Data Driven: How To Leverage Data To Take Your Company To The Next Level

The following article is a republication from Authority Magazine, where it first appeared on November 6, 2025.

The proper use of data — data about team performance, data about customers, or data about the competition- can be a sort of force multiplier. It has the potential to dramatically help a business scale. But sadly, many businesses have data but don’t know how to properly leverage it. What exactly is useful data? How can you properly utilize data? How
can data help a business grow? To address this, we are talking to business leaders who can share stories from their experience about “How To Effectively Leverage Data To Take Your Company To The Next Level”. As part of this series, we had the pleasure of interviewing Chase MacDonald, Senior Product Manager at InformData.

Chase MacDonald is a Senior Product Manager at InformData, recognized for his strategic problem-solving and commitment to driving positive change through data-driven innovation. He empowers product teams by leveraging his expertise to foster impactful solutions and continuous growth. His professional approach centers on aligning user needs with innovative technology to deliver measurable business value.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I actually started my career with the intention of working in the film industry. I moved from Michigan to Georgia to pursue that, but quickly realized that the long hours left me with little time to recharge or pursue growth outside of work. Around that time, I joined what was then SJV, which eventually became InformData, working on processing criminal records. I had no idea what background screening even was, but I was fascinated by the way every state and jurisdiction handled records differently. That curiosity pulled me deeper into product and technology, and I’ve been with InformData for nearly a decade now, focused on building products that make background screening more efficient, accurate, and adaptable.

It has been said that sometimes our mistakes can be our greatest teachers. Can you share a story about a humorous mistake you made when you were first starting and the lesson you learned from that?

When I first started in processing, I quickly realized just how different each state’s court systems can be. Pennsylvania, for example, converted its systems in the mid-2000s, so older cases were stored in a completely different structure, with critical information stored in docket entries rather than in obvious fields. Georgia, on the other hand, has every county doing things differently, with some not even online. It taught me that context really matters in data, you can’t assume consistency, and that lesson has shaped how I approach product development ever since.

Leadership often entails making difficult decisions or hard choices between two apparently good paths. Can you share a story with us about a hard decision or choice you had to make as a leader?

Early in my product career, I pushed for a significant shift in how we managed client workflows for our National Criminal Database product. Historically, our team handled client filters manually. So if a customer wanted to see or exclude certain types of records, they had to send us a request, and we’d configure it on their behalf. It worked, but it was slow, inefficient, and limited the client’s flexibility. I advocated for us to invest in building software that automated this process and gave clients direct control through self-service tools. Moving away from the “this is how it’s always been done” approach took resources and trust, but it was worth it. Today, clients can configure filters in real time, which saves them time, reduces costs, and gives them greater confidence in the results.

Are you working on any new, exciting projects now? How do you think that might help people?

Yes, right now we’re working on expanding monitoring and risk categorization tools. The goal is to make it easier for organizations to not only catch risks in real time but also customize the types of alerts they care about. For example, if a client doesn’t need to see low-level infractions like “fishing without a license,” we can filter those out while still flagging what truly matters to their business. This saves time, reduces unnecessary noise, and lets HR and compliance teams focus on what’s most relevant.

You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?

1. Adaptability. My background in film taught me you can’t plan for everything. You have to adjust on the fly. That skill has been crucial in product development, where client needs and technology change constantly.
   
   
2. Curiosity. Early in my career, I kept asking “why does this work this way?” and those questions opened doors into IT, engineering, and ultimately product. Curiosity helps you spot opportunities others might overlook.
   
   
3. Empowerment. I believe in giving users and teams the tools to make decisions themselves. Building configurable products rather than dictating processes has been one of the most rewarding shifts in my career.

Thank you. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” For the benefit of our readers, can you help explain what it looks like to use data to make decisions?

To me, it means moving from assumption-based decisions to evidence-based ones. Instead of saying, “this process seems to work,” you look at the data: how long does it actually take, how much does it cost, how often does it return value? At InformData, we’ve used data to identify where workflows were bogging down clients, like unnecessary county searches, and redesigned products to eliminate wasted effort. The result is faster turnaround times and better trust in the results.

Based on your experience. which companies can most benefit from tools that empower data collaboration?

Any company where risk, compliance, or trust is central to their operations. That includes background screening firms (CRAs), but also industries like healthcare, insurance, transportation, hospitality, education, real estate, and so many others. In all of these, collaboration and shared access to normalized, complete data can mean the difference between catching a major risk or letting it slip through.

