I was fortunate to be interviewed for an article titled “Fueling Revenue with Data-Driven Marketing Campaigns” in The Financial Brand’s Spring 2024 Insights issue. Written by Alkami, it’s a great deep dive into using data and it prompted some questions and thoughts I’d love to expand on.
Data silos, or simply the fact that every organization has data spread across their teams, is a problem. This is not news to any reader. We’re hoarders of data!
What might be news is that we often do not align roles, skills, or talents to meaningfully impact how we gather, share, and optimize data. There are specific and unique skills to each step of using data. From collecting and cleansing data, to reporting, visualization, and analyzing data, each of these steps requires different knowledge and skill sets. And an employee’s talent sharpens the effectiveness of each step.
Let’s think more critically about both of these topics.
Siloed Data = Partial Insights
Departments like lending, marketing, and operations each collect invaluable data. When isolated, they only paint part of the picture. We know this, but I’m not sure we appreciate this. Siloed data can lead to inconsistencies in how data is defined and can lead to miscommunication. For instance:
- High-Value Customer: The lending department might define a high-value customer by one level of outstanding loan balance, while marketing might focus on a totally different balance when making decisions. When you say high value, what do you specifically mean?
- Deposit Balance: A customer’s deposit balance can be a simple metric, but how it’s presented matters. Is it the balance on a specific date? Is it the average balance maintained throughout the month? Is it a rolling average balance calculated over a longer period? This can matter with the ebb and flow of checking account balances, or seasonality with business deposits, and effect how we make decisions.
Data Literacy is a Spectrum
We hire talented bankers for their skills in finance, relationship building, and risk management – not necessarily for data analysis. Different data tasks require different skills. It’s common to not cultivate these skills or appreciate the differences and what this means a data moves from a number on your core to an actionable decision point. A quick run down highlights basic differences.
- Ensuring data quality requires meticulous attention to detail and strong data governance practices.
- Data visualization, on the other hand, is a creative field that thrives on clear communication and the ability to translate complex information into easy-to-understand formats.
- Data analytics combines both technical and analytical abilities – the ability to manipulate data sets, identify trends, and translate those trends into actionable insights.
Experience, role, and knowledge can create gaps or differences in how data is used and interpreted. A seasoned loan officer might be highly skilled at evaluating financial statements and creditworthiness, but struggle with advanced statistical analysis. Conversely, a recent graduate from a data science program might be adept at using complex algorithms, but lack the institutional knowledge to fully understand the context of the data they’re analyzing. By recognizing these varying levels of data literacy, we can provide targeted training and tools that empower everyone to leverage data effectively within their specific roles.
Next Steps for Success
It might seem like these topics are separate and different areas to tackle. But in reality, the bigger the silos the more likely it is there’s a mismatch of talent working on different aspects of the data’s journey within a financial institution. They’re connected and intertwined, and most organizations need to recognize this and find collaborative solutions.
Here’s how to unlock the power of data within your institution:
- Create Collaboration: Foster interdepartmental collaboration and create mechanisms for data sharing. Simply cataloging and sharing data sources, finding common definitions for data, and centralizing data platforms can be powerful steps. Most readers have regular meetings to discuss risk or marketing, do the same for data.
- Invest in Data Talent: Build a dedicated data team or foster skills sets across your organization. Data tells a story which we make decisions on. Those decisions cost money. Investing in developing this skill set can have immediate financial returns.
- Train and Empower: Offer continuous training to increase data literacy across the organization. Tailor training to different roles and skill levels, providing tools for reporting, visualization, and analysis.
- Match Jobs to Strengths: Recognize that data or reporting is not a job or task, it’s a skill and talent that should be aligned with a role like any other position in your organization. Create pathways for data-focused individuals to thrive.
- Translate Data into Action: Emphasize using data to answer business questions, identify risks, predict trends, and personalize customer experiences. It’s about decisions, not just dashboards. Do the math!
Banking isn’t about who possesses the most data; it’s about who uses it most wisely. Aligning your greatest asset – your people – with the power of data will drive better outcomes. Just as we tailor financial products to our customers’ needs, tailoring our approach to data based on skill sets will empower everyone to contribute to a more data-informed, and ultimately, a more successful institution.
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