Digital Product Management Thinking: Integrating Analytics, Business Model, Coordination and Design Thinking

by Varun Nagaraj

The authors contend that the key to successful digital product management is Digital Product Management Thinking (DPMT) – a collection of systemic practices and skills that integrates Analytics, Business modeling, Coordination, and Design thinking – the ABCD of DPMT.

A common criticism of the cross-functional stage-gate process is that it is too inward looking (i.e. focused on the team’s priorities rather than the customers’ needs) and assumes a relatively static environment.

the lean startup process is built around three pillars. The first pillar is the business model canvas (described in Chapter 2), used as a planning template. The second pillar is the customer development process used for value discovery and validation. A central tenet of this approach is the “getting out of the building” philosophy (talking to external experts and customers), which is critical to gathering information and testing product-market fit. The third pillar is that agile is the development philosophy.

Simulation results support conventional wisdom that shorter sprint lengths reduce the gap between market wants and the delivered performance of released products. This is also known as a “fail fast and review often,” strategy, which enables the development organization to learn and adapt to the market. However, a team cannot continue to arbitrarily reduce the sprint length. After a point, the incorporation of a planning delay or slowing down actually improves matters. Incorporating a planning delay enables learning and sensemaking (Nagaraj et al., 2017) and reduces overreaction to spurious signals. Blindly using agile could result in teams giving up too quickly or over-reacting to negative market feedback that might just be noise. But incorporating analytics thinking and taking the time to separate the signal from the noise makes the agile process more robust.

One of the typical mistakes PMs (especially technically proficient PMs) make when they write a PRD is specifying too many engineering details and venturing too far into the world of functional specifications (e.g., the best location for buttons in the user interface). Doing so impedes the team’s creativity and initiative.

A prototype is often used to establish product or technical viability while an MVP establishes the viability of the product’s value proposition.

Design thinking calls for continuous iteration and experimentation, and analytics thinking requires hard evidence to test and evolve hypotheses. The goal of experimentation within DPMT is to minimize investment in product development until a scalable product configuration can be established through rapid market feedback.

The 4P model (product, price, promotion, and place) provides a practical approach to crafting a GTM plan for a physical or digital product (Kotler & Armstrong, 2015). GTM can also be described in terms of the 4Cs of marketing: consumer wants, cost to satisfy, convenience of buying, and communication. Proponents of the 4C model point out that while its elements are quite similar to the 4P model, the 4C model is more customer-oriented while the 4P model is more company-oriented.

Large organizations are likely to have different individuals responsible for product management (i.e., the PM) and for product marketing (i.e. the product marketing manager or PMM). In such cases, both the PM and the PMM are principal players in the GTM process, with the PM ‘owning’ the product and its pricing, and the PMM in charge of promotions and distribution.

Digital products that embed IoT technologies such as sensors can provide a continuous window into the customer’s actual use of the product. For example, a shoe manufacturer that embeds sensors in shoes may realize that a particular model of running shoes is actually used mostly as a fashion accessory. Armed with that knowledge, the manufacturer might modify the product’s messaging and retarget the shoe toward distribution outlets targeted more at fashion-conscious customers.

One of the first and most persistent questions that a PM is likely to face from investors, executives/management, and team members is, “How big is the market?” Answering this question requires the PM to understand and work through common terms such as ‘total addressable market’ (TAM), ‘serviceable addressable market’ (SAM), ‘service obtainable market’ (SOM), and ‘launch addressable market’ (LAM).