Wings Financial has steadily grown its analytics and business intelligence functions with a focus on integrating capabilities across all departments.
HR has partnered with the analytics team to help ensure a fit for mission and skills.
CU QUICK FACTS
Wings Financial Credit Union
Data as of 9.30.19
HQ: Apple Valley, MN
12-MO SHARE GROWTH: 7.2%
12-MO LOAN GROWTH: 17.9%
As vice president of analytics and consulting services at Wings Financial Credit Union ($5.5B, Apple Valley, MN), Mike Lindberg knows well the challenge of finding the right people in a job market ripe with competition.
Lindberg’s task is made more challenging by the need to find people with the right mix of technical aptitude and collegial attitude to work in a collaborative culture across departmental lines.
But Lindberg doesn’t go it alone. Linwood Mielke, who joined the credit union in the summer of 2018 as an HR business partner, has helped Lindberg on his now five-year journey that has resulted in the creation of a data solutions department as well as Lindberg’s recent promotion to his current position after three years as manager of strategic analytics and member insights.
I lead a team of servant leaders who help satisfy our members and business leaders goals by understanding business process and strategy, building and leveraging deep analytical insights, and applying automation to create better and simpler solutions faster, Lindberg says in his LinkedIn profile.
Here, Lindberg and Mielke discuss the tactics, strategies, and philosophies that drive their daily approach to unifying BI and analytics across the Twin Cities-based cooperative’s business units.
How big is your staff? Is it difficult to fill jobs in your market?
Linwood Mielke, HR Business Partner, Wings Financial Credit Union
Linwood Mielke: We currently employ approximately 575 people across our organization. We’ve hired more than 100 team members this year the majority within our branches.
We also focus on internal development. We focus on the employee and human experience intentionally identifying our people as the base of our strategy map and recognizing their innovative ideas and contributions. We’re fortunate to have a solid foundation of stability and growth in our 80-year history of serving members. These, along with investments in total rewards and compensation, help establish Wings as a great place to work. Employee feedback has led to seven consecutive years as a top 150 employer in the state of Minnesota.
These are some of the factors that make Wings an attractive place to work and drive the number of strong, talented applications.
Read more about how Wings Financial is making data take flight and how other credit union analytics leaders would do things different, or the same, in launching their own programs.
What changes have you made in your hiring approach to ensure a cultural match with people who have the right skills?
Mike Lindberg, Vice President of Analytics and Consulting Services, Wings Financial
Mike Lindberg: We added an assessment in 2019 and have reduced the focus on technical questions over time. Now, during the interview process, we focus on problem-solving and relationships. We also explore team values and principles. We generally find in asking these types of questions that the candidate communicates enough about the technology for us to gauge their knowledge.
Interviewers grade candidates on a 1-10 scale in three categories: solutions leadership, business relationship, and technical application. Understanding where the candidate is on these three categories helps us know what makes a great fit for the candidate and for the organization.
What is the structure of your data solutions department? How long has it taken you to get there?
ML: We currently have seven full-time employees: a manager, a data scientist, four data solutions consultants, and one data solutions analyst. We also have two data science summer interns each summer.
We’ve grown steadily the past four years, adding one to two positions annually due to growth and employee turnover, but mostly growth.
How do you find and recruit applicants for your data solutions department?
ML: We post positions to our career site and many job boards and reach out to placement agencies to help us find candidates that fit the qualifications. Once we’ve reviewed applicants, the HR business partner and then the data solutions manager and/or I will interview the candidate briefly to identify their fit with the team and to see if they share the values and have the skills to help the team succeed.
If the candidate passes this round, there’s a candidate assessment. Then there’s a second round of interviews that involves the analytics team, followed by a reverse interview, where the candidate interviews a senior leader, and then a debrief with the manager of data solutions.
LM: The collaborative approach to recruiting is key to selecting the right individual. It leads to the determination of mutual fit which is a primary factor in determining the right candidate.
We focus on problem-solving and relationships. We also explore team values and principles.
How do HR and the business unit partner in this process?
LM: Interviewing is a team effort for all roles at Wings Financial. A candidate will often find an interview process consisting of representatives from the role’s department, key stakeholder groups or partnerships for the role, human resources, and their leader.
