Evolving from Data Project Management to Data Product Management: An Interview with Michael Horn

(USA and Canada) Creating data products, or monetizing data, increasingly is top-of-mind with chief data officers who are striving to create new and innovative data-driven value streams for their organizations. Recently I had the pleasure of discussing the opportunities, challenges and successful methods of creating data products with Michael Horn, Global Head of Data Products with the international advertising agency, TBWA Worldwide:  

Why and how can an organization take a product management approach, not just a project management approach, to data products?

MH: This is critical. In many large organizations, data staff and operations are a cost center and are not accountable for driving value creation or long-term strategic impact. As such, groups are incentivized to be more operationally efficient, but rarely given the opportunity or resources to invest in emerging methods or the runway to develop new internal or externally-facing solutions. 

Applying product management principles and team structures flips the conversation. "What is the most unique and valuable data we own? Where is there demand for it? What new problems could this data solve? How can we realize the value of our data in new ways?" Only then can a roadmap be chartered and funded that can accelerate or even transform a business, with data in the lead.

What works well, and also what doesn’t work particularly well, when it comes to data product management? 

MH: Corporate data cultures don't turn on a dime - it can take 12-24 months (or longer!) to meaningfully shift internal perceptions and empowerment of data functions. There may be significant skill gaps between current-state teams, especially those focused on "defensive" security and compliance functions, and the "offensive" capabilities required to evangelize data access and usage across the enterprise, and beyond. Finally, if incentives are not aligned across participating business units, a nascent data product function can be torn apart by the stress and politics before they can even define the MVP [minimum viable product]. 

What are the nuances that perhaps make data product management different from traditional product management?

MH: It's not uncommon for the buyers of data products to be a new audience - either new roles within existing customers, or new clients entirely. This may mean that product and sales organizations have to start from scratch or discard assumptions about what solutions are the most valuable or how to sell them. I've seen data products "thrown in" as added value, which goes unrecognized, or heard feedback that "our customers don't want this" – ignoring the broader market, or the different set of customers envisioned for the offering. 

Also, existing internal legal and financial functions may not have experience with data licensing terms and regulatory landscapes, and be unwilling to take what they see as privacy or reputational risks. Their support is critical, and they should occupy central stakeholder roles in the data "startup" which they may not play for a stable core business.

What happens if one doesn't take a real product approach to developing and introducing data products?

MH: Oh, so many things can happen! But the first is that organizations need to have the attention span to incubate and develop data products, and if the organization expects net positive ROI in three months, and to fund out of BAU budgets, disappointment is unavoidable. Worst is when early failures result in a "we tried this and it failed" verdict, inhibiting future investment... when the truth is that you didn't even fail big enough to learn. 

What have been some of your data product successes?

MH: I've developed data products in both a venture-funded startup and in global client-service firms, and both offer unique advantages and risks. In a start-up (Resonate) I loved the focus and the teamwork, but it was easy to get too far out ahead of the market, and get caught up in our own language and technology instead of starting from a singular, identified client need. 

Conversely, in a big client-service firm, the focus on quarterly revenue and solving today's problem can inhibit longer-term investments and development of a distinctive, collaborative team culture – it takes strong vision and sponsorship from the CEO on down to take a big leap forward. In either context, my biggest successes have always been in the teams I assembled, and empowered, to embrace transformative thinking and drive empathetic and ethical data practices.