Product management is complex. Managing a product throughout its lifecycle, from initial concept to end-of-life, requires different emphases on leadership styles, development methods, and metrics. Choosing the right data and metrics enables leaders to navigate to success. Larger organizations in particular can benefit from adopting such a data-driven approach.
Adaptive Product Management with Bee4IT
In larger organizations with many products, stakeholders and product managers, using a data- driven basis for making decisions removes the emotion and cuts short what might otherwise be long arguments. (Gartner 2020)
However, applying a data-driven approach does not come without challenges. This is primarily due to the changing nature of metrics as products mature. Product managers and product portfolio managers must solve two main interrelated challenges:
1. What kind of metrics do I need to apply to a particular product lifecycle stage?
2. How do I compare products in a portfolio that relies on different types of metrics?
While early-life products need to focus on growth metrics, such as repeated usage, the focus for mature products shifts to customer satisfaction metrics, such as churn rate. Additionally, product management needs real-time data to be able to manage effectively. Read more about the different product lifecycle stages and their requirements in the Gartner article. Contact us if you are interested in seeing product and product portfolio management in action with Bee4IT.
Interest in learning more about Gartner’s Hire and Develop Product Managers Who Fit the 3 Stages of the Product Lifecycle? Gartner subscribers can read the full report here (external link).