Data-Driven Work Cultures: Jay Franklin of First Tech Federal Credit Union On How To Effectively Leverage Data To Take Your Company To The Next Level
An Interview With Pierre Brunelle
Being successful as a data- and insights-driven organization requires an organizational strategic priority, mandate and an operational pivot to break down silos.
As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing Jay Franklin.
With more than 25 years of experience in the data and analytics industry, Jay Franklin, Vice President of Enterprise Data and Analytics at First Tech Federal Credit Union, has an intimate understanding of how to leverage data to inform and drive organizational transformation. To meet the evolving needs of credit union members, Jay helps cultivate deep member relationships by leveraging trustworthy data and insights, while consulting with industry leaders to understand the importance of data and insight-driven decision making.
Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
When I started my career, there was no specific career path for data and analytics professionals. I pursued a dual education in both business and technology, then started my career in sales, marketing, product management and finance. In the early dot.com days, I transitioned to management consulting and technology/systems consulting. From there, I seamlessly transitioned to helping clients implement Salesforce automation, customer relationship management and e-stores — helping organizations understand and leverage their system-collected data captivates me. In the early 2000s, I specialized in data warehousing, business intelligence and analytics from a systems implementation and from business insights creation perspectives. Over time, the disciplines of data and analytics became mainstream staples. My background in business and systems implementation gives me a valuable, broad perspective.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?
I have derived value from my career mistakes by leveraging them as learning experiences. Although I can’t recall a “funny” mistake, I can say the most important lesson I’ve learned is to ask for help. Early in my career, I strived for perfection. If things were not delivered packaged in a bow, I feared being perceived as behind. I equated feedback for improvement with failure.
I learned that my colleagues and leaders felt fulfilled when they were able to aid my professional growth by offering constructive feedback. Understanding this, I now eagerly share drafts and partially developed ideas with coworkers and seek their feedback. This approach provides me with great ideas and helps my coworkers feel valued and involved.
Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?
“Heart of Darkness” by Joseph Conrad is the book that has inspired me the most throughout my life. The story is about being in a situation that calls for great internal strength, focus and perseverance because your known support system, cultural norms and institutions are not present in a strange and ominous surrounding. The moment calls for you to identify the source of your sanity, clarity, values and strength. This source in “Heart of Darkness” is called “backbone.” When placed in a surrounding or situation absent of any familiar support, you must call upon this “backbone” to guide you and maintain your sense of self, purpose and values. For me, this inner strength comes from a passion for continuous learning and the confidence to know I will use that learning to determine the best course of action, especially when I may lack a guide to help me to do so.
Are you working on any new, exciting projects now? How do you think that might help people?
We have many exciting projects underway, including improving our master data management capabilities, analyzing and predicting member behaviors and preferences, as well as skill-building at multiple levels across the organization. Accomplishing these objectives will help everyone improve their data and analytics savvy. We are all in!
Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data and insights-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization. So I’m particularly interested in this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?
Building a data- and insights-driven culture requires working cross-functionally, collaboratively and thinking in new ways. It takes everyone’s effort. Being insights-driven comes down to cultivating three priorities: trustworthy data, trustworthy insights and measurable skills growth.
- Trustworthy data relies on developing enterprise governance over a trusted source of data. In many organizations, this involves the curation of an enterprise data warehouse or data lake, but it can also be created virtually through concepts such as data fabric or data mesh. The key is that there becomes one, governed source of truth for any given analytics data set to achieve scalability, security and data integrity.
- Trustworthy insights require a governed, consistent process to ensure that business intelligence dashboards, visualizations and data science models are accurate when deriving insights. This process should include standards for certification of the work product to ensure the proper use of data, query logic, tools, etc.
- Measurable skills growth ensures that employees and executives have the skills required to produce relevant insights and make business decisions, based on these analytics insights — both sides of the coin require skills.
Which companies can most benefit from tools that empower data collaboration?
Every company can benefit from data and analytics collaboration. Throughout my career, I have successfully developed data and analytics strategies and multi-year plans to deliver the platforms and the analytics insights to drive informed decision-making and action-taking in the financial services, high tech, healthcare, pharmaceutical, business equipment and entertainment industries. The distinct application and scope of data and analytics will vary from company to company and across industries, but the overall results are similar: if relevant data is correctly managed, governed, understood and analyzed, it can be used to drive revenue, increase efficiencies and enhance personalized customer experiences.
Often, the roadblock to becoming a data- and insights-driven organization isn’t the lack of appropriate tools and technology, but the incongruity of business leaders and data scientists’ perspectives and knowledge. Members of data and analytics teams need to be culture shift persuaders, while business leaders need to be willing to listen and adapt according to data analytics insights. The competitive landscape and pace of change in various industries calls for continuous learning and upskilling at all levels. Business professionals need to be more data and analytics literate and inquisitive, while data and analytics professionals must develop more business acumen and improve their ability to tell stories with data — both visually and verbally.
We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.
