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ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
ECR Europe Forum '05. Category Management in a limited data environment. Introduction
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ECR Europe Forum '05. Category Management in a limited data environment. Introduction

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Category Management in a limited data environment: …

Category Management in a limited data environment:

Category Management has been one of the most successful ECR tools over the past decade. At its core is what can be labour-intensive collation of accurate consumer information from many different data sources. But what if some data is missing? Learn how to maximize the benefits of Category Management in a limited data environment.

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  • 1. ECR - Starter seminar “Category Management in a limited data environment” - April 26th 2005 – PARIS Copyright © 2005 Accenture. All Rights Reserved. Accenture, its logo, and Accenture High Performance Delivered are trademarks of Accenture.
  • 2. Agenda Category Management in a limited data environment – Introduction - Herve Dehareng, Accenture London Case 1: ‘Sharing the Benefits of Category Management across a wider platform of Retailers’ - Joe Kearns, Diageo - Terence O'Hagan, Diageo Ireland - Pat Maginn, Quinns Spirits Grocers and off-sales Case 2: Category Management via ‘Joined Business Planning’ - Anton Voichik, Gillette Russia - George Nassar, Gillette Russia - Ibrahim Ozturk, Ramstore Russia (Video) 2
  • 3. The category management challenge • Category Management is a capability aimed at delivering the optimal ROI via the selection of the most effective / efficient growth drivers mix Category management objective: 3 key components for the creation of a real successful capability : Quality Way of working / Other Assortment Processes Availability Price Optimal On-going ROI? Capability Persuasion Promotion Tool / Data People / analysis Organization Space Visibility 3
  • 4. Category management holistic process – ECR 1996 • Definition: “Retailer/supplier process of managing categories as strategic Business Units, producing enhanced business results by focussing on delivering consumer value” 8 steps process Consumer driven Fact based Category Definition Category Role Process oriented Collaboration Category Review Category Assessment Category A Category Perf. Measures Category B Category C Category Strategies Integral profit Category Tactics Cat. Plan Implementation 4
  • 5. From a holistic process to a day-to-day approach – ECR 1999 • Summary of 4 step Approach: 1 2 3 4 Define category Acquire data Define your Develop and using consumer and analyse role in the implement decision tree category category plans Acquire Data: • Identify data requirements Supplier portfolio 1 2 • Identify existing data Retailer Develop • Conduct gap analysis Strategy Category Plans • Elaborate acquisition plan Category Retailer Analyse Data: • Use robust and repeatable 3 Implement 4 Review model Category Category • Logical structure to aid the Plans Performance day to day category Competitor management process portfolios 5
  • 6. Web technology to support day-to-day category management – ECR 2001 • Summary of collaborative web-enabled best practices in Category Management Desired Improvements: Challenges: • Lack of trust • Automatic data feeds • Highly labour intensive • Ongoing activity • Too complex • More collaboration • Poor in-store execution • Clear communication to store personnel Collaboration Better, quicker CM Best Practices decisions (Industry) Standards Daily collaboration Proce Plann Sellin ing Better store ss Automated Data g Feeds execution Web technology 6
  • 7. Category Management needs evolution Increased need for “specific” data Need for rigorous approach and innovative solution Required level of details Category management in Category data - General Bronze Detailed level of analysis Limited data environment Too Not much data enough data Silver Need to: 1/ Follow a rigorous approach in selecting the required data Specific Gold 2/ Develop innovative solutions to gather + the required data where they are available 7
  • 8. 1. Rigorous approach: Upfront fact-based validation of statements A/ Upfront fact-based validation of statements Retail Perspective Brand / consumer Perspective Category Management Suggested Validated Statements Hypotheses Shopper Hypotheses Perspective Supply Perspective Approach results • Guarantee that any category management project is based on facts and not misleading statements • Huge gain of time in category management workshops where each subject matter expert has his own view of the category growth drivers • Increased level of usability / connection to execution 8
  • 9. 1. Rigorous approach: structure data / research acquisition plan B/ Structured data acquisition plan Define List data / Hypothesis researches List Analyse Plan & Validation required “in-house” Gap Activate process data / Acquisition researches Approach results • Better use of data / research budget • Creation of a category management knowledge database structured according to specific hypotheses 9
