The worlds of finance and technology are moving at a rapid pace, and both collide and integrate more by the minute. While internal resources are dwindling, there’s more data available than ever, along with an increasing demand for better reporting, compliance, quicker action, and more reliable decisions.

Trying to do it all yourself while maintaining quality often leads to making bad data decisions, which come with higher risk, wasted budget, and missed growth. Making more strategic decisions can help mitigate these risks and lead to better quality, faster insights, and overall better member outcomes.

Know yourself, your team, and your resources

We all have our own strengths and weaknesses, and one of the better qualities of a leader or a team member is knowing not only their own strengths, but also those of their other team members. Something that might take one person hours could be something you can complete with a little focus, caffeine, and thirty minutes, whereas the reverse is also true, maybe something you are struggling with and toiling at for hours might take others significantly less time and brain power.

It’s important for you to know when it’s most beneficial to do it yourself and learn how to become an expert, utilize your team resources, or make the decision to outsource the problem. That common saying, “Time is money,” is true when it comes to deciding which option has the most value to your team and business. These same factors can become even more apparent when you consider how quickly technology and data evolve.

When leaders know their own strengths and the strengths of their team members, it can be easier to tell which projects are doable and which should be outsourced. Every data request should pass through three filters: First, can you do it well? Second, do you have the time? And finally, how important is the outcome? Some things to consider while building your data strategies include:

Focus on what you know or can do:

• Is this something you already know, or would learning this process improve your day-to-day or goals and growth?
• Do you have the time and space to become an expert in this field and be available to answer and assist with related questions and needs?
• Can you confidently stand behind the results, and are you comfortable speaking to and supporting your outcome?

Next, review what resources you have:

• Is there someone on your team or within your business who is already an expert?
• Would the time investment of training, developing, and/or owning this be beneficial for their growth and position, and your business needs?
• Will the outcome meet required quality standards, and are they confident in owning, speaking to, and supporting the outcome?

Then, finally, what other options are available:

• Does it take less time and resources to outsource?
• Would a quick, high-quality turnaround benefit your project, business, and team, or allow for faster action and resolutions?
• Would a specialist or expert’s outcome meet the standards, quality, and needs, and does this make you feel more secure in their responsibility for the outcome?

It’s important to consider which option is more reliable, which protects the member’s data, which would best meet your needs and standards, which is most cost-effective, which supports the goals and desired outcomes, and which provides the best resources, details, and level of understanding. For credit unions, these decisions aren’t just a cost decision; it’s also a risk and compliance decision. Due diligence, data governance, and security protocols should always factor into the equation. Good leaders choose intentionally, not reactively; balance is crucial.

Consider when undertaking data projects:

• DIY is best for low complexity or high capability, like for stats and reports from the core or KPI tracking.
• Internal is best for medium complexity and growth opportunities, like building dashboards or data governance and cleanup.
• Outsourcing might be best if there is higher complexity, higher risk, or requires urgent or quick turnaround, like with data strategies and predictive modeling, heavy or custom reporting, or complex data migrations.

Explore all your options

As a member of the Data Analytics team at a CUSO, it may seem that I would be biased toward the option that puts me in the position to offer my services and expertise, but part of my expertise also includes knowing when it’s best to recommend those DIY or internal resources.

We are passionate about data and truly want everyone to know how to interpret and understand their data, but we also recognize that learning and understanding take time and resources that some credit unions don’t have. We encourage credit unions to investigate options and resources that come included with most of the technology you have today to help utilize it to its fullest potential.

Invest in training and understanding, ask questions, and if you still can’t get there, reach out for help. The goal isn’t to do everything yourself or even to outsource everything; it’s to make intentional decisions about where your time, your team’s talent, and your resources create the most value.

Before your next data project, ask yourself:

• Do we already know how to do this well?
• Do we have time to do it right?
• Is this a recurring need or a one-time project?
• What’s the risk if we get it wrong?
• Would outside expertise accelerate results?

Those five simple questions should get you well on your way to either doing it yourself, utilizing your team’s talents, or reaching out to a data partner for support.