Can product leaders leverage AI as a sparring partner?

In our fast-paced everyday lives, it can be challenging to find time for all the aspects that theory tells us are crucial to being a successful product leader. We are expected to set direction and effectively communicate it through vision, strategy, and roadmaps. Deep domain knowledge, analyzing market trends, facilitating, coaching, and mastering public speaking are all essential skills. Furthermore, we must represent our customers and users by understanding their needs and desires. Managing and prioritizing the backlog, taking ownership of user stories and working closely with stakeholders and teams add to the demands of our role.

When we read books or attend courses on product leadership, we often feel inspired, motivated, and eager to put what we've learned into practice. However, reality sets in as our calendars fill up, and both our teams and management expect us to be readily available to address pressing matters that constantly arise.

As a result, finding the time to gather our teams and stakeholders for lengthy sessions discussing product vision, strategy, or testing hypotheses becomes a daunting task. But what if there was a way to prepare and initiate this work by brainstorming and collaborating with an artificial intelligence (AI)? Perhaps, with the help of AI, we can streamline our efforts and avoid starting from scratch.

In this article, we'll explore how leveraging AI can empower product leaders and alleviate some of the time constraints and challenges we face. By harnessing the potential of AI, we can optimize our productivity, foster collaboration, and drive innovation within our roles as product leaders. Let's delve into the possibilities and advantages of incorporating AI as a valuable ally in our product management journey.

But what if there was a way to prepare and initiate this work by brainstorming and collaborating with an artificial intelligence (AI)? Perhaps, with the help of AI, we can streamline our efforts and avoid starting from scratch.

This is how we did it

To foster effective collaboration with the AI, we can adopt a funnel mindset approach during our conversation. We begin with a broad perspective and gradually narrow down, providing the AI with the necessary information to achieve optimal results. It's crucial to continuously inspect and adapt throughout the process to tailor the collaborative effort to our specific needs. Additionally, it's important to acknowledge that the co-creation with the AI serves as a suggestion, which we can further develop together with the team. For the team members to be motivated, they must be able to identify themselves in the outcome, as motivation acts as the internal spark that drives individuals to take action, pursue goals, and overcome obstacles in their quest for meaningful achievements.

The context

In this scenario, suppose we are a product leader in our organization, and our team provides support for an ERP system, specifically D365 (Microsoft Dynamics). Our primary stakeholders include finance, product supply, logistics, and a data team responsible for showcasing information through Power BI.

To determine the value we offer to these stakeholders, we have adopted Bain & Co's B2B value pyramid framework. We have identified that our contributions mainly revolve around enhancing the ease of conducting business by leveraging various aspects such as operational efficiency, strategic alignment, increased productivity, seamless access, and strengthened relationships.

Now that we have established a well-defined context, we can proceed with our actual sparring session.

Constructing a Business Model Canvas

In order to utilize AI, specifically Chat GPT, as a sparring partner, our initial step involves constructing a Business Model Canvas. We input our contextual information into the AI, which then generates a suggested business model canvas for our product (figure. 1).

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During this sparring session, we meticulously analyze each aspect and determine its suitability. It is akin to a brainstorming session that involves active participation from our team and stakeholders. For example, we may modify the Key Partners section to include the names and functionalities of specific providers, particularly if we rely on third-party solution providers for certain functionalities. Furthermore, we should assess whether including revenue and cost information is relevant, given that our main focus is on supporting our organization.

By refining and updating the Business Model Canvas, we can harness the assistance of AI to develop a vision that aligns with our goals.
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Vision

An AI generated vision statement based on our business model canvas:

Our vision is to empower our stakeholders in finance, product supply, logistics, and data teams by providing them with a seamless and efficient ERP system, D365.

We strive to be the catalyst for operational excellence, strategic decision-making, and enhanced productivity. By simplifying processes, providing access to real-time information, and fostering strong relationships, we aim to enable our stakeholders to achieve their business objectives and excel in their respective domains.

Together, we envision a future where our stakeholders experience ease of doing business, unlock their full potential, and drive sustainable growth for our organization.

