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Improving feature prioritization and software development through generative AI
A pilot transforms product management prioritization with AI
The IBM Chief Analytics Office (CAO) group is responsible for partnering with business units across IBM to embed AI and advanced analytics into workflows and deliver data-informed insights and machine learning recommendations, driving value for business areas ranging from ecosystem, product management, finance and more. For a global organization with over 250,000 employees, this is no small task.
Across IBM, there are more than 500 product managers supporting software product development. Collectively, they received over 30,000 new ideas and feature requests from users during the past year. To put these requests into action, they are categorized so that common themes can emerge and features can be prioritized. Historically, the feature request form contained an optional “theme” field that allowed users to self-identify a theme for their idea. But most ideas lacked an assigned theme, requiring product managers to manually review and categorize each feature request.
Within IBM, various product teams employed disparate approaches to evaluate new ideas and relied on separate platforms to prioritize them. This led to inconsistencies in selection criteria and data quality. Product managers stored configurations, data outputs and complex file formats in a local directory. Not only was this resource intensive, but it prevented file sharing between collaborators and often created accidental duplicates.
To address these challenges, the CAO team worked with Product Management to pilot a new workflow, a product enhancements prioritization solution. The goal was to use generative AI (gen AI) to evaluate feature requests, identify similarities and categorize the requests accordingly. The six-month pilot included a total of 128 product managers focused on 10 software products.
Yingsi Jian, Chloe Moon, and Christopher Yu used IBM® watsonx.ai™, a next-generation enterprise studio for AI builders, to create the solution. Watsonx.ai reads the idea description and assigns it to a category through prompt engineering.
The model utilizes the RICE (Reach – Impact – Confidence – Effort) scoring methodology to evaluate ideas and automatically assign each request into one or more of the eight predefined categories aligning with International Organization for Standardization (ISO) standards for software development. It calculates an objective prioritization recommendation, mitigating decision paralysis and minimizing potential human bias. Additionally, it logs prioritization in the group’s product roadmap tool, offering separate teams a platform for collaboration and real-time progress tracking, while making it easier for product managers to identify common trends and create visualizations based on these categories.
The results of the pilot showed great promise. It demonstrated that the new solution can help increase a product manager’s productivity by streamlining the data search process, delivering and processing information from data sources. This empowers product managers to make well-informed and data-driven decisions. It also is designed to empower product managers to expedite yes/no decisions, enabling quicker responses to customers and improving the overall customer experience. The solution can also help establish a unified language within and across product teams, fostering better communication. The common language can also allow senior executives to aggregate a holistic view of their portfolio by using the same prioritization framework.
To create products that resonate with clients, product managers need to combine data with their business expertise to decide on roadmap items. The solution helps facilitate the bridge between these two different sources.
Going forward, the IBM CAO group plans to explore additions such as:
- deploying a model to identify and categorize similar ideas upon entry
- deploying the solution in additional software products
- launching the solution scoring methodology beyond new ideas and to roadmap items
- piloting notification alerts to product managers of relevant telemetry data
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Produced in the United States of America, March 2024.
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