Course: Digital Product Management Industry Project
Team MKM: Eva-Liisa Heinmaa (Conversion Master in IT), Tiina Vint (Conversion Master in IT), Yaroslava Mykhailenko (Master's in Computer Science), Alamin Khan (Master's in Computer Science), Shirley Salm (Digital Product Management micro-credential programme)
Semester: Spring 2024
The challenge
A significant amount of data produced by public and private sector organizations remains underutilized, often confined to the organization where it was generated. Yet, the potential benefits of data sharing are substantial, presenting opportunities for revenue through data sales and the creation of additional value from data assets.
Although various ministries and institutions have explored different facets of data findability and data exchange, there is no platform (data marketplace) that provides a comprehensive overview of all government-held data while also facilitating data exchange within the private sector to discover, access, and monetize a diverse range of data sets.
The challenge lies not just in the physical availability of data but also in the ease with which it can be found, understood, and employed effectively. Improving data accessibility could unlock significant economic, social, and technological benefits by facilitating innovation, enhancing decision-making processes, and enabling more efficient operations across sectors.
Process and solution
Throughout the course, the MKM team (Majandus- ja Kommunikatsiooniministeerium) actively employed various Design Thinking and Digital Product Management methodologies and tools. Their workflow included sequential stages such as identifying pain points, conducting user research, generating ideas, developing prototypes, and testing usability.
During the problem discovery stage, the MKM team highlighted the following issues:
• Data Maintenance and Ownership: Who is responsible for maintaining the data? Who holds ownership of the data?
• External vs. Internal Data: How can we manage open, business-owned, third-party commercial, and processed data within the same platform?
• Data Storage: Where is the data stored? Where is the raw data stored? Where is the processed data stored?
• Data Quality: Who is responsible for ensuring data quality? How do we guarantee that the uploaded data is valid and compliant with the law?
• Data Integrity: How do we ensure that data remains accurate, complete, and consistent throughout its lifecycle? This involves protecting an organization’s data from loss, leaks, and corruption.
• Business Model: How do we ensure that the business model is effective and sustainable?
After conducting in-depth user research and market analysis, the MKM team decided to focus on the following How Might We question: “How might we make the platform more attractive?”. This question prompted them to design an AI-driven search engine to enhance the user experience and make the Data Marketplace more appealing, allowing users to find data effortlessly without needing extensive data science knowledge
Our aim was to design for a user who doesn't have a lot of knowledge about data. Our main persona is Lisa who has a question and needs data-driven answers. The AI-powered search is perfect to help her, since using it doesn't need any data-related knowledge and it gives a wide range of answers and opportunities to dig deeper. To make the data world even more attractive and easily understandable, we have planned a feature of visualization.
- MKM Team
MKM team's innovative solution tackles the significant challenge of making data more accessible and valuable to a broader audience. Utilizing natural language processing and advanced algorithms, the AI search engine provides precise and relevant results, delivering data-driven answers and visualizations in response to user queries. The project also aimed to address important issues like data quality, security, and legal concerns related to data ownership and the protection of sensitive personal information. Moreover, MKM team spent significant time on ensuring the best possible user experience for the Data Marketplace users.
We focused on the user interface to make the platform intuitive, logical, and user-friendly. We thought through how and when to display different features and how to make keyword and filtering systems innovative and logical.
- Tiina Vint, Conversion Master in IT student
This project showcases the potential of AI technology to transform data accessibility, encourage a culture of data sharing and utilization, and emphasize the importance of data as a valuable asset for both individuals and businesses.