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Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
Creating $100 million from Big Data Analytics in Banking
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Creating $100 million from Big Data Analytics in Banking

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A sanitized version of our presentation to the Teradata Marketing Summit in Los Angeles in March 2014, on how we created $94.95 million in incremental value for a bank by means of a …

A sanitized version of our presentation to the Teradata Marketing Summit in Los Angeles in March 2014, on how we created $94.95 million in incremental value for a bank by means of a customer-centricity strategy enabled by Big Data and Analytics

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  • 1. @Teradata_Apps |#TeradataSummit How to make $100 million with Big Data How we achieved a remarkable return for our investment in total enterprise engagement in the Big Data paradigm. A case study in true end-to-end Big Data and customer-centricity. <Sanitized version for Slideshare> Guy Pearce Managing Partner REData Performance Consulting Toronto, Canada info@redata.ca @pearcegf @data_roi
  • 2. @Teradata_Apps |#TeradataSummit AGENDA
  • 3. 3 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit 0 10 20 30 40 50 60 70 80 90 100 May Jun Jul Aug Sep Oct Nov $million Utilization Payments Xactions Credit A remarkable outcome, but probably not nearly as remarkable as the journey! The results above are but the last chapter in a rich people story, a story about the Magic of Engagement! So, let me begin…
  • 4. @Teradata_Apps |#TeradataSummit AGENDA
  • 5. 5 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Margins under pressure  Increasing Competition Market share under pressure MARKET RESEARCH FINDINGS* • 3rd for “have competent and knowledgeable staff” • 3rd for “understand me” > The findings included that not understanding the customer was a primary reason for customer attrition • 3rd for “make an effort to understand me” These findings were unacceptable. Something needed to be done! The best solutions solve a problem. Burning platforms make compelling cases for change! *Ranking out of the major banks STRATEGIC CHALLENGES Ext
  • 6. 6 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit The problem statement concerned the customer. The right “solution” would therefore have to solve these Customer Centricity Channel Innovation Pricing InnovationProduct Innovation The problem statement showed failing customer engagement. A data-driven customer-centricity initiative was born STRATEGIC ALTERNATIVES
  • 7. 7 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Analytics were customer-centric. Quality and risk were managed implicitly, the latter not ideal Longitudinal Behavioural Analytics, by customer Risk-Return Portfolio Modelling, by customer Contribution Profiling, by customer “Next Best” Predictive Analytics, by customer We integrated diverse analytics to best understand the customer, and then focused everyone’s efforts on how best to serve them The latter helped optimize the sales force geographically, by sales potential * Geospatial rendition of “next best”, aggregated by municipality
  • 8. 8 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Tying it together, we proposed an integrated strategy for data-driven customer-centricity as a solution Nearly half of big companies’ data initiatives fail because of poor integration between operating model and business model KPMG 2014 Strategy, Governance and Stakeholders Marketing Finance Group IT Measurement Business Model Product Management Channel Management Segment Management Operating Model HR Operations Big Data analytics and insights Objectives
  • 9. @Teradata_Apps |#TeradataSummit AGENDA
  • 10. 10 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit • MIS • CRM • Strategy • Technology • Environment • Data Operations • Data Integration • Predictive Analytics • Descriptive Analytics • Data Sourcing (int/ext) There were big lessons in building an action-oriented big data core team The degree of strategically accurate innovation and initiative that drove the team to peak performance is a case study on its own
  • 11. 11 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit • Steering Committee > Channel Operations (action) – Provincial and > 1000 branches across the country > Credit > Product > Strategy > Marketing > Segments > Finance (recording) > Change Management > Human resources (training) > Group IT (group CRM rollout) Lessons learned were used to engage the enterprise, an imperative for any enterprise-scale initiative Change Management 101: What’s the burning platform? Does it impact me? What’s in it for me? How do I look good in this?
  • 12. 12 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Ma‟am, may I suggest… (Aside > W = what products you‟ve got > X = what products a cohort of customers of a similar profile to you have > Y = an estimate of what products you‟ve got at our competitors > Z = an estimate of what products you may need to fulfil your aspirations) (Structured conversation about unique (diff(X-W) union Y union Z)) Resulted in a 1:2 strike rate Renewed, relevant, insightful one-to-one customer engagement
  • 13. 13 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Insightful branch and suite staffing strategy, based on potential, aggregated per customer per centre Aggregated customer insights were used as a guide to set individual sales targets, to assist with determining staffing levels, which in turn had implications for training and branch budgets A case study in holistic strategy
  • 14. 14 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit On adoption: Original slide to the board. Poor choice of words, and over-simplified, but it worked  The best adoption strategy is for people to want what you’ve got!
  • 15. @Teradata_Apps |#TeradataSummit AGENDA
  • 16. 16 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Value Customers Front Line Staff CRM Big Data Analytics B A To create value, Big Data „reached‟ the customer by means of CRM and the front line staff B = Stakeholders and Team A = Strategy Alignment. Purpose For simplicity, the diagram does not show the feedback loops between the different elements
  • 17. 17 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit • Adjust the annual market research survey to facilitate measuring how the engagement was impacting market share • Make governance and risk an explicit track Two things we should have done, but didn‟t think to do in the heat of the moment
  • 18. 18 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Volume Terabyte Scale Variety One internal data source Eight external data sources Velocity Growing at up to 1000 rows per second Processing A Teradata appliance dramatically improved performance and reliability But was it really Big Data? Yes, by Gartner’s definition. We were unable to achieve real time and mobile deployment … maybe in our next engagement!
  • 19. @Teradata_Apps |#TeradataSummit AGENDA
  • 20. 20 3/23/2014 Teradata Confidential @Teradata_Apps |#TeradataSummit Big Data is BIG. Complications aside, Big Data is less effective if it is not positioned at the enterprise level: • The board approves corporate strategy • The CEO sponsors Big Data as a key component of strategy enablement • The CIO‟s team builds it • The CMO‟s team creates excitement • The CHRO‟s team upskills staff • The COO‟s team makes it happen • The CFO‟s team audits and measures Sharing some lessons If the objective of your Big Data project is to create value, then people engagement is a critical success factor
  • 21. 21 3/23/2014 Teradata Confidential The $100 million question: Is Big Data something you should be doing? Guy Pearce Managing Partner REData Performance Consulting Toronto, Canada www.redata.ca info@redata.ca @pearcegf @data_roi

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