Part of my role is to help the hiring manager consider team and company dynamics that might exist when selecting the best qualified candidate. Understanding the specific business, services, and needs of the operations as an HR partner opens the door for trust, candor, and creative decision-making that positively impacts our membership.
I should add that the partnership is not only with leaders, but with all employees and their individual needs. Together, we facilitate the delicate balance of employee, leader, and organizational needs that result in growth, development, and innovation.
How much does experience matter versus education? Do you hire people who have degrees from unrelated fields but people and learning skills?
LM: When we develop a job description, we do our best to consider the necessary qualifications to be successful in that role. In some cases, there are specific proven paths to success from specific education or certifications. Unless otherwise required for a specific role, the relevant application and adaptation of learnings to different and sometimes ambiguous scenarios is more important, however those learnings are obtained.
I’m a strong believer in the importance of being a lifelong learner. Formal education is definitely one path to fulfill this, but lifelong learning is not a one-size-fits-all path. Learning every day from experiences and adopting that learning in the future is important with or without formal education.
ML: Having said that, data science is a whole different ballgame. There’s a greater degree of knowledge, methodology, and technical/statistical understanding necessary to be successful. For this reason, Wings currently looks for candidates that have education and/or applicable experience in the data science field to be a candidate for any data science positions.
Although this thought process will likely change as technology comes to bear, we’re finding that a data scientist position is far more specialized than that of a BI analyst or data solutions consultant.
Can you elaborate on what it takes to be a BI analyst or a data solutions consultant?
ML: Many pieces of analytics are an exercise in understanding and clearly defining a problem. For these items such as data integration, building dashboards, and reporting the learning curve to begin producing valuable deliverables can be quite short, assuming the foundation and structure are built appropriately.
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Most of the organization’s day-to-day needs fall into this bucket, and I confidently say it is possible to train someone within 60-90 days to be functional, assuming the desire and aptitude is there.
From there, a desire to learn with a focus on how data can help the business and being surrounded by passionate data professionals who enjoy serving one another will help stabilize them within the first year. The technology is the easy part and can be trained quite easily if the employee wants to learn and serve their business partners.
How do you find out enough about a candidate to get a feel for how they would do in your environment?
LM: There is both an art and science to selecting a candidate first in forming a hypothesis based on initial facts that could include the resume and/or first responses to questions. Supporting that hypothesis with deeper fact is what solidifies a selection.
A lot of my initial questions surround core principles important to our organization and the role. Follow-up questions that dig deeper into responses are more important. There is a lot to say about the character a candidate demonstrates in representing their past experience, successes, and mistakes. Humility is important to understanding one’s role and ownership of their actions and to predicting how they will actually perform at work.
Talk a bit about your data science summer internship program.
ML: We’ve seen incredible interest in the program, including more than 500 applications for two positions in 2019. Our internship program provides both work on real-world problems within the department and a cross-functional summer program led by our HR department that includes team-based activities for all interns across the organization.
Our interns don’t do the boring, monotonous stuff. They invest themselves in developing models and recommendations on how to address a business problem they choose. We’ve benefited in the quality of deliverables that have come from our interns over the years, many resulting in adopted solutions.
One of our full-time data scientists was an intern with us first. And we’ve had other interns transition into regular employment in application development, project management, and commercial services.
At a Callahan roundtable for analytics executives earlier this year, you described one job applicant who did flawlessly on everything but didn’t want to take a three-hour test. So, he withdrew his application. Is that typical?
ML: We have a fairly rigorous interview process for our analytics positions. We do this to ensure the right fit for both the candidate and the organization.
Over the years, we’ve adjusted and added portions, some of which have added extra time commitments to the process. Most of our candidates understand this is a mutual opportunity to find the right fit and are encouraged by the process, but a few have chosen to not move forward when we explained the time commitment.
LM: Piggybacking on Mike’s response, we recognize it’s a hard ask to request someone spend a few hours taking an online assessment that might not result in an offer of employment. The important thing to note is that this is a validated and leadership-trusted data point along the journey to selecting the right talent for certain positions and for successful development if selected.
It’s also a tangible cost to the organization. Both the tangible cost of this assessment and the cost to the candidate in terms of their own time spent, however, is much less than either party making the wrong decision.
This interview has been edited and condensed.