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Adopting Analytics for Decision Making in Retail презентация
Содержание
- 1. Adopting Analytics for Decision Making in Retail
- 2. AGENDA Analytics: A business reality now
- 3. Analytics: A business reality now Focus is
- 4. Analytics in Retail Opportunity to achieve competitive
- 6. Why do we need Analytics? Pain Points
- 7. Why do we need Analytics?
- 9. Implementation Plan HR Analytics
- 10. HR Analytics HR
- 11. Fraud Analytics Cultural Assessment Understanding activity Patterns Continuous monitoring & innovation
- 12. Supply Chain Analytics Inventory Management Sales Forecasting
- 13. Marketing Analytics Evaluate consumer purchasing
- 14. Infrastructure Requirements Developing a CoE Dedicated
- 16. Expected Benefits Our YOY revenue growth will
- 17. Taking the next step… Need your
- 18. Thank You
AGENDA Analytics: A business reality now Why do we need Analytics? Implementation Plan Expected benefits Taking the next
Слайд 2AGENDA
Analytics: A business reality now
Why do we need
Analytics?
Implementation Plan
Expected benefits
Taking the next step…
Implementation Plan
Expected benefits
Taking the next step…
Слайд 3Analytics: A business reality now
Focus is on fact-based rather than gut
based decision making.
Analytics is a strategic weapon for businesses.
Customer analytics are driving big data initiatives.
53% of big data efforts underway by retail
companies are focused on achieving customer-centric outcomes
Organizations are being practical about adopting Analytics
74% of retailer say that leadership is totally or highly committed to analytics.
Analytics is a strategic weapon for businesses.
Customer analytics are driving big data initiatives.
53% of big data efforts underway by retail
companies are focused on achieving customer-centric outcomes
Organizations are being practical about adopting Analytics
74% of retailer say that leadership is totally or highly committed to analytics.
Слайд 4Analytics in Retail
Opportunity to achieve competitive advantage from ‘Analytical Retail ‘
is enormous.
Few examples:
Kroger gets a 40% redemption rate from its analytically target coupons compared to industry average of 2%
Tesco uses supply chain analytics to save $100m
German retail giant Otto Group used predictive analytics to save $20m
Few examples:
Kroger gets a 40% redemption rate from its analytically target coupons compared to industry average of 2%
Tesco uses supply chain analytics to save $100m
German retail giant Otto Group used predictive analytics to save $20m
Слайд 5
Analytics: A business reality now
Why do we need Analytics?
Implementation Plan
Expected benefits
Taking the next step…
Implementation Plan
Expected benefits
Taking the next step…
Слайд 6Why do we need Analytics?
Pain Points of the Company
The companies YOY
revenue growth is not meeting our expectations
Retail shrinkage of the company is 2% of our annual retail sales
The attrition level is 5% above the industry average
Retail shrinkage of the company is 2% of our annual retail sales
The attrition level is 5% above the industry average
Слайд 7Why do we need Analytics?
Opportunities to explore
Develop
close relationships with customers based on a deep understanding of their behaviors and needs.
Determine the best use of marketing investments.
Balance inventory with demand so that we are never out of stock or carrying excess inventory.
Locate stores, distribution centers, and other facilities in optimal locations.
Determine the best use of marketing investments.
Balance inventory with demand so that we are never out of stock or carrying excess inventory.
Locate stores, distribution centers, and other facilities in optimal locations.
Слайд 8
Analytics: A business reality now
Why do we need Analytics?
Implementation Plan
Expected benefits
Taking the next step…
Implementation Plan
Expected benefits
Taking the next step…
Слайд 10HR Analytics
HR Analytics
Creating value in human capital
Raise Visibility
Align HR data with
business data
Predict the future
Слайд 11
Fraud
Analytics
Cultural Assessment
Understanding activity Patterns
Continuous monitoring & innovation
Слайд 13
Marketing Analytics
Evaluate consumer purchasing behavior, identification of the combination of the
products buying together
Predictive modeling to evaluate price elasticity, margin target, profit and revenue maximization
CRM analytics(demographic, psychographic & purchase behavior), cross-selling and up-selling strategies.
Better store layout planning and assortment optimization
Predictive modeling to evaluate price elasticity, margin target, profit and revenue maximization
CRM analytics(demographic, psychographic & purchase behavior), cross-selling and up-selling strategies.
Better store layout planning and assortment optimization
Слайд 14Infrastructure Requirements
Developing a CoE
Dedicated captive center for analytics
Building expertise in analytics
Creating
awareness
IT requirements
Analytical tools and software
EDW
IT requirements
Analytical tools and software
EDW
Слайд 15
Analytics: A business reality now
Why do we need Analytics?
Implementation and Execution plan
Expected benefits
Taking the next step…
Implementation and Execution plan
Expected benefits
Taking the next step…
Слайд 16Expected Benefits
Our YOY revenue growth will be 15%
Projected increase in the
operational efficiency is 26%
Footfalls and average bill value will increase by 2% each
Gross Margin to increase by 1% by promoting more private labels
We would be able to reduce our retail shrinkage to 1%
We would be able to reduce our attrition level by 10%
All the above factors will lead to overall profit increase by 10%
Footfalls and average bill value will increase by 2% each
Gross Margin to increase by 1% by promoting more private labels
We would be able to reduce our retail shrinkage to 1%
We would be able to reduce our attrition level by 10%
All the above factors will lead to overall profit increase by 10%
Слайд 17Taking the next step…
Need your support, commitment and desire to implement
Need
to appoint a Analytics head
Spread the awareness among the employees
Spread the awareness among the employees
