What Data Leaders Can LearnFrom Great Product Managers
Ultimate guide on treating data as a product
More and more organizations are recognizing the value of treating data as a product. This paradigm shift has brought up a new, specialized role:
The Data Product Manager.
In this article, we will explore what a Data Product Manager is, what data product management entails, and why these concepts are crucial for modern businesses. Read all the way to the end to download your free copy of our comprehensive Data Product Manager’s Checklist.
“You’ve got to start with the customer experience and work back toward the technology—not the other way around.”
Steve Jobs
What can you, as a data leader or data analyst, learn from people like Steve Jobs?
Product management and product design.
The key to successful data management lies in applying the best product management practices to your data. Think of your data as of an iPhone: Who are your users? What problems do they have? How can you help them solve this problem (with data)? And how do you design your data to make it easy to use for them? Basically, that’s what “data as a product” is all about: Applying product thinking to the way you’re handling data within your organization.
While companies are jumping on the data product hype, there’s a common misconception it’s solely about treating data as products themselves. However, the true essence of a successful Data Product Manager (DPM) lies in applying the principles and skills of exceptional product management to data-driven products and services.
Let’s dig into the details.
Learning from great Product Managers:insights for Data Leaders
Data leaders are leaving a lot of untapped potential of their data behind: They can gain valuable insights from the practices of successful product leaders. The role of a Data Product Manager should not be misconceived as merely handling data and packaging it. Instead, it involves applying the skills and principles of great product management to data products. This means designing data products that are not only functional but also desirable and user-friendly.
What is a Data Product Manager?
A Data Product Manager oversees the development and management of data products, such as data sets, analytics platforms, data APIs, or machine learning models that deliver value to users.
Just as traditional product managers are responsible for designing and delivering products that meet user needs and drive business value, Data Product Managers play a similar role in the context of data-driven value generation.
They must ensure data products* are well-designed, intuitive, and aligned with the needs of both internal and external users.
*Data products are integrated, self-contained sets of data. They are trusted, maintained, and reusable resources that are tied directly to specific business cases and, ideally, goal and value definitions. Data products enable organizations to separate meaningful signals from the noise and improve strategic decision-making.
Key responsibilities of a Data Product Manager
Defining the vision and strategy:
Data Product Managers set the vision for data products, aligning them with business objectives and customer needs
Cross-functional collaboration:
They work closely with data scientists, engineers, analysts, and business stakeholders to develop data products that have both technical and business context
Data governance and quality:
Ensuring data accuracy, consistency, and security is a critical part of their role
User experience:
They focus on the usability and accessibility of data products, ensuring end-users can derive actionable insights with ease, for example by providing data product through a Data Product Marketplace
Performance tracking:
Monitoring the performance and impact of data products to drive continuous improvement
What is Data Product Management?
Data Product Management involves the end-to-end lifecycle management of data products, from ideation and development to deployment and maintenance. This approach treats data as products that need to be carefully curated, developed, and managed to deliver value.
Core aspects of Data Product Management:
Product development lifecycle:
This includes stages such as ideation, development, testing, deployment, and iteration
Stakeholder management:
Engaging with stakeholders to understand their needs and ensure the data product meets their expectations
Data strategy and governance:
Developing strategies for data collection, storage, processing, and governance
Market and user research:
Understanding market trends and user needs to inform data product development
Performance metrics:
Defining and tracking metrics to measure the success of data products
Portfolio management:
Managing the data product portfolio and pricing
Applying product management skills to Data Product Management
One key challenge in data-driven organizations is the disconnect between IT teams responsible for managing data and the business users who rely on data for decision-making. By adopting a product mindset, data product managers can bridge this gap by designing data products that cater to the specific needs, expectations, and use cases of business users.
Great product leaders understand successful products are not just functional but also easy (and even fun!) to use. They prioritize user experience, intuitive design, and seamless integration into users’ workflows. Similarly, Data Product Managers should aim to create data products that are as engaging and user-friendly as the best consumer products on the market.
Take the example of the iPhone – its success lies not only in its powerful hardware and software but also in its exceptional user experience. From its sleek design to its intuitive interface, the iPhone has set a benchmark for how products should be designed with the user in mind.
Well-designed data products should not only provide access to data but also offer intuitive interfaces, powerful analytics capabilities, and seamless integration with existing tools and processes. This empowers business users to leverage data effectively, fostering a data-driven culture and enabling better decision-making across the organization.
For data products to be truly effective, they must be designed as exceptional products users find indispensable. This means DPM should always consider:
Customer-centric design:
Like great products, great data products are designed with the user in mind. They should be intuitive, easy to use, and designed to meet the specific needs of their users.
