Downloaded 13 times
Uploaded byNaveen Jain
CUAS Data Journey V3
Naveen Jain discusses building an analytics culture at First Tech Federal Credit Union. Key aspects included establishing executive commitment, focusing on fact-based decision making, developing an information infrastructure, and engaging business units. Early wins included improving onboarding to drive product penetration and reducing mortgage loan cycle times by integrating data and visualizing workflows. Lessons learned centered around maintaining executive alignment, engaging business stakeholders, prioritizing quick wins through an agile development approach.
CUAS Data Journey V3
- 1. Building a Cultureof Analytics at First Tech Federal Credit Union Naveen Jain Director, Digital Analytics
- 2. Focused on Deliveringa Different Banking Experience • We proudly offer a complete suite of financial services including Insurance and Investment Services1 • The NCUA rates us among the safest credit unions in the country2 60 years of service. Established by Tektronix and HP employees. 400Kmembers nationwide 40branches $8 billion in assets 1Securities offered through Raymond James Financial Services, Inc., member FINRA/SIPC, which is not affiliated with Addison Avenue Investment Services or First Tech Federal Credit Union. Investment advisory services offered through Raymond James Financial Services Advisors, Inc. Securities are not guaranteed by the Credit Union, not NCUA/NCUSIF insured, not a deposit, not insured by any government agency, are subject to risk and may lose value. First Tech Insurance Services is a wholly owned subsidiary of First Tech Federal Credit Union. 2Source: www.ncua.gov. 8th largest credit union in the nation
- 3. Adobe Hewlett Packard Enterprise HP, Inc.Yahoo Nike CH2M Intuit Intel Cisco Amazon Philips We Serve Innovators Microsoft Hewlett Packard Intel Microsoft Keysight Technologies Twitter Tektronix GoogleAgilent Technologies
- 4. + 6,500 SharedBranch locations nationwide + 30,000 surcharge-free CO-OP ATMs nationwide Banking Options Nationwide
- 5. What we willbe discussing today 1. What does analytics culture mean 2. Business challenge 3. Key requirements of analytics culture 4. How did we do it 5. Early wins 6. Learnings recap
- 6. Mindful Decision Making •Respond and not react • Fact based decisions across all levels • Trusted information to the right people at the right time
- 7.
- 8. When our membersare high tech Bank Anywhere Millennials Double Digit Growth Analytics
- 9. Key Requirements forAnalytics Culture • Executive Commitment • Fact based decision making and defining strategies • Information Infrastructure
- 10. How We DidIt Vision Technology PeopleProcess
- 11. Vision • Executive Alignment •Organizational Alignment • Strategy and Roadmap • Quick wins Vision
- 12.
- 13. Digital Analytics Platform Employees Membersand Prospects Marketing BranchCall Center Digital Investments & Insurance Web Behavior Core Banking CRM Call Center Shared Branches Maxarr PSCU Loan Origination System Online Banking NPS Marketing Automation eFlow Third Party ETC Data Management Platform (Centralized database, normalized audience view, audience segmentation, scoring, profiling, modeling, etc) Core Banking Visualization & Analytics Technology Support and Service Insights Action 1 2 3
- 14. Data Management PlatformTechnology
- 15. People • Organization • Enable •Empower • Community • Collaboration • Communication
- 16. Key Process AreasProcess Business Engagement Data Governance Infrastructure o Business Engagement Model o Roadmap o COE Model o Executive Alignment o Ongoing Data Owners/ Steering Committee o Scope of Data Gov. o Agile Development o Support o Data Marts
- 17. Business Engagement Retention Services toensure member growth and retention. Continuous Engagement Bi-weekly/monthly meetings. Engage the steering committee. Update wiki with changes in business rules and policies. Support with insights and enabling analyst with tools and technologies. Exposure Partnership brings insights by blending of Analytics team with the LOB. Exposure to analytical tools, technologies, wiki, trainings, data governance and forums. Discovery Discover and document areas that can be streamlined and improved. Gap Analysis. Recommend processes with definite wins on time and resources . Roadmap Roadmap of monthly/quarterly deliverables & business expectations. Quick Wins Set up measurable objectives, KPIs, suggest actions based on lessons learned. Win on short term goals. Expand with continuous engagement Focus on roadmap and specific deliverables Process
- 18. Business Engagement Awareness Evaluation /Product Purchase DeliveryUsage Support Repurchas e Advocacy Customer Interests Objectives Data Sources Opportunit ies KPIs
