Data and Analytics Roles at your Credit Union

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Digital innovation is sweeping across the financial services industry and creating opportunities for banks and credit unions to leverage data as a source of competitive advantage.

Until recently, most credit unions were delegating data management and analytics to the IT department, which in turn created data silos that inhibited the enterprise use of data.

Has your credit union made the business case for creating an analytics team to spearhead important data initiatives? If so, you now need to hire or train the right talent that can turn data into value and deliver on your organization’s data strategy

Chances are you have numerous questions whirling around about how to define the key data roles and responsibilities.  When venturing outside the credit union to evaluate data leadership, this list of tips breaks down key roles and how they should align with your needs.

Chief Data Officer

The CDO is a senior executive who bears responsibility for the credit union’s enterprise data and analytics strategy, data governance, data management, and data utilization.  The CDO’s role will combine accountability and responsibility for information protection and privacy, information governance, data quality and data life cycle management, along with using member data to create business value. 1 

This last point is arguably the most crucial.  If your analytics team is not delivering business value then you’re not achieving the team’s full potential.  The CDO should focus on measurable outcomes for specific use cases to provide the necessary cultural and change management sparks to garner enterprise-wide buy-in.

Data Scientist

A data scientist masters a whole range of skills and tasks from being able to handle the raw data and analyzing that data with the help of statistical techniques, to delivering actionable recommendations based on the underlying data.

The title “Data Scientist” has become a bit of a buzzword as of late.  If your “Data Scientist” can query a database, but the extent of the statistical knowledge is mean, median, and mode…they aren’t a data scientist.

“Real” data scientists have deep knowledge of statistical and probabilistic models and know how to leverage those models for specific analytic applications.

The Data Analyst

The data analyst will retrieve and gather data, organize it and use it to reach meaningful conclusions.  The insights that data analysts bring to the credit union can be valuable in identifying and even helping to predict the needs of the credit union’s members.  They help develop effective ways to collect the data and compile key findings into reports to share with other teams within the credit union.

Think of the data analyst as the individual who translates between the technical world and the business world.  This individual needs to have basic competencies from a technical perspective, but, most importantly, they need to be able to interpret technical knowledge into practical business terms and vice-a-versa.

A good data analyst doesn’t just produce charts, graphs, and other fancy visualizations.  They produce clearly articulated meaning to describe what the visualizations mean to the business.

ETL Developer/Data Engineer

The ETL Developer/Data Engineer is a critical member of the data analytics team as they are dedicated to the fundamental process of capturing, storing and processing your data.  If your CU leverages a data warehouse as your analytics platform, then the “ETL Developer” most aptly describes the job title.  If your organization is leveraging a data lake or hybrid platform, “Data Engineer” is a more appropriate title.

In the end, this role boils down to ingesting new data sources into the platform.  This may come from non-core third-party applications (i.e. consumer LOS, real estate LOS, online banking, etc.) to external data sources (i.e. demographic data, economic indicators, social media interactions, etc.).

Report/Visualization Developer

To effectively deploy self-service reporting and analytics through your BI portal (i.e. Tableau, Power BI, Information Builders, etc.), someone must be tasked with creating these reports and dashboards. This is the critical role of the Report/Visualization Developer.

If your credit union embraces a more decentralized approach to data analytics, then these resources may reside in the business areas instead of centrally managed.  Regardless of where they reside within the organization, this is an essential function for providing a front-end to your analytics platform.

The Right Role for Your Credit Union?

As credit unions grow and look to remain competitive, there’s an obvious need to hire the right data talent who are highly skilled in analytics, who can interpret data, and insight and tangible business value. Demand for data expertise is growing every day. Be sure to understand which roles are specifically needed by your organization.  Most credit unions don’t have the necessary budget to hire each of the resources discussed.  Determine where the greatest internal need exists and identify strategic partners who can assist with the rest of the functions.

The bottom-line, all organizations have the power to become data-driven by accessing data skills – and on almost any budget.  Ready to formulate a winning data analytics strategy?  Contact The Knowlton Group to get started.

Sources:

  1. Gartner Chief Data Officer Survey

 

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Why the Lag Part 2: Solutions to Top Data Analytics Challenges

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If you have reviewed the some of the important steps and hurdles to overcome for credit unions to improve their analytics maturity outlined in our first article on Why the Lag, then you are ready for some more steps in the process.

Challenge:

 Maintaining data quality is a hurdle for many credit unions, but it is a critical component to becoming data-driven. To achieve consistent and reliable member data, credit unions must constantly manage data quality at the source so that they can trust and use the data to enable quicker and more knowledgeable decision-making.  As the saying goes, “garbage in, garbage out” so the importance of clean data can’t be understated.

Solution:

Step one is to know what data you’re collecting, why you’re collecting it and where it comes from.  Make sure that every component is coming from a trusted and knowledgeable source. Validate data as it is entered by automatically flagging missing, incorrect, and/or inconsistent information. Whenever possible, eliminate the opportunity for free-text fields and opt for drop-downs instead.

