B26fbmodule iii (crm)
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ICICI Bank implemented a CRM solution in phases to create a single customer view and better understand customers. The first phase created a data warehouse integrating 6 systems. The second phase expanded data and added segmentation tools. Future phases aim to automate campaigns and integrate additional systems. Key challenges included lack of models, disparate systems, and building a data-driven culture. Critical success factors were a technology focus, independent CRM team, and phased approach. Benefits included increased revenues, cost savings, and improved decisions. The roadmap includes advanced analytics, automated campaigns, and customer profitability models.
B26fbmodule iii (crm)
- 1. Assessing e-CRM through KM in ICICI BANK
- 2. The Purpose for CRM Measurement Three main uses for CRM measurement systems are: • To influence or validate decision making • To guide ongoing activities or tactics • To predict future states
- 3. Companies implement e-CRM measurement very differently based on their internal decision making styles. As companies make decisions about customer strategies, they look to customer measurement to help influence specific decision makers or the decision making process or validate initial ideas about how to manage online customer relationships. Influencing or validating decision making
- 4. Readiness Factors organized by Categories within Dimensions Intellectual Dimension • Strategy • • Orientation • • Leadership • • Mgmt. support • • Champion • Structure • • Organizational Structure • • Business Processes • • Incentives and Rewards • Planning • • Corporate • • Business Units • • Information Technology
- 5. Social Dimension • Culture • • Cultural Perspective • • Attitudes toward change, technology, Sharing • Stakeholder Interactions • • Dynamics • • Involvement • • Technological Savvy • Domain Knowledge • • Within Business Unit • • Across Business Units • • Sharing
- 6. Technology Dimension • CRM Application • • Scope • • Complexity • • Customization • IT Capability • • Project Management • • Skilled Team • • Similar Implementations • Knowledge Management • • Integration • • Data Warehouse • • Infrastructure
- 7. Properties of Complementary Factors expected to enhance Readiness INTELLECTUAL DIMENSION Strategy Orientation Customer-centric; market oriented Leadership Visible commitment of top echelon Mgmt Support Commitment of resources for employee educatoin and training; assignment of key employees throughout CRM process; money for technology and multi- year implementation effort Champion Use the same high-level person throughout the project and dedicated him/her full-time Structure Organizational Structure Centralized structure to implement; CRM compatability with org'l design, authority hierarchy & reporting relationships Business Processes Logical integration of customer-related knowledge; processes re- engineered to mirror CRM application 'best practices' Incentives & Rewards Reward employees that bear the cost of CRM (i.e. Updating knowledge
- 8. Planning Corporate, Business Units, and IT Integrated, connected and established planning process SOCIAL DIMENSION Culture Perspective Integrated (shared values and behaviors), cooperative, and trust-based Attitudes Open to change, positive attitude towards technology Empowerment Employee empowerment is the norm Stakeholder Interactions Dynamics Identification and awareness of CRM stakeholder dynamics Involvement Inclusion of stakeholders in CRM planning efforts Technology experience Technologically savvy stakeholders Domain Knowledge Within business units Enhanced depth of knowledge Across business units Enhanced breadth of knowledge Sharing Willingness to share knowledge
- 9. TECHNOLOGY DIMENSION CRM Application Scope and complexity Reduced functionality; phased implementation Customization Reduced or eliminated IT Capability Expertise Project management experience; balanced team of experts; experience with similar installations (e.g. ERP, SFA) Knowledge Management Integration Global view of customer Data Warehouse Pre-existing data structures, standards, and models built into corporate Knowledgebase Infrastructure Communication networks, data warehouses, computing platforms, web servers
- 10. Banking Industry addresses the key CRM challenges that is faced by them today, including how to: • Identify customers that have the most assets and would be the most profitable • Identify the most profitable products • Cross-sell and up-sell products that are most relevant to a customer’s life stage and financial needs • Improve customer service while reducing service costs in basic areas, such as account inquiry, transfers, the trading of financial instruments, and cash management • Find strategies to eliminate current operational inefficiencies • Implement technology that leads to enhanced productivity of customers, partners, and employees Assessing CRM Readiness in Banks
- 11. Facilities offered at Banks • Internet Banking’ • Tele Banking • Remote login for corporate customers • Electronic reconciliation • SWIFT – Society for World wide International Financial Transaction • Structured financial marketing structure • Video conferencing • Single window service • WAN • Core banking solution • ePay
- 12. • ECS – Electronic clearing services • Digital Signature • e Cheque • Truncated Cheque • Online Banking • Electronic Channels • Paper money replaced by plastic money
- 13. Assessing readiness at ICICI Bank – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 14. ICICI Bank - The journey so far • Established as a Financial Institution in 1955 specialising in Project & Development Finance. • Retail foray in 1995 – Largest private sector bank in India, – Catering to over 11 million customers. – Total assets over INR 1 trillion – Retail deposits grew last year by 50% compared to an industry growth rate of 17% – Leadership in retail credit • Twice as large as nearest competitor in the vehicle loans market • Fastest growing credit card base in the country.
