Use of Data Science in Product Management

About the Guest

Murilo Juchem is the head of the production for a series of 0-to-1 new business creation projects in the Cloud, Mobile, Wearables, and 3D Printing & Digital Manufacturing. He is currently leading Product Management and Data Science for 3D Printing as a Service, a subscription model for 3D Printing. He has experience in product design, outcome-based business models, data science, and building product development teams. Also, Murilo holds a bachelor’s and a master’s degree in Computer Science MBA with FGV (Fundação Getulio Vargas), a top business school in Brazil.

Connect with Murilo Juchem

Key Takeaways

• Data is valuable and can inform other parts of an organization.
• Embrace the diversity of format and qualities of data as there is value to leverage from that.
• Data can be messy, but presenting it in a way understandable to those who consume it can help drive results.

Quote

“The potential for data science to enhance the ability to quantify things is enormous…  positioning a product…quantifying the value, model segmentation, creating pricing profitability scenarios… It’s a game-changer.” – Murilo Juchem

Highlights from the Episode

How do you combine using Data Science Models to position the effectiveness of your 3D Print Products today?

Data science can help quantify the effectiveness of a product. It can be used to help model the cost structure, segment the market for a product, and support marketing campaigns.

What challenges do you face when trying to utilize data within your organization? 

The first challenge is obtaining the data from other parts of the organization. Next, using the data to inform other parts of the organization can be difficult because it requires a lot of legwork and often relies on experts from different areas of expertise. Finally, embedding explanatory visuals in presentations can help engage people and make them more likely to listen to data-related explanations.

Can you share a situation where using third-party data to enrich your first-party customer data helped solve an issue that drove a profitable result for the organization?

This happened when NOAA was used to augment the ability to diagnose issues in the production process and, as a result, provide remedies. In this situation, the third-party data was used to augment customer data to solve an issue that resulted in a profitable outcome for the organization.

Is there a book, blog, newsletter, website, or video that you would recommend to our listeners?

• Fundamentals of Machine Learning for Predictive Data Analytics by The MIT Press

Shout-Outs

Sridhar Solur – CEO at Kenmore brands

Bernardo Huberman – Fellow and Vice President of Next-Gen Systems at CableLabs

Bill Geiser – Co-Founder and CEO at Meta Watch LLC