If you discover problems with incoming data, go all the way back to the original source to make corrections.  The data warehouse or analytics platform is not the place to make those data quality corrections.  Otherwise, you will constantly be correcting for inaccuracies.  Use the data warehouse to identify issues, and then make the corrections at the source.

Challenge:

Lack of leadership buy-in is another challenge we see for those credit unions failing to successfully implement a data strategy. For any new initiative to work well, all departments within they credit union need to communicate, work together and see the payoff of becoming data-driven.  Buy-in will require fortitude and integration into the strategic plan, culture and budget.  This is where analytics becomes as much of a change management problem as it is a technical one.

 Solution:

 To gain support and financial approval for your data analytics initiatives, you need to give senior managers a snapshot of how these efforts can pay-off.  Be sure to provide the “why” the credit union should invest in data analytics and the multitude of ways the data will improve efficiency, member engagement, marketing effectiveness and more. Be transparent and encourage team members to want to be a part of this transformation with concrete examples of how it will improve the “whys” for your credit union (time savings, member service increase, cost reduction, etc.)  Show evidence and examples of how the competition is using data to grow and increase market share.

 Challenge:

 A lack of analytics talent is a major obstacle faced by credit unions desiring to be data-driven. Hiring, training and managing highly skilled, knowledgeable, data-savvy personnel is costly. Given the explosive growth on the job posting sites for those with analytics expertise and the intensifying competition to fill more jobs than there are qualified people, it is difficult to attract and retain the right talent.

Solution:

An effective data analytics talent effort should consider not just compensation but also cultural fit. Striking this balance is critical to set both the data scientist/ data analytics hire and the credit union up for long-term success. Also, consider if anyone in house has the foundational skills necessary to build upon.  Your “Excel gurus” could very well be trained to become your organization’s modern analytics expert.

Millennials, particularly, find it appealing to work with organizations with a strong social and community conscience.  Credit unions inherent operating model – from their community focus to their charitable presence – are well-positioned to offer job applicants the right cultural fit.

Still not sure if your internal team has the right skills?  Consider working with outsourced firms that can augment your internal data efforts.

Is your credit union making the most of member data? If not, what is holding you back?  At The Knowlton Group, we believe that every organization – no matter their size – can become data-driven. The best data and analytics program starts with a great strategy and clearly defined roadmap and implementation plan. Our personalized approach to each engagement ensures that the specific needs and goals of your credit union are captured for maximum results. Want to know how you can further improve your members’ experiences? Let’s talk. Contact me today at brewster@knowlton-group.com or call 860-593-7842.

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Hiring a Chief Data Officer? 5 Qualities Not to Overlook

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With the rapid rise of data analytics, there is a high demand for a key player in the workplace — the Chief Data Officer. The CDO is quickly becoming a new hero for financial institutions ushering in digital transformation. From uncovering profitable insights to developing data-backed business strategies and keeping data systems clean and relevant—the CDO is proving to be an essential addition to the org chart.

If you are a financial institution and are looking to fill the CDO position or outsource this expert to oversee a major data initiative, you will want to start by knowing the profile of this key new executive position.

Below are some essential qualities not to overlook as you seek the right CDO for your organization:

A Team Player

Every organization is split into divisions, groups, or departments such as Operations, IT, and Finance. But, when it comes to sharing customer and organizational data, silos can be detrimental to the success of any data and analytics project. Data needs to be shared and processed freely. Therefore, a key quality to seek is someone with a team player mindset—able to help break down silos and ensure all relevant roles in the financial institution have access to data that impacts their decisions. Since the CDO understands the data on so many levels, they will work with the rest of the C-suite to maximize the value data can provide to the organization. Most CDOs are usually tasked with using the information to automate business processes, understand customer behavior, and ultimately utilize data as a business asset. Collaborating with department heads and working with other teams will be critical.

An Industry Expert

The CDO is a role that requires being able to understand all different aspects of data analytics – from data quality and data governance to data integration and data visualization. But for financial institutions to truly reap the benefits of hiring a Chief Data Officer, an ideal candidate should understand the financial services industry. They should have experience working within the credit union or banking space, have a thorough understanding of the stakeholders, the target customer base, and any industry challenges. They will use this knowledge to help define, develop and implement how the FI should leverage data for maximum business outcomes.

A Referee

One of the top motivations to hire a CDO is to help capitalize on data opportunities and drive revenue. The CDO needs to act as a referee to ensure data is used correctly, is clean and can be used for insight and action. Just as important, the CDO will need to drive ways that data can be used for innovation. Basically, your CDO needs to be good at playing offense and defense. The CDO needs to create data management processes, policies and tools to make the data more useful. The CDO can help unlock data for better marketing, and greater customer service opportunities. But, they will also need to help secure and safeguard the data. Being able to play on both sides of the data equation is critical to the success of data-driven projects.

