The need for data analytics talent

Staying abreast of current data and analytics technology and practices can help community banks maintain their inherent relationship advantages. Hiring qualified data analysts to dive deep into banking data and create meaningful analytics presents a considerable challenge for community banking and credit union executives.

According to recent Gartner research, the focus on the human dimension to data and analytics has three key attributes:

• Driving adoption of analytics by working with business users to ensure accessibility, trust, and relevance to business users.
• Recognizing human involvement across the range of decision-making, from decision support to decision automation. Even the most automated decision-making process needs human involvement in its initial design and formation – and in its subsequent monitoring and evaluation.
• Ensuring analytics deployments consider the multiple aspects of risk.

Here are some guidelines and insight I’ve seen at institutions across the country that address the important challenges of the human side of data analytics: obtaining, training, and retaining data analysts.

Recruit both traditionally and non-traditionally

Community bankers often can’t afford full-time recruiters to scout college campuses for data scientists and technology-focused students potentially interested in banking/fintech careers.

The Georgia Fintech Academy, a collaboration between Georgia’s fintech industry and the University System of Georgia, provides this service to bankers in the Southeastern U.S. They help create interest in fintech, offer appropriate technology courses, and match students to organizations seeking resources. These connections establish linkages and insights on both sides of the table.

Kim Kirk, Chief Operations Officer of Queensborough National Bank and Trust Company, noticed a shift in students’ interest at a Georgia Fintech Academy event with talents more geared toward data analytics, machine learning, and predictive analytics which she noted is “Somewhat different from resumes I have seen from recent college graduates in the past. Data analytics and predictive analytics are particularly interesting to me as we build out our data warehouse and mine our customer data to better understand our customers’ financial landscape, habits, and needs.”

Traditional recruiting methods still help in the search for quality data analytics talent. Community banks can offer younger candidates a chance to learn all aspects of a bank’s business model, as opposed to one facet of banking, which is inherent in many entry-level jobs in larger organizations. Selling this advantage to potential candidates via online recruiting tools, using current staff to recruit friends and family, and trying to convert a hire from larger competitors remain relevant hiring strategies.

Train with purpose

Once a data analyst has been hired, training becomes critical to ensuring both job satisfaction and delivering meaningful analysis.

Gone are the days of rotating younger new college hires through management training programs in lengthy exposures to all a bank’s functional areas. Market and competitive demands dictate these valuable resources make an impact. Instead, institutions today should assign the new data analyst to one area within the bank with a specific pressing problem that can be solved with insightful analytics.

Partner the new employee with a Senior Business Analyst (or analyst type) who understands what results are needed. This expert can help guide the iterations of data-gathering and analysis conducted by the new hire. This solves an immediate problem approach and provides the dual advantage of relevance and timely productivity.

Beyond this initial primary assignment, ensure the new employee takes any online banking courses your institution has access to, such as Banking 101 topics available from training vendors. And don’t forget to start the Risk and Compliance training that is so critical to bankers in current times.

Retain creatively

Apply new thinking to the old problem of employee retention as it relates to data analysts – whose value will increase exponentially with their financial services experience:

• Offer clear and relevant career paths and opportunities within your organization.
• Think of management approaches in new ways.
• Be open to remote and flexible work options that may stretch existing policies within your bank. This same thinking applies to personal workspaces and vacation policies.
• Pair mentors to data analyst new hires who can help these employees navigate not just the world of banking, but the politics inherent within any organization of more than two employees.

In addition to banking training, ensure your bank has the budget for the technology tools, such as Microsoft Power BI, that data analysts require to perform optimally. And allow for employees in this area to attend conferences and vendor courses to expand their capabilities and creativity relative to new data analytics trends.

The time to staff is now

The race for personalization of customer experiences is well underway in banking. If community bankers don’t invest in data analysts to mine their unique data sources, they risk falling behind to the point of no recovery. The time to staff thoughtfully is now.

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• Source: https://www.finextra.com/blogposting/25572/obtaining-training-and-retaining-data-analysts?utm_medium=rssfinextra&utm_source=finextrablogs