When I joined First Tech, I quickly realized that the IT team was overburdened trying to keep on-premises systems up and running, while also trying to implement a hybrid cloud strategy. This lack of reliable performance and uptime was impacting an early attempt at building a data warehouse and driving the adoption of a business intelligence toolset. To combat this issue, I developed an enterprise data and analytics strategy, including a multi-year plan to implement cloud-based data and analytics platforms.
The plan’s first priority was to free up the team’s time by transitioning the enterprise data warehouse effort to Snowflake, a robust cloud data platform. No longer concerned with platform infrastructure, the team turned their attention to collecting and analyzing data to improve operations and enhance members’ experiences. It is rewarding to see that we have completed more than eight major technology implementations in a few years. Now, our focus has shifted to the analytics insights and the data practice skills and behaviors needed to understand our members at a personalized level to improve their experiences and get value from our investments in data capabilities.
Has the shift towards becoming more data and insights-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?
For many teams, the shift to being data-and-insights-driven is an inertia problem, rather than a cognitive hurdle. Incorporating new methods and insights requires a shift away from old ways; this challenges the instinct to act quickly. The desire to quickly do “something” may result in not doing the “right thing.” It is important to remember that making the wrong decision can be costly. Quality results often require a time investment.
Additionally, people often confuse coincidence, correlation and causality. Observing trends between two variables inclines business leaders to take action, based on their assumption that a certain outcome can be ensured. For example, viewing a graph showing that people who bought a particular car and had viewed advertisements from the manufacturer could be interpreted as the ads independently causing the car purchases. However, it is equally likely that people who were already interested in buying that car chose to look at the ads. In this case, spending more on advertising does not necessitate more car purchases. Organizations need to build the skills of the consumers of analytics (i.e., business leaders) to understand what analytics tell them and whether any specific action could cause a change in outcomes. They need to evolve from consumers to participants.
Successful organizations operate with a data- and insights-driven focus and a growth mindset and promote data literacy organization-wide. Without data literacy, the full potential of the data may not be utilized because people will not understand what the insights from the data are telling them.
Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.
- Empower data + analytics people to be cultural data literacy catalysts within an organization
- Align and incent leaders and employees to work cross-functionally toward the common goal of becoming data-and-insights-driven, openly sharing data and insights across an organization so all departments have access to the same understanding of the customer
- Build a governed single data source of truth and managed analytics tools that employees are properly trained to use
- Utilize a digital + human approach that relies on analytics
- Balance data collection and privacy
Being successful as a data- and insights-driven organization requires an organizational strategic priority, mandate and an operational pivot to break down silos.
The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?
As previously mentioned, two of the most important values that promote a data-driven corporate culture are a collective growth mindset and the promotion of data literacy. At First Tech, we found that one general industry roadblock to data understanding was a lack of internal consistency, which is why we developed and distributed a catalog of important business data terms with definitions to our employees.
Another common barrier to a data-driven culture is workplace silos and conflicting incentives among departments. This results in people frequently manipulating insights or metrics (whether consciously or unconsciously) to be self-serving. Having conflicting answers to the same questions makes data insight neutrality difficult and can lead to overall distrust of data-based decision-making. Real competitive advantage is created by working together and being informed through data and analytics insights.
The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?
The pandemic spurred the wide adoption of technology across many industries, and this momentum will only accelerate as we move out of the pandemic. The financial services industry adapted quickly, as the adoption of digital banking was greatly expedited. At First Tech, we’re moving to create an excellent digital and human experience since our members crave both — meaning if a member starts a loan application online, but runs into issues, they can simply pick up the phone and speak with a representative who already knows what the issue is for guidance.
The pandemic pushed organizations to consider how to build trust through personalized online experiences. Simultaneously, consumers were propelled to use more digital solutions. This became a dilemma because consumers crave trusted relationships with financial services providers, but they primarily do their banking on mobile devices. To provide relevant experiences with technology, organizations must prioritize proactively collecting data through various channels and at every reasonable opportunity. Digital banking allows consumers to make choices more easily from anywhere, but their choices often rely on their perceived relationship with a financial institution. Over the next few years, data and analytics use will evolve to cultivate more personalized digital interactions between institutions and their customer base.
Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you?
Given that we are a credit union, we don’t simply have customers; we have members who own us and who depend on us knowing their goals throughout their life stages. To this end, Member Centricity (generically called Customer Centricity) is the name of our game. Everything we have talked about in this interview has to be in place if we are to continue to meet and exceed our members’ needs and expectations; it requires a coordinated enterprise-wide commitment and aligned effort. We are super excited about the opportunity this brings to First Tech to be the trusted financial institution of choice for our current and future members.
How can our readers further follow your work?
You can follow First Tech on Twitter, LinkedIn, Facebook, Instagram and our website.
Thank you so much for sharing these important insights. We wish you continued success and good health!
About The Interviewer: Pierre Brunelle is co-CEO and Chief Product Officer (CPO) of Noteable, the collaborative notebook platform that enables teams to use and visualize data, together. Prior to Noteable, Brunelle led Amazon’s internal and SageMaker notebook initiatives. Pierre holds an MS in Building Engineering and an MRes in Decision Sciences and Risk Management.