- 15. ICICI Bank - The journey so far • Wide Range of Products – Bank accounts, credit cards, loans, bonds, insurance etc. – Products across income and age groups • Distribution Network & Reach – Branches: Largest private network in India – ATMs: Largest network in India – Phone: Largest call centre in India* – Internet: Maximum functionality in India * Compared to any other Bank
- 16. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 17. Key Drivers • Transition to Universal Banking – Necessity to have a single view of the customer. – Integration of customer knowledge across businesses. • Liberalisation of the Financial sector – Growing commoditisation – End of the ‘passive’ customer – Customer knowledge and increased focus would be the key • Organisation specific issues – Information Silos – Use of OLTP systems for reporting – No single version of the truth
- 18. Objectives • To resolve disparate relationships across multiple products • To understand the behavioral and financial profile of customers • To leverage this understanding to effectively target specific customer segments with relevant offers and communications; and • To frame strategies from a customer perspective rather than the predominant account-centered perspective • To create an analytic infrastructure which would be the single source of the ‘truth’
- 19. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 20. Building Blocks Single View of the Customer Knowing & Understanding the Customer Transforming Knowledge into Action Phase 1.0 Phase 2.0 Phase 3.0
- 21. Building Blocks Single View of the CustomerPhase 1.0
- 22. Solution Overview • Phase 1.0: Jan 2000- July 2000 – Base infrastructure set – Integrated a Customer matching tool with the warehouse The result was a single view of the customer and their banking habits. – Data extraction from 6 source systems. The warehouse consolidated information about customer • Demographics • Product holdings and balances • Transactions and channel usage
- 23. Building Blocks Single View of the Customer Knowing & Understanding the Customer Phase 1.0 Phase 2.0
- 24. Solution Overview • Phase 2.0: October 2000- July 2001 – Expansion of primary data warehouse to include 2 new source systems – Implementation of Behavior Explorer - a front end for OLAP analysis - Segmentation,profiling etc. • PowerPlay: Easy to use, multi-dimensional data views for the end user • Impromptu: Drag-and-drop queries for ad- hoc reporting – Resulted in reduced dependence on IT and OLTP systems for regular reporting
- 25. Building Blocks Single View of the Customer Knowing & Understanding the Customer Transforming Knowledge into Action Phase 1.0 Phase 2.0 Phase 3.0
- 26. Solution Overview • Phase 3.0: Under Implementation – Redesign of the logical data model to suit changing business requirements, and incorporate new businesses with a focus on channel integration. – Implementation of ETL tool to ensure more efficient extraction of data from the source system – Improvement in the customer matching logic – Implementation of campaign automation tool
- 27. What we intend to achieve Till 2012 • Bring in better quality, profitable customers through targeted campaigns. • Execute a rule-based customer contact strategy • Improve campaign efficiencies in terms of cost, planning and roll out time and response rates . • Expand capacity and improve performance of existing infrastructure. • Analytical framework based on current and projected information requirements. • Reduce load on production systems by moving time and resource intensive processing to the Warehouse.