Continuing with the collaborative nature of this process, we must approach it as a co-creation session with the AI. It may require multiple iterations before we truly see ourselves reflected in the envisioned outcome, cultivating the strong emotional connection necessary for effective communication.

Once we reach a point of satisfaction with the outcome, our next step is to craft a strategy.

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Strategy

As mentioned we approach the AI with a mindset of narrowing down, which means that we keep using all our previous work as input after iterating to a level where we feel confident and satisfied with the result. As a result we get the following strategic key elements.

Again we have to see this as a facilitated session where we get input from an AI instead of people. We still have to work with the input and iterate to create something that we can use in our day to day work. After several iterations, we reach a level of confidence and satisfaction with the result.

Roadmap

When constructing roadmaps, AI can serve as an invaluable sparring partner and co-creator, offering insights and support throughout the entire process. Its data analysis capabilities, suggestion generation, and decision-making assistance makes AI a valuable contributor to ideation, discovery, and the exploration of user needs.

In the provided example, the collaboration with AI led to the identification of six distinct phases, each accompanied by specific suggestions for concrete actions:

1. Foundation and Preparation
2. Implementation and Configuration
3. Stakeholder Empowerment and Training
4. Continuous Improvement and Enhancements
5. Proactive Relationship Building
6. Agile Adaptation and Innovation

_{Click to view the text generated by AI (ChatGPT)👇}

Roadmap

Phase 1: Foundation

• Define the project scope and objectives in alignment with the vision and strategy.
• Conduct stakeholder interviews and workshops to gain a deep understanding of their pain points and requirements.
• Establish strong partnerships with Microsoft and implementation consultants.
• Develop a comprehensive training plan for stakeholders to ensure smooth adoption.

Phase 2: Implementation and Configuration

• Customize and configure the D365 ERP system based on the identified stakeholder requirements.
• Collaborate closely with stakeholders to ensure the system aligns with their operational and strategic needs.
• Conduct thorough testing to ensure data integrity and system functionality.
• Develop integration strategies and implement seamless integration with Power BI for data visualization and reporting.

Phase 3: Stakeholder Empowerment and Training

• Deliver comprehensive training sessions tailored to each stakeholder group, focusing on system functionalities and best practices.
• Provide ongoing support through documentation, knowledge bases, and helpdesk services.
• Encourage stakeholders to provide feedback and suggestions for further improvements.
• Monitor adoption rates and identify areas where additional training or support is required.

Phase 4: Continuous Improvement and Enhancements

• Establish a feedback loop with stakeholders to gather insights and identify areas for improvement.
• Prioritize enhancements and new features based on stakeholder needs and strategic objectives.
• Conduct regular system upgrades and updates to ensure compatibility and security.
• Monitor system performance and address any issues promptly to maintain high uptime.

Phase 5: Proactive Relationship Building

• Foster strong relationships with stakeholders through regular communication and engagement.
• Schedule periodic meetings and workshops to understand evolving needs and challenges.
• Provide personalized support and guidance, addressing stakeholder concerns and exploring opportunities for optimization.
• Collaborate on strategic initiatives to leverage the full potential of the D365 system.

Phase 6: Agile Adaptation and Innovation

• Stay abreast of technological advancements, industry trends, and changing business requirements.
• Continuously assess the evolving landscape and identify opportunities for innovation and process improvement.
• Explore emerging technologies and evaluate their potential for enhancing the D365 system.
• Regularly review and update the roadmap to align with new priorities and strategic goals.

By following this roadmap, the organization can gradually implement and optimize the D365 ERP system, empowering stakeholders, delivering value, and ultimately realizing the vision of streamlined business processes, operational excellence, and valuable strategic insights.

To make the roadmap actionable, we can further enhance its effectiveness by setting clear objectives and key results (OKRs). By defining specific and measurable targets, we can track progress and ensure alignment with the organization's strategic goals.
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Objectives and Key Results

Developing and implementing OKRs can pose challenges for individuals and teams. However, leveraging the capabilities of AI can offer assistance in generating OKR suggestions and analyzing data to facilitate the achievement of those objectives. While AI may not directly contribute to the execution phase, it can provide support by offering insights, recommendations, and data analysis. By harnessing the power of AI, we can enhance the OKR development process and utilize data-driven insights to drive progress and success in reaching our objectives.

