Introduction

Throughout this series of blog post, we're looking at the work of product management spread across four different areas.

So in the last two section, we looked at Product Market Intelligence and Product Strategy,. In our discussion of market intelligence, we delved into the significance of gathering and analyzing relevant data about the market, customers, and competitors. And under Product Strategy strategy, we emphasized the importance of setting a clear vision and specific objectives.

In this blog, we will focus on the new product development process, particularly prioritization and roadmapping. In this critical phase, product managers are faced with the challenge of choosing what to build and what to leave aside.
We're going to talk about four prioritization techniques that goes from kind of the long term, big picture all the way down to the near term and the fine details.

Product Roadmapping

Roadmaps are time-based charts used to plan a product or service's evolution. They visually communicate plans to development and executive teams, helping prioritize technology investments and trade-offs. However, detailed roadmaps can hinder creativity and focus solely on output. Three styles of roadmaps include simple product area mapping, technology-platform-market approach, and a timeline-based listing. Choosing a suitable approach and updating the roadmap quarterly aids in effective communication and prioritization. Various tools like PowerPoint, ProductPlan, Roadmunk, ProdPad, and Jira support roadmap creation.

Let's apply Roadmapping to FluxyAI

OKRs (Objectives and Key Results)

OKRs (Objectives and Key Results) are a powerful tool used by successful product management companies like Google, LinkedIn, and Netflix. They convert long-term product vision and roadmaps into quarterly goals. Objectives represent business goals, while Key Results are measurable outcomes.

Let's apply OKRs to FluxyAI

Product Development Buckets

Development buckets are a prioritization tool to focus development efforts on impactful items. Four steps include determining categories, allocating future time, organizing the backlog, and guiding development efforts. The goal is to devote more time to big impact items, aligning with strategy and objectives. By using percentages, like 60% for big impact items, teams ensure balanced focus. Tools like Jira aid in tracking progress and adjusting allocations in sprints. Development buckets ensure critical product enhancements are not neglected amidst other demands.
Remember, development bucket is basically allocating time to develop a product.

Let's apply development bucket to FluxyAI.

Discovery and delivery

Product management involves various areas like market intelligence, strategy, new product development, prioritization, and road mapping. The next focus is on discovery and delivery, a critical process in new product development.

Discovery and delivery is a process for new product development, emphasizing innovation based on customer understanding. It involves a series of steps to validate and optimize ideas, prototypes, and product releases.

Steps in the Discovery and Delivery Process

1. Ideas

   Gather ideas from customer interactions, sales teams, executives, competitors, and innovation sessions. Collaboration among diverse team members leads to innovative ideas.

2. Discovery

   Experiment, prototype, and test ideas to determine what works in the market. Quickly and inexpensively vet ideas with customers to find product-market fit. Validation includes customer value, usability, feasibility, and stakeholder support.

3. Delivery

   Incrementally release new capabilities to customers, prioritizing smaller and sooner releases. Faster value delivery, earlier market feedback, and quicker course correction are the benefits.

4. Optimization

   Continuously optimize the product based on market feedback and product analytics. Utilize A/B tests and experimentation to refine the product and maintain market competitiveness.

The Discovery and Delivery Team

The discovery and delivery process is led by a three-person team, including an engineering lead, a UX lead, and a product manager. Collaboration and diverse perspectives within the team are essential for successful product development.

Non-Linear and Iterative Process

The discovery and delivery process is non-linear and iterative, not following a strict step-by-step approach. Ideas spark new ideas, and progress is made through continuous learning and evolution.

Let's apply Discovery and Delivery to our Usecase (FluxyAI)

The Opportunity: you have noticed that lots of users are using Fluxy via mobile phone because a lot of people who are coming FluxyAI's website are from lower income group of the society.
The Challenge: What are you next steps? Should you talk to design engineer and design a mobile app right away?

Specific step by steps

• One the first iteration, just get the word out on social media and see the customer reaction
• If customer response is good, design a prototype and roll out to selected group of users.
• If customer response is good, test the design and functionality and roll out to bigger group with more features.

Stage gate vs Discovery & Delivery

The stage-gates process is prevalent in many companies for new product development. It involves phases and checkpoints where projects are reviewed and decisions made. In contrast, the discovery and delivery process is agile and rapid, suitable for software development. The choice between them depends on the cost of correcting mistakes. While not all teams can switch completely, incorporating some discovery and delivery practices can benefit any product manager. Key aspects include direct customer interactions, product concept testing, and incremental releases.

And finally, it's time to optimize your product in an iterative manner. Product analytics and experimentation are powerful ways to optimize products. Analyzing data on customer engagement, usage, and paths helps understand product value. Product managers can utilize tools like Mixpanel and focus on core value moments. Pairing quantitative data with qualitative customer interviews leads to valuable insights.