- 19. Roadmaps Phase 1 (Q42015) • Setup data-marts/ buckets around account, member, product and other objects • Data Governance framework – Data definitions • Eloqua Onboarding dashboard/ reports setup • Enabling LOBs with Tableau Phase 2 (Q1 2016) •Member 360 Profile •Data Integration & Reporting framework for Web/ Marketing •Account Life Time Value •Data Governance – Data Challenges/ Standardization Phase 3 (Q2 2016) •Executive Dashboard for all P&L LOBs •Key business Insights •Call center Performance DB • Data Governance - control procedures Phase 4 (Q3 2016) •Predictive Modeling based on member info •Data Governance – data management projects Data Governance Ongoing Implementation Enabling Tableau - Power Users Support Process
- 20. Data Governance ProgramScope Process • Data Owners, Data Stewards and/ or Data Consumer • Enterprise teams accountable and managedRoles & Responsibilities • Data Owners assign one of the data classification (Public, Internal Use, Confidential or Secret) • Classify security impact (low, moderate or high) and reclassify Data Classification • Ensure Confidentiality, Integrity and Availability security policies are met towards Enterprise data • Classify into impact potential as: Low, Moderate or High Security Policy • Use Data Risk Matrix to classify appropriate risk category Risk & Compliance Rules • Bring data from various sources and then validating/transforming them to ensure trust.Data Warehouse • Ensure business rules on the Wiki page are current • Ensure adequate documentation is posted on Wiki page for quick reference Business Rules & Documentation • Identify, document, investigate and recommend solutions for data quality issuesData Quality • Managing customer/product master data Master Data Management DataGovernance
- 21. Agile Development ProcessProcess
- 22. Success Stories 67% andgrowing
- 23. Onboarding Drives ProductPenetration
- 24. Improved Mortgage LoanCycle Times • Problem: Working with disparate data sources and a complex process, the Mortgage Loan processing & funding team needed a tool to help monitor, track and measure loan cycle times across different loan stages and cross functional teams. • Solution: Designed an integrated solution. Using Alteryx for data blending, logical flow and data formatting into creating a Tableau extract for visualization.
- 25. Solution – LQBDashboard Mortgage Sales Ops team managing loan processing and funding cycle times
- 26. Sales Funnel • Problem:Various leads originating from different marketing channels. Need to analyze and help Marketing team to focus on right channel to help member growth. • Solution: Designed a solution using Tableau and Sales Force that allowed complete view of end-to-end Sales funnel in tracking and following up lead generations.
- 27.
- 28. Learnings From OurJourney So Far… Learnings • Executive Alignment • Business engagement and alignment • Fail fast and quick wins (Agile Development)
- 29. Contact Info • Email– naveen.jain@firsttechfed.com • LinkedIn - https://www.linkedin.com/in/naveenjain • Twitter - @naveenjain
Editor's Notes
- #4Â Our strategic partners include HP, Microsoft, Amazon, Cisco, and Genentech.
- #5Â With 40 branches in 8 states and another 6,500 branches & 30,000 ATMs through our CU Services Network, we provide a convenient, nation-wide solution. In fact, members who relocate internationally still maintain their relationship with First Tech (members in 21 countries).
- #7 The banking marketplace is tough. It’s fiercely competitive with consumers shopping around for the best rates possible and little differentiation among products. Financial institutions struggle to find the right balance between improving profitability and providing competitive pricing and an unmatched customer experience. Activities that focus on the customer experience – like lower fees, concierge services and enhanced agent support – can run counter to goals like lowering operational expenses and reducing labor costs. The key to achieving this balance is an enterprise wide commitment to data and analytics. Such a commitment will enable you to: See problems coming and take steps to prevent them instead of being reactive and constantly fighting fires. Foster a culture of fact-based decision making through all levels of the organization. Build a strategic analytic culture where analysis is part of your corporate DNA. Deliver trusted information into the hands of decision makers in time for them to take action. These goals, though lofty, are achievable – and necessary for organizations seeking to survive and thrive in today’s economy.