User engagement:
Successful data products are those that users WANT to use, not just have to use. This requires a deep understanding of user needs and continuous engagement to refine and improve the product.
Iterative development:
Just as with traditional products, data products should undergo iterative development, incorporating user feedback and adapting to changing needs.
Quality and consistency:
Ensuring high-quality, consistent data is akin to ensuring a physical product meets quality standards. This builds trust and reliability.
Goal alignment and communication:
Helping business and data teams design data products aligned to business value in real projects they work on. They document, measure, and communicate on key performance metrics of data products, and manage user expectations.
Cross-functional collaboration:
Effective Data Product Managers facilitate collaboration across IT, data science, and business teams, bridging gaps and fostering a cohesive approach to data strategy.
Monetization strategy:
Data Product Managers help set prices for data product monetization strategies.
Data contracts:
Ensure data contract & SLA adherence.
Great product leaders understand that simply building a product is not enough—they must also drive adoption and engagement. Similarly, data product managers should focus on creating data products that users actively want to use, rather than being forced to use them.
This can be achieved by involving end-users throughout the product development process, gathering feedback, and iterating based on their needs and preferences. By fostering a sense of ownership and engagement, data product managers can increase the likelihood of successful adoption and sustained usage of their data products.
By designing data products that are both functional and delightful to use, organizations can bridge the gap between IT and business, ensuring that data initiatives are aligned with business goals and user needs.
We asked our product experts at One Datawhat they think makes a great product:
"From my UX perspective, a good digital product is characterized by the fact that it creates value at the interface between user needs and business needs. A consistent focus on users doesn't just play a role during development, but is also an important basic principle when searching for a business model - especially when it comes to complex enterprise software. After all, a good product must solve real problems for people. Through intuitive user guidance, appealing design and high performance, it helps people to focus on the essentials and navigate through the digital world with little mental baggage.”
Kyra Bollmeyer, Teamlead UX&UI, One Data
"A good product meets the needs of its users, delivers concrete business value or resolves a pain point, and offers exceptional functionality. It must be reliable, high-performing, and easy to use. Additionally, a good product drives innovation, creates new demands, and continuously evolves to improve.”
Ziye Wang, Head of Product Management, One Data
"In my opinion, a product is good if it contains all the promised functions, explains them in a simple and understandable way and is intuitive to use. It is also characterized by good quality, which causes me as a user no or hardly any problems that would interfere with its function or hinder me in my work or use of the product. In addition, updates and enhancements should be clearly communicated and I should be able to provide feedback.”
Lukas Lang, Senior Release Manager, One Data
“A product solves a problem or improves the user's life. In business, this means creating more value, being more efficient, or saving money. A product is also alive and constantly being expanded. However, a product cannot be alone, which means that the surrounding is also crucial. This, along with the discovery of new fields and technologies, is what makes it work. Listening to the user is vital for making a product market-ready. This is what makes a product successful.”
Dr. Florian Stegmaier, Head of Software, One Data
Why your company needs a Data Product Manager
Data Product Managers bring a unique blend of skills that bridge the gap between data science and business strategy. Here’s why your company should consider this specialized role:
- Focused data strategy: They ensure that your data initiatives are aligned with business goals
- Enhanced collaboration: By facilitating communication between technical and non-technical teams, they enhance overall productivity
- Improved data quality: They implement robust data governance practices, leading to higher quality data
- Innovative solutions: They drive innovation by identifying new opportunities to leverage data for business growth
- User-centric approach: They ensure that data products are user-friendly and provide actionable insights
The Complete Data Product Manager's Cheat Sheet
One Data has brought together a curated, complete list of skills and strategies Data Leaders should adapt from Product Managers to become kick-ass Data Product Managers. This will provide you with guidance a through your data product journey and is a resource to cross-check along the way.
Download the Data Product Manager’s Cheat Sheet here ↓
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More InformationConclusion
Everyone is talking about data-driven decision making. Everybody wants it, a few of them actually get it right. Data Product Managers play a crucial role in unlocking the full potential of an organization’s data assets. By adopting the mindset and practices of exceptional product leaders, data product managers can design data products that are not only functional but also delightful to use, bridging the gap between IT and business, and fostering a data-driven culture across the organization.
By treating data as a well-designed product that users actively want to engage with, data leaders can drive innovation, enable better decision-making, and ultimately create a competitive advantage for their organizations.
At One Data, we understand the critical role of Data Product Managers and the importance of data products to deliver measurable business value. Our platform is designed to help you build, manage, and share your data products efficiently, ensuring they are user-friendly, reliable, and aligned with your business goals. With One Data, you can improve data quality, and enhance collaboration across your organization. Discover how we can help you transform your data into valuable assets that your business users will love to use.
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