By taking a fresh look at the makeup of their analytics organizations, enterprises can innovate their business models and take advantage of digital disruption.
In today's analytics world, business as usual is no longer good enough.
That was one of the lessons learned at Fannie Mae as it underwent a digital transformation three years ago, when company officials started rethinking their analytics processes.
"When we think about digital transformation, that requires a huge amount of technology. And looking at our history, we do not have a stellar track record with that kind of thing," said Scott Richardson, the mortgage financing company's chief data officer.
In a presentation at the Gartner Data & Analytics Summit 2018 in Grapevine, Texas, Richardson said that Fannie Mae had historically viewed data as simply a byproduct of business processes. But he wanted data to be viewed as more of an asset.
Fannie Mae had teams of analysts spread throughout the organization working in line-of-business functions, but Richardson wanted a more centralized approach. He wanted to modernize the Washington, D.C.-based company's data governance policy, update its data infrastructure, find new ways to deploy advanced analytics techniques and generally promote a data-driven culture.
To do this, he started by identifying data enthusiasts within lines of business. He named these individuals chief data stewards for those business groups, giving them the responsibility to make sure data governance policies were being followed.
On the technology side, his team stood up an enterprise data warehouse -- the first time Fannie Mae had built one. It collects and standardizes data from point systems across the company.
But perhaps the biggest change to the company's analytics processes was setting up a centralized data group. Teams throughout the company had their own analytics roles, and Richardson said he didn't want to interfere with the good things they were doing. But he did want to make sure they weren't doing things in silos or duplicating the efforts of other teams.
The centralized data group is primarily responsible for curating data. Data sourcing was previously handled by IT. The team is also tasked with promoting a data culture and evaluating opportunities for self-service analytics.
"We thought we could do interesting things with data," Richardson said. "If you want to be successful, you have to nail that digital experience."
New analytics processes unleash business changes
Modernizing the analytics process isn't just about improving analytics performance. It can also fundamentally change the way your company does business.
"Technology is not just about doing things better; it's also about being able to do things we weren't able to do previously," said Ashish Bayas, CTO at commercial vehicle manufacturer Navistar Inc.
Technology is not just about doing things better; it's also about being able to do things we weren't able to do previously.
Ashish BayasCTO, Navistar
Navistar recently launched a connected vehicle offering called OnCommand. This service takes telemetry data from vehicle sensors and aggregates it in a customer dashboard. Users in trucking and transportation back offices can see information related to driver safety and vehicle health, enabling preventative maintenance.
Bayas said this approach to data and analytics is helping the 116-year-old company remain relevant in the digital age.
"We are a Midwestern industrial company," Bayas said. "Now we're talking about rapid prototyping and apps. This is the disruption and change we're talking about."
Think like a startup
Taking the new thinking about analytics processes a step further, Gartner analyst Jim Hare said analytics teams should approach their work like a startup.
Hare, who also spoke at the conference, said that analytics capabilities like machine learning and AI are driving the business models behind some of today's most successful new companies, like Uber and Airbnb. Analytics teams in other organizations should take a page from their playbooks and look for ways to innovate, he recommended.
The way to start is to look for problems that can be fundamentally changed through analytics processes. Analytics teams are often told to look for quick wins to prove their value, but Hare said the real value is in finding brand new approaches to big problems.
This will involve a higher degree of risk taking than some analytics teams might be used to, Hare said. Taking on bigger projects means a higher percentage of initiatives will fail. But that's the only way to find the truly transformative new ideas.
"You need to get out of your shell a little bit," Hare said. "Think about the impact you're having to your business and how you can help your company transform. You have to think about that next wave of disruption because either you're going to be doing it or some company you've never heard of will."