A Data Champion

For many FIs, data analytics is still a relatively new area or concept. Therefore, a CDO will need to champion the data and be the leader for what a strong data strategy can achieve for the FI. By championing the data, the CDO will constantly be working to improve the quality of the data and should encourage users to follow established data governance policies. The CDO needs to have a good working relationship with team members and possess the business maturity to set a data framework that all will use and follow. To continuously champion the data, a good CDO should understand the latest technologies around data analytics and be learning constantly to stay ahead of the curve to ensure a return on BI investments.

A Visionary

An important quality in a CDO is someone who can make meaning out of the data. Your organization will want someone who has a vision for business opportunities over the next 1,2 5, and even 10 years and can use the data in innovative ways in support of driving revenue. A CDO who has a vision for what results, activities and actions are needed to align the data strategy with the FI’s overall business strategies will set the organization up for future success.

Finding the right CDO can make the difference between a financial institution that leads and one that simply is just keeping up or worse – not getting a true ROI from their data investments.

Is your organization in need of a Chief Data Officer? Contact The Knowlton Group to help your organization achieve all your business intelligence and data-driven objectives with our Chief Data Officer expertise. Email us at brewster@knowlton-group.com to learn more!

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The Role of the Chief Data Officer

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For years, financial Institutions have been using data analytics to seek out opportunities, reduce costs, create efficiencies, make better and faster decisions, and ultimately improve the customer experience. Though many have begun the data analytics journey, most are not getting the most value of their data analytics initiatives. To be fair, it’s not the easiest process. You must build the right infrastructure to capture data. Then, you need the ability to access and extract data. Lastly (and most importantly), you have to convert the data into meaningful insight with the goal to create real business opportunities.

Today, with the increased focus on data management, data protection, and analytical competency, many financial institutions are finding gaps in their data program and are discovering they don’t have the right skillset to manage all facets of their analytics initiatives.

Enter the Chief Data Officer.

The CDO has proven to play a significant role in helping many FIs steward their data, drive operational intelligence with data, and generate real business value by monetizing data assets. Historically, IT departments were responsible for most of the big data and analytics projects. But as the push to deliver insights from the data has become a major driving force behind data and analytics projects, the role of the CDO has become crucial. According to Gartner research, by 2019, 90% of large global companies will have an appointed CDO. (1)

Why a CDO?

Not sure if your organization needs a CDO? If considering adding a CDO to your org-chart, it’s important to be able to make the distinction between your existing data analyst, data scientists and CIO. While data scientists typically have backgrounds as mathematicians or statisticians, CDOs should have a background in the financial services industry, know your market and combine that with a technical understanding of data and its potential for reaching growth goals.

Here are six advantages a CDO can bring to your financial institution:

Develop a Data Strategy

Data analytics is a powerful enabler for fraud detection, business intelligence, marketing insights, product research and so much more. With massive volumes of data flowing through the FI every day, it can be difficult to decide what data to keep and analyze. A CDO makes those key decisions as part of an overarching data strategy. They can help with mapping out goals, monitoring progress, and fine tuning the strategy as needed.

Enhance Data Governance

The CDO bears the responsibility of stewarding the data and ensuring data quality. They help implement proper data management and data governance systems and processes to ensure data is trustworthy, reliable, and available for analysis across the financial institution.

Leverage Data

The CDO will help find ways to use existing data to uncover new business opportunities, solve business challenges, and dive deeper into other insights that produce new sources of revenue tied to data.
Oversee Data Protection: Risk management and compliance with customer data are major issues among regulators, and the CDO can assist to ensure compliance and reduce risk. The CDO helps define the information management strategy to meet compliance demands; and shares information with the chief risk officer. If your FI lacks a dedicated compliance team, then a CDO can become a major contributor towards this function.

Manage Data Operations

A CDO makes key decisions around the storage, handling, and use of a FI’s data, including the type of platforms used, connections to/from production applications, analytics processes, and efficient flow of data.

Enhance Data Communications

Ultimately the CDO is a liaison between other departments. The CDO will work closely with the IT department, yet help with strategy in marketing, operations and many other functions throughout the FI. The CDO will collaborate with other departments, while overseeing goal setting.

Not sure if you should hire a Chief Data Officer yet?. Let The Knowlton Group act as your outsourced Chief Data Officer. Your financial institution will receive a trusted advisor and a strategic partner to enable you to leverage the massive amounts of data flowing through your organization. We will work with you to create long-term strategies for growth, top performance, and carve out a competitive advantage. Our mission is to help transform your organization into a data-driven organization. Contact The Knowlton Group today by email at brewster@knowlton-group.com to learn more!

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Sources:

1. Gartner Estimates That 90 Percent of Large Organizations Will Have a Chief Data Officer by 2019, January 2016. Gartner Press Release

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