- 28. Teradata Warehouse Credit Cards Asset Products Bonds & FDs Demat Retail Banking ICICI Direct Customer Matching ATM Web Financial transaction data from channels Consolidated customer and product information from the various source systemsStand alone systems for each business E n d U s e r s Cognos Current Architecture
- 29. Teradata Warehouse Credit Cards Asset Products Bonds & FDs Demat Retail Banking ICICI Direct Customer Matching ATM Web Financial transaction data from channels Consolidated customer information from the various source systems Third Party Products Stand alone systems for each business E n d U s e r s Cognos Call-Center E T L Future Architecture RO Leads sent to channels Campaign Calculator Branch SIEBEL
- 30. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 31. Key Challenges • Lack of role models – ICICI Bank was the first in India to attempt a comprehensive EDW and CRM platform implementation. • Disparate platforms – Each company in the group had built its own customer databases and operating platforms. A complex integration task was necessary. • Data integrity – Issues of accuracy and completeness of data, particularly in a developing economy like India where there is no universal customer identifier such as a Social Security Number. – A customised data matching algorithm was developed taking into account the specific characteristics of data available
- 32. Key Challenges • Lack of a data driven culture – Historical issues in getting getting reliable data. – Only data that was necessary to ease operational processes was captured. – Structured, data-driven decision-making has not been very prevalent. – The CRM team has had to demonstrate the value of collecting additional information. • Market conditions – The Indian market moves very rapidly and often unpredictably, so the bank needed to retain flexibility while developing better predictive powers
- 33. Key Challenges • Managing Vendors – Co-ordinating with multiple vendors who each handle different parts of the overall solution – Expectation management by vendors – Global best practices are available but implementation in the local context requires the agility to adapt.
- 34. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 35. Critical Success Factors • Technology Orientation – As an organisation, ICICI Bank has always been an early adopter of technology solutions and therefore employees are open to new ideas and technology driven solutions – Senior management has played a key role in driving use of the datawarehouse • Organisation structure – The datawarehouse team is managed by a business team and is not driven by IT – The team is not housed with any particular channel or product group so it can assume a truly enterprise- wide perspective • Phased approach – The EDW solution was implemented in phases to ensure rapid ROI and immediate value delivery
- 36. Critical Success Factors • Designed for change – The LDM is in the third normal form to increase flexibility for adding to or modifying the structure to accommodate new businesses, products and channels – The ETL solution being implemented will ensure flexibility and reduce the time taken to add new data sources. With this touch-and- take approach, increased data volumes should be easily handled • Scalability – The Hardware platform of choice is designed for augmentation and planned scalability
- 37. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 38. Business Benefits • Revenue enhancement – Over 150 large tailored marketing campaigns have been run, generating 2.6 million leads, with response rates ranging from 8-36%. • Significant savings in customer acquisition costs • Reduced time-to-market for campaign execution from an average of 10 days to 3 days. • Strategic decisions across the business groups are being aided through analysis like channel usage patterns, value migration, product basket analysis etc.
- 39. Outline – ICICI Bank - The journey so far – Key Drivers – Solution Overview – Challenges – Critical Success Factors – Business Benefits – The Road Ahead
- 40. Roadmap • Analytical applications – Implementation of applications, which would allow business users to have almost real-time information on key performance indicators, balance scorecards etc. – Delivery of this information through multiple channels such as • Internet • Mobile • Wireless
- 41. Roadmap • Campaign automation and shift towards a technology-enabled, rule-driven marketing environment. This would include: – Integration of the data warehouse solution with the front-office solution – Customer-level profitability models enabling service differentiation – Predictive models that will enable the bank to touch customers at the right time with the right offer – Integration with a marketing ROI and scenario planning solution, which will aid key decision makers to have a one view of their marketing investment.
- 42. Roadmap • Campaign automation and shift towards a technology-enabled, rule-driven marketing environment. This would include: – Integration of the data warehouse solution with the front-office solution – Customer-level profitability models enabling service differentiation – Predictive models that will enable the bank to touch customers at the right time with the right offer – Integration with a marketing ROI and scenario planning solution, which will aid key decision makers to have a one view of their marketing investment.
- 43. 4. ) Balanced scorecards - Introduced by Robert S. Kaplan and David P. Norton in 1992, The balanced scorecard is broken down into four sections, called perspectives: The financial perspective The strategy for growth, profitability and risk from the shareholder’s perspective. The customer perspective The strategy for creating value and differentiation from the perspective of the customer. The internal business perspective The strategic priorities for various business processes that create customer and shareholder satisfaction. The learning and growth perspective The priorities to create a climate that supports organizational change, innovation and growth.