In our situation, we have identified four objectives, each with three key results. While this may seem overwhelming, we can approach it as a brainstorming exercise. We have the flexibility to select, prioritize, and refine these objectives and key results until we are satisfied that we have a solid foundation for collaborative ideation with our team.

_{Click to view the text generated by AI (ChatGPT)👇}

OKR

Objective:
Enhance Stakeholder Satisfaction and Value Delivery

Key Result 1:
Increase stakeholder satisfaction scores by 15% within the next quarter through improved system usability and performance.

Key Result 2:
Achieve a minimum adoption rate of 80% across finance, product supply, logistics, and data teams within the next six months, indicating successful stakeholder onboarding and engagement.

Key Result 3:
Identify and implement at least three high-impact system enhancements based on stakeholder feedback and needs within the next year, demonstrating a commitment to continuous improvement.

Objective:
Optimize User Experience and Productivity

Key Result 1:
Reduce the average time spent on common tasks within the D365 ERP system by 20% within the next quarter, enhancing user productivity and efficiency.

Key Result 2:
Improve the overall system usability score by 10% within the next six months, based on feedback from user surveys and usability testing.

Key Result 3:
Implement at least two user-requested features or enhancements within the next year, aligning the system more closely with user needs and preferences.

Objective:
Seamless Integration and Data Accessibility

Key Result 1:
Achieve seamless integration between D365 and Power BI for data visualization and reporting within the next three months, enabling stakeholders to access real-time insights and make informed decisions.

Key Result 2:
Increase the percentage of stakeholders who regularly utilize Power BI reports and dashboards by 25% within the next six months, indicating successful integration adoption and data-driven decision-making.

Key Result 3:
Ensure a high data integrity score of 98% or above through regular monitoring and data quality assurance measures within the next year, fostering trust and confidence in the system's data accuracy and reliability.

Objective:
Strong Stakeholder Partnerships and Collaboration

Key Result 1:
Conduct quarterly collaboration workshops with stakeholders from finance, product supply, logistics, and data teams to gather feedback, identify pain points, and generate innovative ideas for system enhancements.

Key Result 2:
Establish monthly communication channels, such as newsletters or knowledge sharing sessions, to keep stakeholders informed about system updates, upcoming training opportunities, and best practices.

Key Result 3:
Implement at least two personalized support initiatives, such as dedicated support resources or tailored training programs, within the next year to strengthen relationships and address specific stakeholder needs.

Objective:
Continuous Improvement and Innovation

Key Result 1:
Conduct quarterly market research and competitive analysis to stay abreast of industry trends, emerging technologies, and customer expectations.

Key Result 2:
Iterate on the product roadmap based on stakeholder feedback, ensuring that at least 80% of the planned enhancements align with identified pain points and strategic objectives.

Key Result 3:
Develop and launch at least one innovative feature or functionality within the next year, showcasing the organization's commitment to pushing the boundaries of technology and delivering cutting-edge solutions.

These Objectives and Key Results are designed to align with our overarching vision, strategy, and roadmap. They serve as tangible and measurable targets that enable us to monitor progress and foster continuous improvement in delivering value to our stakeholders. Regular monitoring and reassessment of the OKRs will help us maintain focus, adaptability, and responsiveness to evolving needs and market dynamics.

Hypotheses and Product Discovery

Before we move forward, it is vital to actively engage the entire team in shaping our vision, strategy, roadmap, and OKRs. Our goal is to ensure that these components resonate with everyone and foster motivation and commitment in working towards our common objectives.

In this particular scenario, we will leverage the AI's assistance to propose an approach to product discovery that aligns with our goals. By involving the AI in this exploration, we can benefit from its suggestions, which may include evidence and effort scores, to guide our decision-making process. This collaborative effort will enable us to gather valuable insights, validate assumptions, and iteratively refine our strategies, ultimately helping us achieve our desired outcomes.