  • 10. 2. Innovative solutions: Access to insight in limited data environment There are many cases where the environment can be “data limited”: I. Data unavailable a. No data provider Gillette / Ramstore b. No access to data source - case 2 II. Incomparable data III. Data acquisition too expensive IV. Too short in time V. Analysis scope too large / disparate Diageo / Quinns Spirits case 1 … an innovative solution is therefore required to access to the necessary insight 10
  • 11. Your Questions Introduction Gillette - Ramstore ? Diageo – Quinns Spirits 11
  • 12. ECR - Starter seminar “Category Management in a limited data environment” Appendix - April 26th 2005 – PARIS Copyright © 2005 Accenture. All Rights Reserved. Accenture, its logo, and Accenture High Performance Delivered are trademarks of Accenture.
  • 13. re ss pr og k in Wor ECR Paris Click to add title
  • 14. The challenge and environment Category Management Beverage Industry in Ireland: area of opportunity: Required data/insight: Areas of category Retail data at store level: management success with key > Space management to reduce retailers off-sales/out-of-stocks > 1. Plan-o-grams > 2. Visibility > Merchandise Plan-o-grams > 3. Shopping environment according to the shopper segmentation > Space allocation > Planogram > Implement shopper decision > Shopper decision tree tree > Specific store requirements How do we share our Category Management Successes with > Ability to Build/adjust plans at store level ⇒ Too many POS to be handled 66% of the market – i.e. small retailers?
  • 15. Solution Develop a tool and use sales force to assist in improving insight: Why? > Regular visits/calls > Weekly to monthly > Relationships already established > Regional difference understood > Eager to learn Category Management principles How? > ‘Driving Shopper Satisfaction’ > ‘Tools of the Trade’ > Training to sales force
  • 16. ress rog p k in Wor RAMSTORE & GILLETTE Oral Care Category Management Project Anton Voichik National Key Account Manager Kirill Liseev Oral Care Business Director
  • 17. The category management opportunity and the need for data / insight Oral care category in Category Management Russia: Required data/insight: area of opportunity:  Category growth slowing Retail data at store level: down  Pruchase frequency  Space allocation  Strong consumer upgrade to premium products  Product assortment  Nationally growth has been  Promotion mix driven by distribution  Shopper / consumer education  On-going education expansion at POS  Oral-B has strong leading position in manual and power oral care Shopper / consumer insight:  Oral B has the expertise to  Footfall grow the overall cake and drive oral care category  Research at POS level
  • 18. Limited availability of required data Required data/insight: Possible sources of information: Retail data at store level: Limited data environment:  Space allocation  Agencies: - Data not complete - Data not ready  Product assortment  Promotion mix  Sales force: - Too time consuming  On-going education  Retailers: - Data not shared with suppliers Shopper / consumer insight: Limited data environment:  Agencies: - Research not ready - Analysis too long in  Research at POS level time versus deadlines
  • 19. Oral Care solutions 1: Join Business Plan Gillette Oral JBP Care JBP strategy articulated around the expected category management key growth drivers: – Increase turnover and profit via maximizing frequency of purchase – Shopper and consumer education via on shelf communication – Increase footfall via life style images  Access to data:  Keyallocation JBP:  Space data to deliver  Retailer: Data shared with  Product assortment Gillette as preferred suppliers  Promotion mix  On-going education
  • 20. Solutions 1/ Joined Business Plan: The development of a Joined Business Plan with a strategy articulated around the expected key growth drivers: – Increase turnover and profit via maximizing frequency of purchase – Shopper and consumer education via on shelf communication – Increase footfall via life style images ... enabled the sharing of information including the one required to better develop category management 2/ Use corresponding and existing researches developed in other comparable environments: Use of Gillette French shopper and consumer researches as a first basis and filter to better understand and suggest: – Consumer consideration set – Attraction of shopper – Selection process – Trade up and frequency habits ... Further developed and validated by local researches
  • 21. Solutions 1/ Joined Business Plan: The development of a Joined Business Plan with a strategy articulated around the expected key growth drivers: – Increase turnover and profit via maximizing frequency of purchase – Shopper and consumer education via on shelf communication – Increase footfall via life style images ... enabled the sharing of information including the one required to better develop category management

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