- #9 Wide spectrum of Member demographics – primarily tech savvy millenials External & Internal members Rapid growth rate in range of two digits, fastest in CU industry Need to provide products and services that meets the needs of our members at right time of member life phases Need to provide quick analytics to continue to grow, manage and sustain member
- #10 What are the Key ingredients of Analytics Culture A strategic analytic culture starts and ends with executive management commitment. When executives are fully bought in to the concept of an analytic culture, they set goals, priorities and expectations based on the use of analytics. They invest in technology, people and processes that will continue to foster this culture. Analytics Commitment - Companies with a strategic analytic culture set their business strategies based on what the analytics tell them. Every department needs to actively use analytics as appropriate for the responsibility and maturity of its function. Organizations with a strategic analytic culture are motivated to back up conclusions with data. It isn’t about instinct, but solid proof. Colleagues across the organization ask “why,” and demand data in response. Commitment to Data management - Good analytics are pointless without good data. The foundation of a strategic analytic culture requires an organizational commitment to creating, cleansing, storing and accessing information from across the enterprise. And that means more than just being able to get to the data. It also means building common, agreed-upon definitions of key metrics, so that when executives review information they can spend their time making decisions rather than arguing about definitions.
- #11 Vision – People/ Process/ Technology === Combination of these three along with executive alignment all within a Data Governance framework from process standpoint.
- #12 Analytics Culture starts with creating a vision. This should include very clear benefits to the business and includes specific ROI. Just doing analytics for the sake of doing is not enough. It should be actionable and tied to the business value. In our case when we created the ROI, we lead with the marketing impact and how the investment will lead to increase in new membership as well as cross-sell and up-sell opportunities. Roadmap – There should be a SMART roadmap associated with the vision. Specific, measureable, achievable, results-focused and time bound. Sharing with the executive team to obtain their commitment. Nothing can succeed without strong executive commitment. Also, sharing and socializing the vision within the organization to obtain alignment and finding some quick wins that can help create the momentum. E.g. in our case, we created a sales funnel dashboard that provided a visual view of leads, opportunities, funded accounts by channel, region, etc.
- #13Â Technology is complex but still the easiest of the whole initiative. People and process part are more complex, where a whole of creative goes in. Identified data sources to pull the data from. Having tools to analyze the data and obtain insights Most important is the take action on the insights. E.g. if you have figured out that a certain member has higher propensity to get an auto loan, that is not enough and you need to ensure that appropriate action is taken on that insight to put the right offer in front of the member using right channel and at the right time
- #14Â We started first with set of technologies that will allow us to get to the insights based on the data that we already have. Quite often, I hear from business users that we want this data and that data before we can do anything. This did two things. We were able to engage with the business in agile manner. Today we see quite some penetration in our business users of Tableau. Before most of the analysis was done using Excel and Access. It allowed us to take start getting insights from the data that we already have in more or less pure form. Then we started with the technologies that will allow us to take action based on the insights. This is where we invested in Marketing Automation and Website Personalization tools. Using Marketing Automation, we started automated onboarding program that sends out educational emails to our members educating them about our products and services. We are already starting to see the higher engagement with these members.
- #15Â Architecture diagram
- #16 Organization COE (Center of Excellence Model) Enablement Individual LOB scheduled / adhoc engagements Initial Workflow Design & Scheduling Adoption Active Tableau Power User Community Collaboration tool – Wiki Confluence Evangelized Analytical Tools Monthly Events/ Weekly Tableau User Group Evangelized at Executive Level Empowerment Showcase advanced users workbook Publish to Production
- #17Â Organization Assembling the passionate people COE Model
- #18Â Business Engagement COE model Dashboard Process Workflow Engagement Model Roadmap Data Governance Alignment at the highest level Monthly Data Owners/Steering committee Scope of Data Governance Infrastructure Agile Development Support Data Marts Having a very pretty quick win dashboard that people can take as template
- #19Â COE picture
- #22Â Business Roadmap
- #25Â Multiple business definitions for a member triggered need to establish Data Governance for standardizing definitions, business terminology and processes. In early stages, DG team has; Established Data Governance Steering Council identifying CFO and CIO (Chief Investment Officer) as key stakeholders Identified 35+ different data sources and assigned data owners, data stewards and data specialists Formation of Data Stewards Council & engaging periodically to educate, train and prioritize with engaging key business units Defined a practical Data Governance Road Map to ensure program sustainability and participation from key data stewards.
- #26Â Daily 20 min stand up meeting to track daily progress, impediments and information associated to planned sprint stories. Colored sticky notes help identify the owner of the story and product. Defined process for flow of data processing and managing project tasks
- #32 Designed Enterprise level dashboard that all BU’s could relate and consume. Weekly Tableau Power Users group meetup internally Tableau training day at multiple user locations for onboarding Support engaged advanced users. Tableau adoption trend since beginning of year 2015 has phenomenally increased from initial 10% in Feb to over 46% of total employees ending September.
- #33Â Failures Data marts Executive Alignment (Marito and Hank sooner) Engagement with the business Setting expectations Successes Quick Prototyping Agile approach