#1 or #2 position in more than 80 countries

Nearly one-quarter of the world’s population use our products daily

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Our Vision

“Lead the world in

essentials for a

better life”

Our Businesses

Europe Consumer International Consumer

North America Consumer

Health Care K-C Professional

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Sales & Operations Planning North American S&OP

Trade Marketing, Revenue Strategy Demand Planning, Sales & Planning

Technology Supply Planning, Gap Management

One set of numbers across all functions and businesses: Sales, Finance, Marketing, Production & Capital Planning, Capacity, etc.

Adult/Fem Care Family Care Baby/Child Care

S&OP Cycle Moved from reactive to collaborative

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Monthly Cycle

Demand Review

Business Planning TL

/ Supply Chain Planning

Executive S&OP Meeting

North Atlantic Supply Chain VP / Customer

Development VP

Consumer Portfolio Management

Meeting

President, NACP

Capacity Review/ Gap Mgmt

Operations Director/ Sr

Specialist

S&OP Improvements Demand Review:

•High & Low Side Risks

Capacity Review /Gap

Management:

•Target Utilization Strategy

•Risk Analysis

•Metrics

•Decision Tracking

Executive Review:

•Quantify and $ decisions

• Closing the loop on

decisions

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Supply Chain to Value Chain

Start at the

basket Store needs

the product Ship to

store

Ship to

customer

warehouse Ship to K-C

warehouse

Make

New K-C View

Supplier

Old K-C View

The K-C Demand Journey

2009 – 2011

Short-Term Demand Sensing

• Terra Technology

2010 – 2012

Long-Term Demand Sensing and Shaping

• Retail Data Strategy (RSi)

• Trade Promotion Management and Predictive Analytics (Promax)

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Short-term Demand Sensing

• Terra Technology – POS, POS Forecast

– DC inventory & withdrawals

– Store Inventory

– 2010 Go-Live

• Safety stock process tied to Terra Forecast error

• Forecast level = code/location/daily

10-Oct 10-Nov 10-Dec 10-Jan 10-Feb

1 Week Horizon 2 Week Horizon

Long Term Sensing – Retailer Data

Leveraging DSR Capability to drive results • Better execution at retail shelf

– Promotions, rollovers, base volume, category management

• Supply chain execution

– Right Product, Right Location, Right Time

Results: • Analysis time reduced from

3-4 weeks to 3 -5 days • Increased speed to market

on new items by 40% • Everyday In-stock:

Improved by 4.5% • Promotional In-stock:

Improved by 2.0%

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Shelf-Back Replenishment Initiative Scope & Justification

Scope Store/shelf replenishment capability: Extends the accountability of the KC Supply Chain to the retail store/shelf

Justification • Improved store in-stock • Reduced lead-time to replenish DC’s • Improved promotional sell through • Reduced store inventory • Indispensible Partner

Store/Shelf-Back Replenishment

• Our Hypothesis:

– If we access store/shelf level information and develop actionable recommendations for product flow, then we will increase retail in-stock with lower inventory and cost

NOTE: This is easy to say, but VERY hard to do

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Deliverables

• Assessment of opportunity for top customers

• Methodology for calculating the ROI by customer

• Roadmap for phased implementation

• Definition of store/shelf replenishment processes

– Customer Specific attributes

• Evaluation of current tools and processes (Phase II)

– Data requirements

– Everyday replenishment

– Promotion planning and execution

Customer Capabilities

Must have’s

– Share DC/store level data

• POS, inventory, in transit/on order, forecast

– Store/shelf in-stock is key measure of supply chain performance

– Willing to execute recommendations

– Shared vision for business process and roadmap

– Executive sponsorship from retailer leadership

– Access to retailer counterparts

– Methodology for sharing data and insights

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Customer Capabilities

• Nice to have’s

– Direct access to replenishment tool and ability to adjust settings

– On-site imbedded at the customer location

– Alignment to the sales team and/or forecasting function:

• Formal ties to action insights for value in KC

• Tools and processes connected to Retail Operations teams

– VMI helps

Return on Investment Model Customer #1 Customer #2

Gross Sales $831 $456

% Promotion 42% 15%

Store in-stock - turn 92% 95%

Store in-stock - promo 89% 86%

Out of Stock factor 48% 48%

Turn sales increase $8.7 $5.6

Promo Exec. increase $14 $56

Total Sales Increase $32 $17

- variable contribution $5 $9

Profit from Sales $27 $8

Damage % 5.6% 8.1%

Store Count 800 3000

Opportunity / store $0.67 $0.31

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K-C’s past approach

• Correcting retailer perpetual inventory errors

• Finding distribution voids

Reduce out of stocks

+1-2% revenue

• Accelerating turns per linear facing by understanding consumer preferences and managing by store clusters

Increase sales

+1-2% revenue

• Pushing real-time consumption information into the demand planning process

Improve demand planning

+13% accuracy

• Proactively managing shipments and orders for promotional, seasonal, and other expiring inventory

Decrease buybacks

10% decrease

• Partnering with Retailers: meet reporting mandates; attain category advisories; enable CBAs to do ad-hoc reporting without data cleansing tasks; consistent KPIs

Add facings vs comp.

+1% revenue

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Best Practices • Develop forum for best practice sharing

– Internal first; external quickly – Meetings with regular cadence – Rotating leadership – Sharing wins

• Align on “standard work” where possible – Executional Customer Replenishment teams using SharePoint to drive

consistent process – Leverage with other teams

• Opportunity for common platform for data analytics – Some are dictated by the customer – Align with IT Retailer Data Strategy initiative – Tool execution opportunity – leverage standard back-office where possible

Process Flow Data Source Data Elements

RSI (or other tool) • Daily Store POS (baseline)

Customer Data • Daily store on-hand/on-order inventory • Store-Item facings • Min Presentation Target • DC on-hand

Spreadsheet (Ad-hoc) • Store level forecast

1. Analyze data &

determine store item inventory deployment

recommendation

2. Complete store item

deployment recommendation

template

3. Collaboration meeting

with Buyer/Forecaster/Vendor

3B. Confirm DC IOH can

support inventory deployment

4. Store inventory deployment is

executed by the customer

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Real Customer Wins

• Loss sales for a recent promotion were less than 1% vs. 7% previously

• Implemented a phased DC replen inventory resulting in 10% less inventory on the SKU

• Developed a process to deplete inventory on codes that transition out of the plan-o-gram

• Identified 1000+ stores that needed inventory prior to the event to support the forecast.

• Sales increase of 17% on sell-thru – SCOTT Towel 275% – COTTONELLE Bath 240% – Led Problem Solving session to identify root cause and implement

countermeasure to improve forecast compliance during next Ad • Week prior to Easter had strong store traffic / need to adjust forecast in

future

Challenges / Lessons Learned

– People • Collaborating customers

• Aligning & organizing internal & external resources

– Processes • Streamlining / standardizing

– Systems / Tools

– Data • New data requirements – industry standards

• Existing data quality

• Timeliness / latency in sharing

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• Trade Promotion Management and Predictive Analytics

• Capabilities – Optimize Demand Variability thru Demand Modeling

– Scenario Planning

– Trade ROI & post-event analytics

Long Term Sensing and Shaping thru Trade Promotion

Future Capabilities

• Improve Inventory Management

– More robust inventory modeling tools

– Supply Chain/SKU Segmentation

• Customer Forecast Collaboration

• Continue our Lean Progression across the Value Chain

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Supply Chain to Value Chain

Start at the

basket Store needs

the product Ship to

store

Ship to

customer

warehouse Ship to K-C

warehouse

Make

Technology Connects Information Flow

Supplier

Terra Technology

APO

RSi

Promax

gATP

Why?

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Our Ambitions by 2015 • Be recognized by our customers as

being the best in value chain capabilities and thought leadership: – Top tier customer scorecard

performance • Superior on-shelf supply, lower

value chain costs, lower inventory and lead-time

– Incremental $300 million top-line sales from supply chain improvements • Primarily driven by retail in-stock

improvements

– $100 to $200 million in inventory and cost improvements

Low Inventory

Low Cost

High In stock