- 45. CRM Balanced Scorecard metrics • Developing successful business build good relationship with customers. But not all clients are equally desirable for the business. You really need only those customers that will help the company become strong, flourishing and prosperous. Customer Relationship Balanced Scorecard Metrics is created to estimate customers. • But, even having got right clients you can not be sure that success will constantly follow the steps of your business. If something goes wrong, customers can change their attitude toward the company, demonstrate dissatisfaction and indifference. To prove efficiency and turn clients back recovery tools are to be used. And the global task of the policy is to find the reason for displeasure, extirpate it and build favorable relationship with the customers again.
- 46. Customer Relationship Evaluation Balanced Scorecard Metrics details • . This is the actual scorecard with Customer Relationship Performance Indicators and performance indicators. The performance indicators include: customer relationship scorecard, customer quality, customer long-term value, customer life span, customer segmentation, satisfied customers, dissatisfied customers, customer potential, damage and recovery manager ,dissatisfaction management.
- 47. Measure performance and benchmark with Balanced Scorecard How to use Balanced Scorecard concept to measure a business performance? It's actually easy. You will need to pass tree simple steps. • First, you will need to design a set of proper metrics, which will describe your business well. It is very important step, as it will affect all your future estimations, • Second, the metrics should be grouped. There should not be too many metrics and groups of metrics. It would be great if you will have four or five metric groups and about 3-5 metrics in each group. You will need to set the importance values for every metrics, you will need to describe the way, how do you measure the metric value, you will need to set a target values for metrics. • The final step is calculating the performance, using your estimation of metric values, their weights and weights of their groups. The total values will tell you how the business is performing within the certain viewpoint.
Editor's Notes
- #32: Lack of role models: ICICI Bank was the first in India to attempt a comprehensive EDW and CRM platform implementation. Disparate platforms: As the bank had entered different retail businesses at different times, each company in the group built its own customer databases and operating platforms. A complex integration task was necessary. Data integrity: Coupled with the platform issues there was widespread concern about the accuracy and completeness of data, particularly in a developing economy like India where there is no universal customer identifier such as a Social Security Number. Lack of a data driven culture: Because it has historically been difficult to get reliable data, structured, data-driven decision-making has not been very prevalent. Given this culture, only data that was necessary to ease operational processes was captured. The datawarehouse team has had to demonstrate the value of collecting additional information. Competing products: Rapid growth meant ICICI often had overlapping products or conflicting messages, a problem compounded by product-driven marketing. To compete effectively, the challenge was to develop a capability for customer focus with an EDW and CRM platform that reflected customer behavior and to leverage this understanding through customer-focused product development and customer-centered marketing. Market conditions: The Indian market moves very rapidly and often unpredictably, so the bank needed to retain flexibility while developing better predictive powers Managing Large scale,unfamiliar tech projects - vendors promise the moon; global best practices are not implemented by local team;difference in quality of loacl v/s expat tech teams,little experience in managing projects of this size,scope & complexity
- #33: Lack of role models: ICICI Bank was the first in India to attempt a comprehensive EDW and CRM platform implementation. Disparate platforms: As the bank had entered different retail businesses at different times, each company in the group built its own customer databases and operating platforms. A complex integration task was necessary. Data integrity: Coupled with the platform issues there was widespread concern about the accuracy and completeness of data, particularly in a developing economy like India where there is no universal customer identifier such as a Social Security Number. Lack of a data driven culture: Because it has historically been difficult to get reliable data, structured, data-driven decision-making has not been very prevalent. Given this culture, only data that was necessary to ease operational processes was captured. The datawarehouse team has had to demonstrate the value of collecting additional information. Competing products: Rapid growth meant ICICI often had overlapping products or conflicting messages, a problem compounded by product-driven marketing. To compete effectively, the challenge was to develop a capability for customer focus with an EDW and CRM platform that reflected customer behavior and to leverage this understanding through customer-focused product development and customer-centered marketing. Market conditions: The Indian market moves very rapidly and often unpredictably, so the bank needed to retain flexibility while developing better predictive powers Managing Large scale,unfamiliar tech projects - vendors promise the moon; global best practices are not implemented by local team;difference in quality of loacl v/s expat tech teams,little experience in managing projects of this size,scope & complexity