In fast-paced environments, especially those flooded with customer requests, product managers often find themselves caught in the cycle of continuously triaging customer asks, understanding the scope of requests, and delivering products to satisfy those needs. In this article, we’ll explore why relying on backlog grooming alone isn’t enough, how it can ultimately hinder the growth and impact of your product and even your career and why you need to define product strategy.
There are three key issues with backlog grooming:
1. Over-emphasizing one customer ask
2. Building for a small scope instead of an end-to-end delightful product experience, where you end up creating bugs leading to further customer requests
3. Lack of significant impact: At the end of a quarter or a half-year, a product manager might look back and find that they’ve spent the majority of their time putting out fires rather than making meaningful progress. This can diminish enthusiasm for the product area and lead to frustration.
What else is not a good product strategy:
1. Product planning is sometimes considered as a synonym or equivalent or replacement to product strategy. But, product planning and product strategy are different beasts altogether. Product planning is about timelines, risks, how to mitigate and who will execute, etc., while product strategy is about the why behind those solutions. Many companies overly emphasize on product planning without confidence in reaching goals.
2. Product positioning frameworks: Companies often confuse product strategy with product positioning frameworks. While positioning outlines how to talk about the product, who the target audience is, and how we differentiate ourselves from competitors, product strategy is about the journey to achieve a goal. Positioning is great for educating go-to-market teams; product strategy, however, is about how to drive product development in a way that leads to real customer impact and growth.
After successfully overcoming the above pitfalls, another pitfall that product managers fall into thinking that it doesn’t need to evolve. This is dangerous. Product strategy should be a living, breathing document that adapts based on continuous discovery, experimentation, and learning and not team outings/retreats. A product strategy is never “done”—it must evolve to reflect the realities of user needs, market changes, and organizational goals.
What is a good product strategy?
Defining a good product strategy is working backwards from your goal. A good product strategy not only covers the “why” but also the “what and how”.
Let’s break down the essential building blocks of a great product strategy:
1. Vision: It represents the long-term aspiration for the product. Once it’s defined, it typically doesn’t change, but it serves as the guiding principle for all decisions. A strong vision provides clarity and purpose for everyone.
2. Goal: Measurable time-bound outcome
3. Challenges:
- These are road blockers to achieving your goal and vision.
- Challenges/problem areas must be prioritized and continuously reprioritized based on new insights from product discovery, user feedback, and experimentation.
- It’s not enough to just check off features; the goal is to discover and solve the problems that matter most.
4. Target metrics: Metric to measure the success after resolving your problem area. These can be further broken down logically for each sub-problem area.
5. Actual status: Represents the current state of the product. Problem discovery also happens by clearly defining metrics and identifying the current status.
6. Solution: After gaining clarity on big problem areas, define and brainstorm multiple solutions. Solutions are to be further prioritized for experimentation based on confidence and effort.
The below representation communicates the building blocks visually:
A real-world example of a product strategy in action
Let’s consider the example of a talent acquisition product and how a strong product strategy can transform the business:
1. Vision: Within 3 years, we will achieve the gold standard for autonomous, AI-led talent acquisition. Our product will become the definitive solution, enabling organizations of all sizes, globally, to efficiently discover and hire exceptional talent.
2. Goal: In order to reach this goal, we need to reduce the time to hire from an average of 60 days to 7 working days within next 3 years.
3. Challenges:
1. Challenge 1: Recruiters do a monotonous task of requisition creation
- 1. Current metric: Avg. time to create a requisition/job opening = 30 minutes
- 2. Target metric: Avg. time to create a requisition/job opening = 5 mins
- 3. Solution 1: Provide recommendations of similar requisitions in the platform to copy form [Prioritized due to high confidence, low effort with medium impact]
- 4. Solution 2: Enable requisition creation using voice AI. Voice AI requests for preliminary information to
- 5. Solution 3: Integrate with HRIS system to auto-create requisitions
2. Challenge 2: Recruiters spend 80% of their time on resume screening and screening calls
- 1. Current metric: Avg. time to do the initial screening of a candidate via a call: 25 mins (but automated by AI)
- 2. Target metric: Avg. time to do initial screening of a candidate via a call is 25 minutes
- 3. Solution 1: Automate screening candidates with preliminary questions using voice AI
- 4. Solution 2: Implement a chat-based AI assistant that screens candidates asynchronously. It can ask preliminary questions and evaluate answers through natural language processing, saving recruiters time while maintaining flexibility for candidates.
- 5. Solution 3: Enable AI-powered video interviews where candidates answer predefined questions. AI analyzes speech patterns, facial expressions, and responses to identify suitable candidates for the next stage.
3. Challenge 3: 70% of hiring managers agree that they are not given access and insights to close the candidate quickly
- 1. Current metric: Avg. time to move candidates across stages is 4 weeks
- 2. Target metric: Avg. time to move candidates across stages is 5 days
- 3. Solution 1: Create a centralized hiring dashboard that aggregates data from applicant tracking systems (ATS) and provides real-time insights into candidate progress, bottlenecks, and feedback from interviews.
- 4. Solution 2: Use an AI-powered communication tool to send automated, personalized follow-ups to candidates and hiring managers at each stage.
- 5. Solution 3: Provide hiring managers with a chat interface to query and get real-time status updates on candidate actions, such as application submission, task completion, or interview participation, ensuring better visibility into progress.
Backlog grooming, while essential, isn’t a substitute for building a thoughtful, flexible product strategy. A good product strategy is about understanding the big picture, defining a vision, identifying the most important challenges, and continuously evolving to meet user needs
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