Overview

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What is Product Management?

technical, marketing, design, biz, project

role within organizations

Essential Toolkit

causality analysis

decomposition

pattern recognition

generalization or abstraction

hypothesis and algorithm design

testing

Foundation

product + market fit

market analysis

product modeling

feasibility

prioritization

Process

strategic

tactical

Document Map

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What is Product Management?

Product management is variable between organizations and individuals, but typically exists at the intersection of:

technology

design

marketing

business

project management

Product's Role in the Organization

Big Co: own features or products and be more narrow in vision, relying on the larger organization for support.

Startup: serve as designer, customer advocate, mini-ceo, marketer, and team coordinator.

At the end of the day, the product manager's biggest role: critical thought and execution

Essential Toolkit

There are a number of conceptual tools that an effective product manager should strive to master, explored below.

Causality Analysis

Identifying cause and effect within systems, is critical.

Many interactions are misunderstood by casual observers, who often confuse correlation with causation.

By looking at data, the intentions of individuals, and the histories of systems over time, causation can become much clearer.

Decomposition

Decomposition is the process of breaking a larger structure into its constituent elements.

Decomposition allows you to reduce conceptual complexity while maintaining a clear view of all the elements of your product.

Pairing decomposition with causality analysis can provide a clear view of what the most salient elements are within a system, helping to focus efforts and simplify designs.

Generalization or Abstraction

Generalizing or abstracting types of entities and interactions allows for faster (if less precise) thought about concepts, and the application of experience across a broader set of instances.

Since time is often of the essence, this technique is quite valuable to the product manager looking for quick insight or understanding.

Pattern Recognition

As a product manager encounters, identifies, and solves problems over time, they will start to recognize patterns. Paying attention to these patterns (and applying abstraction) will allow a product manager to build a toolkit or pallet of concepts to reach for when trying to understand new challenges.

Hypothesis and Algorithm Design

Once you have identified the elements, types, patterns, and essential interactions within a system, you can begin to build up hypotheses or algorithms that describe the situation more formally. This construct is critical to modeling the system, as it helps you to think very clearly about where you will be creating change and delivering value.

Testing

Now that you have a model that represents your product's or system's interactions, you can start to test.

Pay attention to your model, so that you are testing the right elements, and noting their effect properly on the rest of the variables. Also use the model to target the variables most likely to yield meaningful change.

With all testing, aim for statistical significance in your sample sets. When this isn't reasonable, always spend extra time thinking about how your sample may bias your results, and limit your certainty accordingly.

Foundation

Now that we have a basic and general toolkit, we will cover some of the foundational elements of product management.

Product + Market Fit

There's a ton of hype about product/market fit, but the basic principle is this:

Are the needs and dynamics of your market clearly served by the value of your product in a compelling and sustainable way?

For a deeper look into this, go read Four Steps to the Epiphany by Steve Blank... just don't drink too much kool aid.

Market Analysis

What are a market's needs and dynamics? It is incumbent on the product manager to be able to speak to:

Demographics: What are the primary segments involved in the market? What other factors might be influencing them?

Graph Analysis: What combinations of types of entities are required for the one successful minimal experience in the product?

Intentions: What are the intentions (acknowledged or otherwise) of each of these types of entities? How are these intentions currently being met?

Product Modeling v1

When modeling a product, it should be possible to factor out the following to provide a more complete picture of the system:

participants, context, discovery, engagement, value exchange, acquisition, life cycle

Note: these points are biased slightly toward the product types the Labs approaches.

Participants

The representative members of the product ecosystem, whether they are explicitly users or not. There are multiple interesting elements to consider in regards to participants:

Context

The situation, need, or opportunity that characterizes the domain of the search. For instance, 'dating', 'event partner(s)', and 'roommates' would be be the 'seeking context' of a product, while 'online only' or 'offline interaction' could be 'engagement contexts' of the same products.

