Key Takeaways: A Conversation for Data Practitioners and Product Managers to Collaborate and Drive Business Outcomes

Key Takeaways A Conversation for Data Practitioners and Product Managers

In the following webinar and article we talk about how data professionals and product managers can work together to drive business success. Hear from experts and gain actionable tips you can use at work today.

 

How can data practitioners and product managers work together to meet business objectives? What is the nature of the relationship between data science and product management and how can professionals in both fields successfully and effectively work together?

We spoke with experts Nick Kadochnikov, Head of Data Science at ShipBob, and Peter Bradford, Pragmatic Institute’s Director of Enterprise Transformation to explore the connection between data practitioners and product managers. They talk about how cross-functional team collaboration can help organizations stay ahead of the competition and other pivotal topics, including:

  • The intersection between data science and product management
  • How data can be better integrated into the product development cycle
  • Decision making models based on insights from data practitioners
  • How to create strong partnerships between data practitioners and product managers

You can listen to the conversation in full here, or scroll below for the key takeaways from their conversation.

 

Cross-functional team collaboration between those in data and those in product management is important for organizations to make data-driven decisions. For example, business leaders from different organizations are applying data insights to consumer behavior to create a more tailored approach.

Here are three examples of well-known companies driven by the application of data science:

  • USAA SafePilot is one of the many insurance programs that offer users insurance premium rebates for safe driving, as determined by mobile telematics.
  • Netflix’s recommendation engine filters thousands of titles using recommendation clusters based on user preferences. 80% of Netflix viewer activity is driven by personalized recommendations, contributing to a 93% retention rate. Amazon Prime Video uses similar technologies.
  • Airbnb leverages A/B testing image recognition and natural language processing to determine which photos work best, to test ranking algorithms and understand user’s feelings behind reviews.

Data science can play a critical part in decision making and can be used in service of product management activities to produce more effective strategies.

Additionally, dashboards and effective visualization are required to deliver actionable insights to business users and leaders.

 

Applying Data Science to Product Development

Product managers and data scientists are birds with different feathers, but clearly there’s a lot of value in the collaboration. Data science can influence businesses in many ways, so why isn’t it more often part of the innovation process?

Product leaders continue to use insights to improve designs, delivery and adoption, but there is more they could do. Here are some examples of how product managers can better integrate data science:

  • Develop deeper insights into the user journey
  • Improve the design and identify where users get stuck
  • Drive engagement and adoption, especially when integrated with digital software

 

Leveraging Data Science for Business Decisions

Business leaders normally use data science to reduce risks and wastes with products. Business functions at all levels are using data science in their roles.

Below are a few examples of how different team members can leverage data science.

 

There’s a new path to improve product innovations, however, it requires movement from data practitioners and product managers to function correctly and improve. Therefore, product managers should become data fluent, as well as data scientists should improve their business sense.

In addition, data can be so rich and driven by market needs, it can help business leaders make decisions. Moreover, it can help organizations collect consumer data to get a better understanding of the users’ pain points. Inviting data scientists to the next product meeting will help them understand and capture better insights into what the business is trying to solve.

Resources to Continue Learning 

Data Science for Business Leaders

The world of data is moving fast, do you have the skills to move with it?  This course will show you how to partner with data professionals to uncover business value, make informed decisions and solve problems.

Learn More

 

Business-Driven Data Analysis

Learn how to deliver critical insights that power business strategy. This course teaches a proven and repeatable approach you can leverage across data projects to deliver timely analysis with actionable insights.

Learn More

Author

  • Pragmatic Editorial Team

    The Pragmatic Editorial Team comprises a diverse team of writers, researchers, and subject matter experts. We are trained to share Pragmatic Institute’s insights and useful information to guide product, data, and design professionals on their career development journeys. Pragmatic Institute is the global leader in Product, Data, and Design training and certification programs for working professionals. Since 1993, we’ve issued over 250,000 product management and product marketing certifications to professionals at companies around the globe. For questions or inquiries, please contact [email protected].

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