Companies born in a digital era don't have to think twice about incorporating data into the workstream. But for long-standing enterprises to remain dominant in the market, companies have to transform the way they use advanced technologies, combining physical and digital assets to take on competitors. 

Founded in 1920, Pitney Bowes has had to adapt its business model to remain relevant. A king in the mailing and shipping business, Pitney Bowes transformed its portfolio for global e-commerce. Today, the company serves more than 1 million businesses and 90% of the Fortune 500 companies.

To stay competitive in the changing world of e-commerce, Pitney Bowes is enhancing how it uses data to streamline internal processes and transform the customer experience.

"You have a lot of digital capabilities and at the same time a lot of physical capabilities, like in our traditional mailing and shipping logistics expertise," said Olga Lagunova, chief data and analytics officer and VP of commerce cloud technologies at Pitney Bowes, in an interview with CIO Dive. "So to us, the challenge is how do we take full advantage of this richness of what we can do digitally and bring it very quickly to the areas where we may be more physical today than digital."

For example, Pitney Bowes has a partnership with eBay, connecting the company's sellers in the U.S. to more than 100 countries as part of a global shipping program. The technology, with APIs invoked more than 45 million times a day, can collect and analyze data from millions of orders and shipments, applying machine learning in real time, according to Lagunova.

Pitney Bowes also uses its troves of location intelligence data and provides software solutions on top of it. Companies like Zillow and Twitter use the technology to identify consumer trends and capitalize on emerging markets.

Data for one, data for all

A big push for Lagunova is data democratization at Pitney Bowes to enable employees to gather insight from data in the time and form they need. As part of the company's modernization efforts, Pitney Bowes wants to better use data to understand and serve clients. But to do that, every department needs to be able to tap into and employ data.

Data appears across all parts of the product pipeline. As Pitney Bowes develops products, it has to be able to measure how customers use the products and the overall client experience — what they like and don't like.

But to make changes in response to customer reception, departments across lines of business need access to the data, according to Lagunova.

• Digital marketing segments use data to make sure Pitney Bowes targets the right customers with the right messaging.
• Sales uses data to drive leads and better tailor customer conversations.
• Client care uses data to understand customer experience in real time to determine if they are problems. The group can also feed information to service employees working onsite to help customers.

Each of those teams needs a piece of the customer data formatted to best fit department needs, an example of data democratization.

There are many different ways to consume data, which is one of the ultimate parts of data democratization, said Lagunova. Part of it is making "sure that it's not only something that only a few people in the company can understand and do, but make these advanced capabilities available in the form appropriate to a particular user so as a company we can get smarter everywhere."

Changing the business through data

For many organizations, data use started in siloed departments, relying on a handful of experts who knew how to employ analytics tools. But with the shift toward cloud storage and increasingly user-friendly data tools, more corporate groups are making analytics-powered decisions.

At its core, Pitney Bowes' digital transformation wants to accomplish three things:

• Improve customer experience
• Create new business and growth opportunities
• Improve operational efficiencies

While data is not the only way to accomplish business goals, it can certainly help facilitate execution.

"I think data is a great tool, it's a facilitator, or maybe even a common language that helps to break silos, even functional silos," said Lagunova. "It elevates the business discussions from what is true, what's happening to why and what to do about it."

While data-based decision making seems logical, it requires a cultural shift that needs buy-in from all levels of employees in companies.

Transitioning into "a company that is data driven requires a culture that values data-driven decisions, fosters curiosity and experimentation and data-based learning," said Lagunova.

It's not just a matter of looking at the data, but understanding what it's telling organizations and knowing how to respond, an opportunity that Lagunova said ultimately better serves the client.