_{Click to view the text generated by AI(ChatGPT)👇}

Hypothesis' and Product Discovery

Hypothesis 1:
By conducting stakeholder interviews and workshops during Phase 1, we will gain a deep understanding of their pain points and requirements.

Success Criteria:
Achieve a satisfaction score of 80% or higher from stakeholders regarding the understanding of their pain points and requirements.

Evidence:
Conduct surveys or feedback sessions with stakeholders after the interviews and workshops to assess their satisfaction and validate that their pain points and requirements have been adequately captured.

Effort Score:
Moderate. This hypothesis requires effort to organize and conduct the stakeholder interviews and workshops, analyze the findings, and ensure alignment with stakeholder needs.

Hypothesis 2:
By customizing and configuring the D365 ERP system based on stakeholder requirements in Phase 2, the system will align with their operational and strategic needs.

Success Criteria:
Obtain a system satisfaction score of 75% or higher from stakeholders after the system customization and configuration.

Evidence:
Conduct surveys or feedback sessions with stakeholders after the implementation and configuration phase to assess their satisfaction with the system's alignment with their operational and strategic needs.

Effort Score:
High. This hypothesis requires significant effort to customize and configure the system according to stakeholder requirements, and close collaboration with stakeholders is crucial.

Hypothesis 3:
By delivering comprehensive training sessions tailored to each stakeholder group in Phase 3, stakeholders will effectively adopt the D365 ERP system.

Success Criteria:
Achieve an adoption rate of 80% or higher, measured by the number of stakeholders actively using the system within one month after the training sessions.

Evidence:
Track user activity and system logins to measure the adoption rate, and conduct surveys or feedback sessions to assess stakeholders' confidence and proficiency in using the system.

Effort Score:
Moderate. This hypothesis requires effort to develop and deliver tailored training sessions, as well as track and monitor the adoption rate of stakeholders.

Hypothesis 4:
By establishing a feedback loop with stakeholders in Phase 4, we will identify areas for improvement and enhance the D365 ERP system.

Success Criteria:
Implement at least 70% of the identified enhancements and new features based on stakeholder feedback and strategic objectives.

Evidence:
Maintain a record of stakeholder feedback and enhancement requests, track the implementation progress, and conduct surveys or feedback sessions to validate stakeholder satisfaction with the implemented improvements.

Effort Score:
High. This hypothesis requires continuous effort to gather and analyze stakeholder feedback, prioritize enhancements, and implement them in subsequent system upgrades.

Hypothesis 5:
By regularly reviewing and updating the roadmap in Phase 5, we will align the project with new priorities and strategic goals.

Success Criteria:
Achieve a roadmap alignment score of 80% or higher, measured by the number of new priorities and strategic goals incorporated into the updated roadmap.

Evidence:
Review the updated roadmap and compare it to the new priorities and strategic goals. Conduct surveys or feedback sessions with key stakeholders to validate the alignment and their satisfaction.

Effort Score:
Moderate. This hypothesis requires regular reviews and updates of the roadmap based on changing priorities and strategic goals, as well as obtaining feedback from stakeholders.

Conclusion - the answer is "yes"

"Can product developers leverage AI as a sparring partner?" asks the headline. The answer is a resounding yes.

Artificial Intelligence (AI) has emerged as a valuable companion for product leaders, offering support in various aspects of their role. By harnessing the power of AI-driven tools and insights, product leaders can enhance their strategic thinking, improve decision-making processes, and and perhaps even gain a competitive advantage in the market.

In today's fast-paced digital era of product leadership, AI becomes a valuable partner, empowering us to achieve impactful outcomes. By embracing the transformative potential of AI and collaborating with it as a sparring partner, product leaders can unlock new frontiers of innovation, success, and customer satisfaction. The synergy between human intellect and machine intelligence paves the way for a future where product leaders thrive and organizations excel.

However, it's important to note that even as we iterate and collaborate with AI, we must work closely with our teams to ignite the necessary motivation to work towards our vision and strategy through roadmaps, OKRs, and product discovery. Together, we can leverage AI's capabilities while ensuring a human-centered approach to achieve our goals.

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