A Product Management Approach to Data Monetization

Part I of III

Central to treating data as an asset, data monetization should align with familiar research and development (R&D) and product management/marketing approaches. Not to oversimplify the many challenges and activities involved in monetizing data, certain basic concepts will reap significant rewards if executed well. 

Evolve from Data Project Management to Data Product Management

Although you may already have a data leader, such as a chief data officer (CDO) or an analytics leader, the first step toward data monetization is to designate a team tasked with identifying and pursuing opportunities for and generating demonstrable economic benefits from data assets. They may report to a data and analytics executive, into the enterprise architecture group, a chief digital officer, or perhaps even a business unit head.

Creating a distinct, dedicated data product management role is vital, especially when business and data leaders agree on pursuing direct data monetization by generating revenue or other financial benefits from licensing or exchanging their data. Typically, companies already have a defined approach for managing and marketing products. Analogously, if you are considering licensing data in any form, you need someone whose job is to define and develop the market for the data asset and to productize it.

Finding qualified talent for this role can be difficult. Traditional product managers may have an advantage over other candidates, even without significant knowledge of data and analytics. But why not consider hiring individuals with experience as a data broker such as Experian, Equifax, Dun & Bradstreet, IRI, LexisNexis, Nielsen or J.D. Power? 

Ideally, the data product manager reports to the CDO (itself an emerging role for data-savvy organizations) or into a new data product line of business head. This chain of command, askew to the IT organization, underscores that data is a business asset, not an IT asset. A data product manager provides a counterweight to data scientists, who can get seduced and obsessed by intriguing problems that may be tangential to the business objectives.

Speaking of CDOs, Gartner’s most recent Chief Data Officer Survey finds that a CDO’s success is 3.5 times more likely when they have met data monetization objectives, versus only 1.7 times more likely when they have demonstrated return on investment (ROI) from data and analytics investments, and 2.3 times more likely when they have successfully reduced time to market. All the more reason to hire a dedicated data product manager. 

The CDO’s success aside, how do organizations as a whole benefit from being more data-driven, or even by getting into the data product space--that is licensing data or data derivatives? In “Infonomics,” I recounted how organizations demonstrating certain data-savvy behaviors have a 2x market-to-book value premium over the market average, and those using data or digital products and services as a primary offering have a 3x market-to-book value advantage. Accountants may not value data, but investors sure do!

Borrow from the Traditional Product Management Playbook

The data product manager can and should borrow liberally from existing product management disciplines:

• Conceiving and planning new ways to monetize data,

• Identifying or developing information markets among partners and others, and

• Coordinating with IT, marketing, finance, legal, and other product management groups to execute information productization objectives.

Paul Vallée, the former CEO and current board member of Canada-based Pythian, said company executives spoke about their experience in taking more of a product management approach. They determined a committee approach was not getting things done and that the company required a single owner to drive the process: “We needed somebody who understood exactly how the business works. We needed someone who had been with the business a long time and had been involved in establishing our practices. That was what we needed to do in order to break through that inertia and to get rid of the committee for day-to-day decisions. Although a group of stakeholders should always be consulted throughout the project, at the end of the day, one person needs to be a leader.”

Similarly, Samir Desai, Chief Digital and Technology Officer at Abercrombie & Fitch, said the key is getting the right individual into the role: “Not everybody is cut out to be an innovator. I think you need to choose someone who understands the business and the technology, and who has the right kind of personality fit to play that role.”

You May Already Be a Data Product Manager

Many data and analytics professionals believe they have been doing data product management for years without being officially anointed. “The title may or may not matter, depending upon the organization,” offered Steve Prokopiou, Data Product and Proposition Lead at First Central. “It’s about engaging with the business and delivering what they’re looking for by acting as a translator, asking sensible, structured questions about data usage and benefit. And perhaps adopting the language of product management in doing so.” Prokopiou also suggested that having the formal moniker might give one a mandate to get involved earlier during requirements’ specification, rather than waiting for incomplete or difficult to translate requirements to land on their desk. 

“A data product manager does need to be entrepreneurial but doesn’t necessarily have to have a product management background,” said Lillian Pierson, who calls herself a data product manager within her own firm, Data Mania, a creator of educational content. She believes that treating almost everything you produce as an actual product compels you to take a more disciplined approach. Pierson advised that a data product manager should have a multi-disciplinary skillset, including: 

• An understanding of analytics or data science and data strategy 

• Knowledge of how systems and processes operate

• Able to anticipate what technologies work well together 

• Knowing how to design features and functions

• Experience with performing market or stakeholder research 

• And a penchant for people. 

Every organization today should be formally looking to squeeze more value from their data assets. But they should not treat data monetization as a science experiment or a one-time exercise, but rather as a true product management discipline. Your business most certainly has an existing approach to core product or service conception, design, development and introduction. Adopt and adapt it for productizing your data. 

About the Author

Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe where he consults with business, data, and analytics leaders on conceiving and implementing new data-driven value streams. He originated the field of infonomics and authored the best-selling book, “Infonomics” and the recent follow-up, “Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets.” Laney is a three-time Gartner annual thought leadership award recipient, a World Economic Forum advisor, a Forbes contributing author, and co-chairs the annual MIT Chief Data Officer Symposium. He also is a visiting professor at the University of Illinois and Carnegie Mellon business schools, and sits on various high-tech company advisory boards.