Discovery

The mechanism by which participants discover each other, and the tools with which they attempt to navigate the space of people (and make decisions about those people). This includes search and discovery mechanisms, recommendation systems, facets, filters, and the primary data on each individual that is used to guide the process.

Engagement

The modes in which people interact with one another. These can include email, in-app messaging, instant messaging, media sharing, event scheduling, and other styles of engagement (and permutations thereof).

Value Exchange

The ways in which parties involved in the product - users, businesses (us), advertisers, etc - realize value. Users might realize value through the satisfaction of meeting others, or in receiving feedback on their posts. The Labs might accrue value through aggregate data, market reach, and direct monetization. This modeling should always look at sources, sinks, and their relationships and impacts on experience and sustainability.

Acquisition

The manner in which new users will be brought into the product ecosystem at various phases of the product life-cycle. This should account for distribution channels, the relative importance of paid acquisition, the use of viral acquisition loops, and the estimated thresholds for location or user-class network effects that must be hit along the way.

Lifecycle

The set of typical trajectories that users in the product will likely progress through over time, with transition points, influences, and calculation of life time value for each user type.

Product Modeling v2

For a more succinct way to describe a product's model, Brian will often rely on just the following:

ACQUISITION

ENGAGEMENT

MONETIZATION

Feasibility

Now that you have your product modeled, you can start assessing the feasibility of the possible solutions. In doing so, be sure to consider at least the following:

Technical, Experience, and Cost Feasibility

In order to make these assessments, the product manager should be at least conversant in the domains in question.

Prioritization

Prioritization is an art, and the rank of various elements in a queue will often be the subject of much debate. It helps to have objective methods to inform this ranking, like using a combination of the factors below.

Value: the value proposition of the feature, to both the users and the company.

Impact: who is impacted by the feature, under what circumstances

Risk: the set of risks associated with a feature, including unknowns, competitive forces, and technical complexity

Cost: a rough estimate of time, resources, and opportunity cost

Process

Here at the Labs, we follow an accelerated iterative process to help us meet our operational mandate and to quickly evaluate product and market opportunities.

Strategic Process

On a high-level, we should always think about the portfolio of products within the Labs and the nature of trends in the market, and utilize our rapid evaluation loops to quickly test possible entrants into the space.

A key to making this work is to focus on the needs or problems, rather than the solutions, as the solutions might vary wildly as we learn.

Tactical Process

The devil, as always, is in the details.

Tempo

Nothing will help you more, tactically, than understanding tempo - how to set it, how to change it, and what tempo works in what circumstance. Research, prototyping, testing, maintenance, and other modes all have their own tempo, and these will be modulated by team composition and market type. Figure out the rhythms available to you.

No matter what tempo you're on, though, always keep moving forward.

Automation

Automate everything reasonable. Time is valuable, but we work in iterations. Tasks will come around again and again, and the less time we waste over iterations, the better. Automation can also be employed to enforce habits or standards, or to accelerate releases.

At the very least, consider automating tracking (pivotal, git hooks, etc), testing (CI server), and deployment (CD server).

Market Engagement

When was the last time you spoke to a user (or a potential user)? What? Really? Get out there and fucking talk to your users.

Ok, now go do it again.

Internal Engagement

Congratulations! You're leading a team, and working alongside other teams in the Labs!

Now you're trying to coax a bunch of bright, driven, and headstrong individuals forward as a team. Good luck!

Whatever you do now, don't micro-manage. That doesn't work with the types of people who work at the Labs.

Leading your Team

Everyone will have their own nature and style, but keep these recommendations in mind while you lead:

Provide clear narrative - if everyone understands the story of the product, they can make smart decisions without direction

Lead through action - people respect product managers who actually produce as well as manage

Empower the team - give people the latitude to make the decisions they think will best serve the product

Hold all accountable - measuring people (even one's self) by what they said they would do will help all to improve

Lead through opening - ask questions to lead people to insights and answers, as it can be more effective than simple telling