Data is all around us and there are patterns to be uncovered. How data insights are revealed and shared needs to expand beyond the lens of a line of business’ purview. Data knowledge must take on the optics of an enterprise vision to understand customers better. But today, many FIs are still reporting in silos aligned to either products or organizational hierarchies. One unit’s analysis usually excludes insights from other products or groups, which can create confusing and conflicting customer analysis. This generates problems downstream as those contradictions are distributed to frontline workers, supervisors and managers who regularly engage with your customers.
Bringing enterprise data together for real value creation
Recent events have put a spotlight on the value of building 360° views of customers with enterprise data. The personalized and targeted interactions those 360° views enable, provide a distinct and compelling edge in attracting new customers and keeping existing customers loyal. These are the experiences customers expect after receiving years of streamlined engagements from Amazon, Netflix and other data leaders. Getting there requires making a transformation to a data culture.
What is a data culture? Simply put, it’s enabling your enterprise workforce with data-powered decisioning. It’s getting the right data into the right hands. The harder question is: “How do you create a data culture?” First, let’s define what culture is. In an office environment, culture is the manner in which staff execute against goals. It’s the way we do our jobs. It’s learned and shared norms, approaches, beliefs, assumptions and values whether they’re written or verbal. Strategies succeed or fail because of people. Culture influences their behaviors.
More than ever, you need a data culture
Here are four strategies that will help your teams create a data culture and drive success through the discovery of valuable patterns in your data:
- Prioritize data as a corporate strategy and start with a data health check –
1) Identify where and how data is used across your organization.
2) Take an inventory of requested data and reporting enhancements.
3) Brainstorm on how your customers might be helped with stronger analytics.
The crosshairs from these three are the beginning of a data strategy. The outcome is a better understanding of customers’ needs which you can meet with actionable campaigns.
- Develop programs to support a data culture – As an organization, you want to, simultaneously, make reporting and analytics easier and more comprehensive. Consider:
- Defining a common data language – Institutions are frustrated by different interpretations of analytics because different units may have different understandings of a data term or attribute. To solve this, standardize your data-speak. Ensure there’s a universal understanding of key data terms and that your data owners and report recipients are on the same page.
- Consolidating data teams instead of handling data by department, roles or products – A consolidated data & reporting team can help eliminate unit or product biases and misunderstandings in analysis.
- Empower your staff to make data-based decisions – Use analysis that takes enterprise data and build dashboards with visualizations, graphs and KPIs that provide insights at a glance. Add drilldown capabilities to better understand segments and individual customers.
- Involve people from the top-down and from the grass roots – Building a data culture is a change project. Major initiatives succeed with leadership buy-in and support throughout the entire project. Better solutions are built when front-line workers share feedback that includes how they use data, what works and what can be improved.
- Embrace your inner data geek – Data and patterns are all around us. I jog every day in my neighborhood. Along the way I see patterns, such as the number of residences that have overwhelming crabgrass and truck ownership that mirrors national sales percentages. There are two homes that still receive a newspaper delivery. Next door is a strip center with a grocer, restaurants, cleaners, barber, etc. The data and patterns are there in the locations, amounts, payment types and methods. Look for data in your everyday lives and apply that to your daily work by seeking patterns and insights beyond the spreadsheet and line-item reports.
Patterns are there and waiting for you to discover them. Look closer and encourage your teams to do the same. Reach across the enterprise and bring insights together. Then talk, strategize, and take action to create more satisfying outcomes for your customers.