Mortgage Companies: 3 Steps to Better ROI on Your Data Investment

August 5, 2022

Wrangling data is an essential part of digital transformation for many mortgage companies. But addressing the technology side alone – say, by investing in a data exchange platform but not onboarding or training – will not yield a positive ROI.

To see the consistent, ongoing bottom-line improvements digital transformation promises, employees have to use new tech in ways that improve their daily work. So how can you make that happen? By shaping your data engineering investment to drive adoption from the beginning.

Here are three steps to take during a data engagement to maximize your downstream ROI.

Read more: 5 Ways Data Is Redefining Financial Services

1. Draw a Map of Your Company Today and Your Path Forward

The starting point on the map should include an org chart that indicates which data sources each team member relies on. From there, it should show your data and analytics strategy: which data silos need to come together so everyone can access the data they need.

The map should also indicate how the organization will change with the new capabilities the data project introduces. For example, let’s say you plan to adopt Tableau to create dashboards and Snowflake to run data analysis.

The day you make that decision, you may have a whole team of people whose job it is to run Cognos reports. Without a clear path forward and communicated direction, this group may become resistant to the new way of doing things, as they may perceive it as putting them out of a job. Identifying who in the organization uses what data, downstream reporting impacts, and team skills will help identify training and change management opportunities. 

Mapping new roles and functions is easier when you start with everyone’s goals. LOs want to close loans. Servicers want to process payments and handle calls. Team leads want high performance across team members. And so on. A strategic plan that leads to high adoption typically does two things:

  1. It clearly shows individuals and teams how to be successful in their roles (and, ideally, how the new data infrastructure will let them be more successful).
  2. It provides insight into how they’ll be measured, where those metrics come from, and how they’re turned into pay and bonuses.

This map offers the “what” of getting from where you are today to a data-forward way of operating. Now let’s look at the how.

2. Understand Your Team & Their Data Literacy

In any group, there are varying levels of comfort with data, technology, and change. To shorten your time to value with a data and analytics engagement, identify which group each of your employees falls into:

  • Innovators
  • Early adopters
  • Early majority
  • Late majority
  • Laggards/Resisters

Each of these groups will move through change at a different pace. Helping them progress from building awareness, interest, and then wanting to try it is a challenging problem that we help our customers through regularly.  Customizing your training materials to each group and their rate of change is also critical.Harvard Business Review offers some excellent insight on how to do this well.

In essence, though, convincing employees to use your new data tools is no different than convincing them to use any other new technology or software. The key is to focus first on those who will embrace the new capabilities and run with them, highlight that group’s successes, let them serve as evangelists, and then provide the educational, and onboarding materials that enable the rest of the team to enjoy similar results.

Some of those materials will depend on your team’s level of data literacy. No matter where the team’s data literacy levels are, nearly all data and analytics deployments benefit from a centralized hub that joins people from different parts of your organization.

3. Build a Hub to Join Technical and Non-Technical People

This hub functions like any intranet site in that it will be the go-to destination for building a community around the data and analytics capabilities you introduce.

By making information about the data (data diagrams, data lineage, information about how frequently data updates occur, information about where data comes from and who owns it, explanations of how metrics are calculated, etc.) centrally and publicly available, you greatly reduce the back-and-forth between business users and developers.

If a user has a question not answered by existing documentation, both the question and the answer can be captured in the portal for anyone to access. 

For example, imagine an LO is struggling to understand how to import data they got from an emailed referral. A member of your IT team can hop on a video call to show the LO, record the call, and share the recording in the hub for future reference.

Because it functions as a community, the portal can also help drive excitement about (and ultimately adoption of) new tools and features. Developers can use the portal to showcase what they’re working on, get feedback, and build tools that business users are excited to start using.

Digital Transformation Is Only Half Digital

There is no digital transformation without digital technology. True transformation can’t happen without the non-technical work of organizing people, managing processes, and planning.

That’s both good news and bad; on the one hand, new technology won’t magically transform your organization. But on the other, your institutional knowledge of the people at your organization and the ways you operate today are among the most valuable tools available to drive meaningful change.

For more insight into both the technical and human side of enacting digital transformation at your organization, get in touch.

Author: Christopher Cronk
About: Christopher Cronk is Vice President and Managing Director of Data and Analytics at NTERSOL. He is an award-winning data and analytics executive with approximately 20 years of experience in professional services, management consulting, data, and analytics. Mr. Cronk has worked extensively across multiple industries including Communications, Financial Services, Insurance. Healthcare & Pharmaceuticals, Retail, Media, High Technology, and Automotive and has helped many Fortune 500 companies strategize, implement, quantify, and realize millions in ROI on their technology, data, and analytical investments.