Can you share some examples of how data analytics and data collaboration can help to improve operations, processes, and customer experiences? We’d love to hear some stories if possible. 

One example is in healthcare: when a doctor joins a hospital, their credentials and history need to be validated not just by the hospital but also by multiple insurers. Rather than each player duplicating work, a data collaboration model can centralize and normalize that information. Another example is in real estate, where safety and trust are critical. Agents often meet prospective buyers or sellers for the first time with limited information — sometimes just a phone number or an address. By leveraging data, agencies can quickly validate whether the individual is who they say they are, confirm property ownership, and flag any potential risks. That kind of upfront insight not only protects the agent but also gives clients greater peace of mind. In both cases, collaboration reduces redundancy, speeds up verification, and builds confidence for all parties involved.

From your vantage point, has the shift toward becoming more data-driven been challenging for some teams or organizations? What are the challenges? How can organizations solve these challenges?

Yes, often the biggest challenge isn’t the technology, it’s the mindset. Some industries, like CRAs, have done things the same way for decades and are hesitant to change. Others worry that automation could replace jobs or uncover risks they’d rather not deal with. The way forward is transparency and education: showing how better data reduces risk, saves money, and empowers people.

Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.

1 . Normalize and Clean Data. Raw data is messy. By normalizing and categorizing, you make it usable across teams and industries and create a basis for flexibility and customization.

Example: DUIs can have many different names or acronyms, such as Driving While Impaired,” “Driving While Intoxicated,” and more. Cleaning up the data for categorization can ensure the end user is able to understand the raw data and what it means to their process and the end user.

2. Empower Users. Give clients the ability to configure filters and workflows themselves. This not only saves time but also increases trust.

Example: Some clients can have several use cases for the data being accessed with their end users. Enabling the ability to not only customize what results return, but also configure multiple profiles with different filter settings to accommodate the end user’s needs giving users the ability to better accommodate multiple workflows

3. Focus on Completeness, Not Just Coverage. More data isn’t always better, better data is key to success.

Example: Not all data sources contain key information needed for informed risk assessment around criminal data. At a minimum, ensure you have a full name on file, a full or partial DOB, charge description, date associated with the case, and a disposition or notation of whether the charge is pending. Having this information is key to being able to properly assess risk, so your sources should be vetted to ensure you can obtain complete data, as the saying goes you want quality over quantity.

4. Adapt Across Use Cases. Data designed for one market can often solve problems in another.

Example: Our monitoring product was built with the CRA market in mind as an additional stream of reliable subscription-based revenue to address gaps in post-hire annual follow-up background checks. We quickly realized how this data can be used to help save on costs in other markets, such as identifying risk trends in driver fleets before those records would potentially appear on an MVR. By having flexibility and clean data, we were able to take the product and easily adapt the offering to fit multiple markets outside of just the background screening market.

5. Use Data to Reduce Risk in Real Time. Continuous monitoring turns data into an active safety tool, catching risks before they turn into legal disasters.

Example: We did a monitoring pilot with a package delivery organization. During that pilot, an employee was arrested in uniform for a felony charge. It was identified that months prior, another charge was found that would’ve disqualified the employee from working for the organization as they require self-disclosure of criminal information. Had they been monitoring the employee, the PR issue of an employee arrested in uniform could’ve been avoided, as the risk associated with that particular individual could’ve been identified months prior, and appropriate action could have been taken to address that risk.

Based on your experience, how do you think the needs for data might evolve and change over the next five years?

I think we’ll see a shift toward real-time, continuous data as the expectation. Point-in-time checks won’t be enough. At the same time, companies will demand more contextual filters, giving them the ability to decide and prioritize what matters most to them. AI will play a larger role in automating normalization and surfacing insights, but it will need to be paired with human oversight to maintain trust.

Thank you for your great insights, we are nearly done. You are a person of significant influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be?

I would inspire a movement around responsible, safe, and trustworthy data. In a world where misinformation spreads quickly and digital connections are everywhere, having reliable ways to verify people and protect communities is essential. If we can make trusted data more accessible, accurate, and responsibly used, we can create safer workplaces, communities, and stronger relationships.

How can our readers further follow your work?

The best place to follow along is through InformData’s website and blog, where we share updates about new products, industry insights, and thought leadership. I also contribute to webinars and panels in the background screening industry, and I’m always open to connecting with peers on LinkedIn.

Thank you so much for sharing these important insights. We wish you continued success and good health!