How to Design and Execute A Compelling Banking Data Strategy in 3...
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How to Design and Execute A Compelling Banking Data Strategy in 3 Simple Steps

By Andre Iervolino, Vice President, Business Intelligence & Data Analytics, Financial Partners Credit Union

Andre Iervolino, Vice President, Business Intelligence & Data Analytics, Financial Partners Credit Union

With over 20 years of local and international experience in corporate planning, marketing, strategic research, business intelligence, operations, customer success/engagement, and digital transformation in various industries such as Xerox Corporation, the American Chamber of Commerce for Brazil, and multiple Credit Unions, Andre has created and executed strategic and action plans generating millions of dollars in revenue for the businesses he has worked for. In addition, he is an expert on talent acquisition, development, and retention of diverse multi-cultural teams. In all his corporate roles, he has successfully leveraged the use of Big Data through data analytics to make organizations prescriptive enterprises. 

Data, Data, Data…finally, organizations of all sizes from all kinds of industries have arrived at the conclusion the data they have about their customers, their markets, their competitors can be transformed into actionable intelligence through the application of data analytics strategies and methodologies. In this article, I will walk you through 3 simple steps you can and should consider adopting in your organization to successfully deploy an effective data strategy and make an impact on your business’ key success metrics through stellar data analytics execution. Are you ready? Let’s go!

Step 1: Identify Your Organizational Business Drivers

This step has nothing to do with business intelligence, data, and analytics. In fact, before you ever think of designing a data strategy for your organization, you must identify which key metrics are the most important ones. Only then you can craft a successful data strategy and Business Intelligence strategic and operational plan. Below are examples of key Banking organizational business drivers/metrics I have used and continue to do so:

-Customer Acquisition: number of new and current customers
-Customer Retention: number of lost customers and annual attrition rate
-Customer Participation: deposit, investment, loan balances, product per customer, product mix
-Customer Engagement: net promoter scores, loyalty scores, cross-selling indices, social engagement scores, repeat purchases, length of relationship, transactional volume and types (Top Wallet status), service mix, service delivery mix
-Net Income (self-explanatory) 

Step 2: Understand How These Business Drivers Can Be Impacted

Now that you have identified the most important organizational business drivers, you must ask yourself “which are the dimensions of the business that impact the organization’s business drivers the most?”

Dimensions of the business with most impact:

-Pricing: margins, demand elasticity, incentives, operational efficiencies
-Product Development/Design: demand for new/current products, features, product cycle, future road maps
-Promotion: brand positioning, target marketing, cross-selling, lead generation, offerings
-Place/Distribution: service delivery road map, market entrance/exit, branch optimization, sales channels efficacy, platformication, data science application
-Process: organizational and departmental improvements, customer experience, AI application
-People: culture, executive/Senior/Middle management, sales and technical forces, talent acquisition, development, retention, tool box

"Approach your data strategy and analytics planning and execution with the mind of an entrepreneur"

Step 3: Design a Business Intelligence Strategic and Operational Plan (Short and Long Term)

Now that you know your most important organizational business drivers and areas on how to impact them, you design a 1-3 Year Business Intelligence Strategic and Operational Plan for the enterprise. The model I follow for the creation of this plan is the same model I use for the design and execution of corporate strategic plans. You must approach the development of this plan as if your Business Intelligence and Data Analytics business unit is its own business within your company. On other words, approach your data strategy and analytics planning and execution with the mind of an entrepreneur! Here are the elements that comprise a successful BI Strategic and Operational Plan:

-Vision: Who You Want to Become
-Mission: What Your Purpose Is
-Primary Data Strategy: What You Will Be Doing to Fulfill Vision and Mission
-Key Results Areas: Why and Where You Will Focus Your Attention, Efforts, Resources on
-BI Services/Dimensions: Areas of Specialization by BI Sub-Divisions
-BI Integrated Programs: How, When, and to/for Whom You Will Be Executing in Excruciating Detail

-Success Metrics/ROI Analysis and Feedback Loop

And that’s it! Now stay tuned for the next article where together, we will dive into specific examples of successful BI vision/mission statements and data strategies, strategies to impact key results areas, the sub-divisions of BI departmental structure, and the 10 Business Intelligence Integrated Programs I have designed over the years that will take your data analytics from A (start) to Z (the finish line).

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