5 Key Data Product Marketplace Learnings from Forrester and Workday

How do you scale data consumption by humans and agentic AI to drive business value? That’s the challenge facing Chief Data Officers (CDOs) and data leaders as they look to widen data access across their organizations.

Data products, and data product marketplaces, are central to generating value from data and making it available to employees and AI agents. As their adoption increases, Huwise brought together analysts from Forrester and its customer Workday through an executive roundtable to discuss practical ways to scale data sharing and to explain the ROI it delivers.

The executive roundtable participants were:

• Jayesh Chaurasia, Forrester Analyst, who explained the evolution of the data product and AI market
• Jan Sythoff, Forrester Total Economic Impact (TEI) Consultant, who outlined how Huwise’s data product marketplace delivers 474% ROI over three years
• Joe DosSantos, VP Enterprise Data & Analytics at Workday, who shared his first-hand experience of implementing a data product marketplace, covering what worked, and what didn’t, within his organization
• Franck Carassus, Co-Founder and CSO, Huwise, who chaired the event, contributing his experience to the discussion
  

Based on their conversations, we’ve highlighted five key learnings that help accelerate data value for humans and AI. To watch the full recording, just click here.

Jayesh explained that despite investing heavily in data technology over the last decade, users still find it difficult to quickly find the right data, understand what it means, and use it confidently. Essentially, while organizations have built much of the entire data supply chain they lack a storefront through which the enterprise can consume it. 

Forrester research backs this up. While 80% of organizations prioritize data sharing, they face challenges such as poor data quality, data silos, and a lack of data skills when it comes to consumption.

While organizations have more data and more tools than ever before, consumption remains fragmented. No matter how well designed, a data asset is not economically viable if people cannot discover, understand and use it. 

Three trends are focusing data leaders on delivering more seamless consumption: 

1. The data consumer is changing, thanks to the rise of AI agents. Agent use simply won’t scale if they are provided with fragmented, difficult to understand, or low quality data 
2. The need for adoption. Every company is now focusing on increasing data usage to unlock value
3. The need for reuse. Organizations want their data products and other data assets to be reused multiple times to increase efficiency and prevent duplication

Data product marketplaces provide the storefront to access data, helping CDOs increase data consumption. Through an intuitive, self-service interface they help humans and AI discover relevant data products, engage with data, reuse products multiple times across the business, maximizing efficiency.  

In conclusion, Jayesh explained that future business advantage will not come from owning more data. Instead it will come from acting upon that data, Success, particularly of AI, is increasingly dependent on the data accessibility rather than just data availability.

Franck stressed the central importance of reliable, quality data to AI success. While human users can double check a piece of data before acting on it, agents act directly on that data with no prior review, meaning that unreliable data will undermine their success. 

This is where a data product marketplace comes in. It makes trusted certified data products available at scale with automated and governed access for both employees and AI agents. 

Robust, descriptive metadata makes it easy for agents to find the most relevant data they need to answer specific questions and complete processes. The marketplace also provides the context required for agents to understand which data is the best fit for their specific needs. They can see which data is most used by humans for similar processes and choose accordingly. For example, if one data product is always used by finance analysts at quarter end, it sends a strong usage signal to agents carrying out similar tasks. 

To demonstrate the value that data product marketplaces deliver, Huwise commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) analysis of its solution. This was built on interviews with four customers, and Jan explained how this translated into real return on investment, based on Forrester’s longstanding methodology.

Customers chose to implement a data marketplace to overcome four pain points:

• Fragmented data landscapes across multiple tools
• Low trust in data
• Limited visibility and data asset reuse
• Slow, IT-driven data access that did not scale

A quote from one of the Huwise customers that Forrester interviewed sums this up:

As the TEI found, implementing a data marketplace delivers significant quantitative and qualitative benefits:

Quantitative: 

• Faster time to insight and productivity savings for business users, with a 50% drop in time spent searching for data
• Productivity savings on data search and preparation for data teams, reducing data time spent by data analysts by 50%
• Reduced analytics effort with a 4x drop in time wasted on duplicated work. 
• Avoided IT costs, as users access data through self-service rather than requesting reports from IT

Qualitative:

• Increased value realization from existing data investments by providing a storefront for data
• Improved data literacy with self-service adoption driving greater confidence in using data in decision-making. 
• Increased organizational agility through access to a single version of the truth
• Future ready foundation for agentic AI enablement
• Simplified deployment and reduced long-term operational costs, with payback within 6 months

Altogether this adds up to $7.8 million in total benefits over three years for a composite 10,000 employee organization. This translates to 474% return on investment in the data product marketplace. 

Workday’s decision to implement a data product marketplace was driven by a clear problem statement. As Joe outlined, it was difficult for people to get their hands on the data that they were actually looking for, amongst Workday’s thousands of data assets. Finding the right information was time-consuming and expensive for both users and the data team. 

The aim was to have trusted, unified and understandable data in one place where it is easy for humans and AI agents to access. To plan data products and to assign data owners, Workday broke down its business processes into the data domains that support them. 

By starting with a taxonomy of the business and dividing it into value chains and processes the company was able to craft data products that would exist in specific data domains and be owned by named people. This enabled it to create a data factory that mobilized and accelerated the availability of data products. 

The first asset Workday produced provides a good example of reuse and internal adoption. This covered recurring revenues and was initially used by a small group of people. By marketing it internally and sharing it via the marketplace, there are now 50 different use cases for the product across the company within three or four different operations groups.

Simply creating data products is not enough. As Joe said, if you build it they don’t necessarily come. That made making sure that people could find and use data assets the most important success factor. Workday’s Huwise-powered data marketplace provides a familiar, intuitive self-service experience for users, similar to eBay or Etsy. The aim for the marketplace is to connect consumers, such as business executives, data analysts and agents with data producers in the same way that an e-commerce marketplace does.

Achieving success meant establishing a sense of community across all the different data domains, with consumers and producers coming together. The marketplace includes robust search capabilities, providing a front door to the data products that allow all of Workday’s agents and people to find relevant data effectively. 

Thanks to Huwise, the experience is personalized to different communities, such as marketing, sales or enterprise data analytics. When they visit the marketplace, they see news, relevant assets and updates relevant to them, and can easily contribute to discussions around data or ask questions. Importantly, data products and assets can be directly viewed and consumed through the marketplace, with role-based access management to enforce security and governance.

The requirement to provide business people and AI agents with access to reliable, trustworthy data is clear and growing. Thanks to Forrester’s research, the benefits are equally understandable. Demonstrating this, the majority of roundtable attendees said they were looking to include data marketplaces within their 2026/27 roadmap, just ahead of those currently evaluating or piloting solutions. Now is the time to scale data consumption and transform data investments into business value.