Product management has similar objectives for any kind of software rollout, but some responsibilities are specific to analytics and data products. Here are five ways a great product manager improves the results of data science initiatives.
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While data science requires experimentation and discovery, deploying data science products and programs to end-users requires similar disciplines as bringing a SaaS to market or a business application to departments. When deploying software, product managers have the critical role of delivering business value and improved user experience, and they have extended responsibilities when working on data science initiatives.
I’m a strong proponent of applying scrum in data science initiatives and assigning product managers to oversee the development of data science products, including data visualizations, machine learning models, and genAI capabilities. By assigning product management responsibilities, organizations align data science initiatives to business strategy and are more likely to develop ongoing enhancements to extendable products rather than experimenting and developing one-off analytics and …