Transforming Product Management: Leveraging AI to Address Common Challenges

Imagine being the captain of a ship, navigating turbulent waters and ever-changing weather conditions. This analogy perfectly describes the daily life of a product manager (PM) in the software development space. From aligning teams to managing shifting timelines and priorities, product managers regularly battle the odds to bring valuable technology to market. It was with these all-too-familiar circumstances in mind that we conducted our latest market research. Our goal was to better understand common challenges facing product management professionals, and to explore how artificial intelligence (AI) is being used to support them along the arduous journey.

Understanding Product Management Challenges: An Outside Perspective

Revelry began by sharing an extensive survey with a wide array of professionals, including product managers, senior product managers, directors of product management, and VPs of Product. Responses across the survey group pointed to a variety of common, recurring challenges, with the top three being:

  • Aligning cross-departmental teams: Nearly 20% of survey respondents find it challenging to sync multiple departments, such as sales, engineering, marketing, and customer service, likening it to herding cats.
  • Ongoing timeline management: Managing deadlines amidst shifting priorities and unexpected roadblocks is a leading concern for at least 12% of survey participants.
  • Initial discovery of project timelines: 10% of survey respondents say accurately estimating project duration is complex and often sets off chain reactions that impact the entire project lifecycle.

Time-Consuming Tasks and Processes Slow Product Dev Across Organizations of All Sizes

Our survey findings also brought to light several specific business tasks and processes that are considered particularly time consuming. These include:

  • Updating sprint boards: Ensuring sprint boards remain up-to-date with all required tasks, their priorities, and statuses.
  • Following up on dev team progress: Tracking development progress, providing feedback, testing, and re-prioritizing tasks on an ongoing basis.
  • Data analysis
  • Writing reports and creating user stories to guide the engineering team.
  • Documenting user requirements: Detailing user requirements, including supporting documents.
  • Meeting coordination: Scheduling and conducting various meetings, including status updates and planning sessions.

Internal Perspectives: Adding Challenges Faced by Revelry PMs to the Mix

To get an even better understanding of the challenges facing software product managers, next, we took our survey questions to our own PM team. Not only do these experts bring experience and perspective from managing product development for a variety of our partners; but many also have contributed to Revelry internal product builds.

Revelry product managers echoed much of what was expressed by our external survey participants, particularly those challenges related to initial discovery and ongoing management of project timelines. Additionally, our PM team highlighted issues such as the tedious nature of grooming backlogs, updating internal presentations, and maintaining project transparency across departments. Writing reports, creating and managing user stories, and taking comprehensive meeting notes were also cited as tasks that can consume between 5-10 hours each week.

“One of the main challenges we face is the coordination of multiple teams, especially in ensuring effective communication with engineering departments. It requires constant status updates and frequent adjustments, adding a layer of complexity to our roles,” said one Revelry product manager.

“Collecting and analyzing user feedback is another ongoing task that demands careful consolidation from various sources,” said a second Revelry product manager. “The process is crucial for making informed, data-driven decisions, but also time consuming and labor intensive.”

Furthermore, our product managers expressed a desire to streamline competitive landscape analysis and manage product changes more efficiently. This underscores the workload split between strategic planning and operational tasks.

AI and Product Management

While still in its infancy, artificial intelligence is (thankfully and wonderfully) already being used to address many of the common challenges facing product managers and, in turn, helping revolutionize product management. To this point, our survey found that many PMs are currently using AI to:

  • Save time and eliminate repetitive tasks: By leveraging AI to automate recurring tasks – like updating sprint boards, writing reports, and managing communication workflows – PMs have more time to focus on higher-value activities, like strategic decision-making and innovation.
  • Enhance data analysis and insights: AI significantly improves the speed and accuracy of data analysis, enabling product managers to make informed decisions quickly. This leads to better outcomes and a more efficient decision-making process.

AI Tools Supporting Product Managers

Our market research revealed that product managers across organizations are leveraging a variety of AI tools to enhance their current workflows. Key tools identified include:

  • ChatGPT: Used for research, brainstorming, writing reports, and generating user stories.
  • TypingMind: A tool that facilitates quicker data entry and management.
  • Claude: Employed for automating and optimizing communication workflows.
  • Bard: Utilized to summarize large texts, helping in faster documentation.
  • Gemini: Known for enhancing data annotation and curation.
  • CoPilot: Assists in code writing and review, enhancing collaboration between product and engineering teams.
  • Shield: Provides security-focused AI functionalities.

At Revelry, our product managers are also employing these AI tools:

  • ProdOps: For optimizing product operations.
  • Figma: To facilitate design work and / or user flows.
  • Typeform: For collecting user feedback.
  • Zapier: For automating repetitive tasks.
  • Airtable and Quip: For project management and collaboration.
  • Cleanshot: For capturing and organizing essential information.

Conclusion

This blog post (and the research that inspired it) merely scratches the surface of the complex, yet exciting intersection of product management and AI. In our next posts, we’ll delve deeper into how AI tools can be seamlessly integrated into various aspects of product management, from initial project discovery to ongoing market analysis. Stay tuned!

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