Freddie Mac Single-Family

A ravind “Jag” Jagannathan is chief data officer and vice president of business transformation in Single[1]Family’s Strategic Delivery, Data and Operations division. Mr. Jagannathan, also known as “Jag,” is responsible for the overall data strategy, governance, execution, integration, data product ownership and business intelligence for Single-Family. He also manages all shared assets for the company, including modernization.

AnkitGoel is vice president of data transformation and analytics solutions in the Single-Family Strategic Delivery, Data and Operations division. He is responsible for developing the future state Cloud Data Lake strategy and implementing a multiyear transformation effort from the existing data assets. He is also responsible for business intelligence/analytics, business rules, business information architecture, metadata management and business data architecture functions for Single-Family.

As business leaders, we operate in a complex, competitive and ever-evolving world made even more challenging by the current COVID-19 pandemic that has changed how we work.

“A holistic product delivery model for data based on persistent funding is critical to empower business capabilities in an agile world”

For those of us in the housing industry, the last year has been filled with as many opportunities as challenges. We’re experiencing a technology transformation that has improved how we deliver value to our lender clients and housing professionals.

A key part of this positive change is how we’ve revolutionized data. Creating, storing, analyzing, managing, and delivering data is an increasingly valuable cornerstone of almost every business. In fact, of all the products a business relies upon to deliver client value, data has become one of the most prized.

Data as Product

When we think of products, we envision concrete, distinct, and often proprietary items that organizations produce and deliver, increasingly in digital format. Historically though, data has been seen more as a service. Data teams were backend support rather than frontline resources. The process of finding, manipulating, analyzing, and delivering data was also viewed as slow. Not anymore.

 In addition, the role of chief data officer was primarily a defensive one, focused on housing content and building trust around data sources. Given the support role and governance nature of data work, funding has been a struggle for data teams in many organizations.

The primary focus of many businesses has been on the client side since organizations gain revenue directly from clients. This is still true, but now data – and the teams that provide it – play a more central role in providing client value. That’s why we believe the concept of data as product has become such an integral one to businesses. A holistic product delivery model for data based on persistent funding is critical to empower business capabilities in an agile world.

 Data as a Business Driver

Data teams are now integral to what draws clients to organizations. In many ways, we’ve become lead actors in our organization’s show, not just supporting players. Since trends indicate that this will only increase, we should concentrate on how best to provide insights as a powerful tool to truly empower client-facing teams and business decision[1]makers. Whether it’s a loan, security, or infrastructure, data teams are the ones managing the delivery of those business objectives. Who better understand the data, the patterns, and the techniques for analyzing and presenting value than the experts on the data teams?

 While most companies today know there’s a high demand for their data, data leaders need to help our client-facing colleagues understand better and then position these changes as benefits to clients. Here are three to consider. Aravind Jagannathan

Three Important Data Trends

• The digital universe is expanding. Big data technologies are less about volume and more about approaches, tools, and data processing methods that help to extract from tons of ore the gold that companies need to make the best decisions. How we manage content is a key foundational block. This impact shows how data teams harness the data they already have, as well as how they proactively procure the data they need to have the best information to then analyze and disseminate.

• Businesses rely on artificial intelligence, data analysis, and machine learning. For example, in the housing industry, they help professionals quickly assess risk and efficiently maximize opportunities without sacrificing output quality. From faster, more accurate appraisals to sophisticated forecasts, the use of analytics often helps lead to smarter decisions about mortgage risks. Unlike before, these already-popular tools are no longer reserved for high-profile use cases. They can and should become more part of improving operational processes as well as automating parts of the data pipeline.

• With all the technological advancements in the last few years, data products are produced and shared faster than ever. Data teams need to reinvent themselves with vertical integration strategies that enable the production of finished products. In other words, they should aim to offer more polished insights and analytics, not just raw data. Like modern grocery stores that provide raw produce and ingredients as well as ready-to-cook and cooked food for one-stop shopping, data teams can leverage data as a product to create value for clients.

Looking Forward

Going forward, data leaders will need to find smart ways to speed up access to – and customize – data, with no adverse effect on quality. Our ability to take raw data and create valuable insights will make our data teams even more valuable to our organizations.