Maintaining a Successful Harmony of Product Requirements between Client and Data Specialist
In a recent project, a team adopted the Four Principles of Explainable Artificial Intelligence, focusing on the Knowledge Limits principle to operate under known conditions. The project's goal was to develop device health management dashboards that identified high-risk devices requiring attention.
Weekly meetings were held to discuss the project's status, next steps, and demos. These meetings proved crucial in keeping all parties informed and ensuring the project stayed on track. The user interface of the dashboards was designed to be easy to navigate, providing detailed explanations to analysts in their terminology. This enhanced explainability and communication, leading to the client taking on more responsibility for the project's direction.
The client, a company with a strong understanding of data analysis, required a technical team to develop machine learning and analytics for their dashboards. Initially, there was conflict between the two teams due to unmet expectations and perceived unmet goals. However, to resolve this conflict, the client's product manager was empowered to take on more responsibility and make decisions based on their business case and desired outcome.
The co-manager model in project management, which involves equal authority and responsibility for both the client and technical team, was employed in this project. This approach created a level of ownership for both teams and contributed to the roadmap's success.
The accuracy of the dashboard outputs was evaluated through weekly demos and client feedback. The dashboards provided explanations for their output by allowing analysts to click down to the underlying data. This transparency helped the client understand the algorithms' predictions, and their feedback, based on their industry domain knowledge and experiences, allowed for the production of a practical solution that created expected business value.
In such collaborative projects, the client product teams typically include product managers, product owners, and business analysts. Product managers lead the overall product strategy and collaborate cross-functionally to ensure data science outputs align with business goals. Product owners have detailed knowledge of client needs and drive development accordingly, acting as key client-facing roles. Business analysts communicate market and user needs to technical teams, supporting product enhancements based on data insights.
The team's active participation in decisions and changes to requirements was empowered due to the client's understanding of the project. Providing all information empowers clients to aid in their decision-making and ownership of the product they support.
In conclusion, this project demonstrates the value of collaboration between client and technical teams in achieving project success. By adopting the co-manager model, the team was able to create device health management dashboards that met the client's needs and delivered expected business value.
In this project, the client's technical team focused on developing machine learning and analytics for finance, business, and data-and-cloud-computing aspects to enable their business careers. The successful implementation of the device health management dashboards also required a strong understanding of technology, as it involved explaining complex algorithms in terms understandable by analysts. This project demonstrates the importance of collaboration in finance, business, technology, and data-and-cloud-computing sectors, leading to the creation of practical solutions that deliver expected business value.
