Data Monetization

The Entity shall conduct a capability assessment to evaluate the Entity’s ability to monetize its data and identify the gaps that need to be addressed to achieve effective data monetization. The capability assessment exercise shall cover, at a minimum:

• Data management maturity report covering all the domains in the national data management framework
• Current state assessment report of existing technology and infrastructure

The Entity shall identify and prioritize the data products that are required to realize the Entity’s data monetization vision and strategy. For the identified data products, the Entity shall develop detailed charters for the identified data products. The charters shall outline, at a minimum:

• Data product description and development rationale
• High-level data product development cost estimate
• Expected benefits and business value aimed to be derived (ROI)
• Expected timeline for development and deployment of the data product
• Data sources that would feed the data product and the required data fields
• Priority level assigned to the data product. The Entity may follow the product effort-value matrix to prioritize its products as outlined in SA.1.1.1.SS2
• Stakeholders involved in the implementation of the data product, the owner that would lead the data product, and the target consumers that would benefit from the insights generated by the data product
• Dependencies that need to be overcome to initiate development of the data product (e.g.: technologies, resources, and capabilities required to implement the use cases)
• Indication if ethical, security and privacy components exist may exist and how they shall be addressed

• The Entity shall define and document the delivery model that it will adopt including in order to provide access to its data products including, but not limited to:
  • Raw Data (i.e.: involves selling data in its unprocessed form, usually as bulk downloads or physical media transfers)
  • Data-as-a-Service (DaaS)/ API-based (i.e.: involves providing data through an API or online service, allowing customers to access up-to-date or real-time data directly through web services)
  • Data Platform (i.e.: a comprehensive platform that not only provides data but also tools and functionalities to analyze and visualize that data)
  • Data Marketplace (i.e.: an online platform where data providers can list and sell their data to interested buyers, and can include both raw data and APIs)

• The Entity shall define and document the pricing model that it will adopt to charge customers on accessing its data products including, but not limited to:
  • One Time Flat Fee (i.e.: fixed price charged once for accessing the data product)
  • Pay As You Go (i.e.: usage based depending on the amount of data consumed by the customer)
  • Subscription Based (i.e.: recurring fee for accessing the data product)
  • Freemium Model (i.e.: basic services are offered for free, while advanced features or higher usage limits are available in paid versions)
  • Hybrid (i.e.: a combination of two or more pricing strategies)

The Entity shall develop a go-to-market strategy to support the effective launch and promotion of its data products to the market. The strategy shall include, at a minimum:

• A list of identified target industries/ audience that can benefit the most from the Entity’s data products
• A defined value proposition that may highlight how the Entity’s data products can solve specific problems or add value to businesses
• A plan outlining the marketing and sales activities and the channels the Entity will use to reach its target audience effectively. This may include content marketing, social media campaigns, email marketing, webinars, or channel partnerships

The Entity shall develop a data monetization roadmap, in alignment with the Entity’s data strategy, that will be used and monitored to implement and activate data monetization initiatives across the Entity. The roadmap shall include, at a minimum:

• List of initiatives required to:
  • Rectify identified gaps based on the data monetization capability assessment conducted in DM.1.1.2 (e.g.: this could include data quality improvement, technology investments, etc.)
  • Develop, test and deploy the data products identified and prioritized in DM.1.1.3
• Sequencing of data monetization initiatives based on their impact, feasibility, and alignment with business priorities and sequence them to ensure a logical progression towards the goals
• Resource allocation outlining the budget, personnel, and technology resources required for each initiative

The Entity shall design the data product architecture with a focus on scalability, security, and integration, and ensuring alignment with the national data architecture and modeling standards. This exercise shall include, at a minimum:

• Developing a high-level design document that includes the following indicative list of contents:
  • Brief description of the data product
  • Business and technical requirements
  • High-level architecture diagram across the different layers (e.g.: integration layer, ingestion and storage layer, data processing layer, and presentation layer)
  • Associated business processes
  • User stories/ journeys
  • Data flow diagrams
• Developing a low-level design document that includes the following indicative list of contents:
  • Detailed design diagrams covering class diagrams, sequence diagrams, state diagrams, detailed module descriptions, database schema design
  • Algorithm design (e.g.: pseudocode, flowcharts)
  • User interface design (e.g.: screen layouts, user flows, navigation maps)
  • Security specifications (e.g.: security controls, encryption techniques)

The Entity shall ensure that each data product provided or exchanged has an associated data contract/ data sharing agreement. The data contract shall be developed in alignment with the data sharing, integration & interoperability standards and shall outline, at a minimum:

• Parties Involved (i.e.: identification of all parties involved in the data exchange)
• Data Description (i.e.: detailed description of the data, including data type, format, and volume)
• Terms of Use (i.e.: specifications of the terms under which the data is provided or exchanged)
• Security and Privacy Requirements (i.e.: outline of security and privacy measures in compliance with applicable laws)
• Terms of Access (i.e.: details on access conditions, including duration, exclusivity, and renewal conditions)
• Customer Obligations (i.e.: mechanisms for ensuring customer adherence to the terms of the agreement)
• Termination Conditions (i.e.: specifications on how and when the contract can be terminated)
• Data Retention and Deletion (i.e.: obligations concerning the retention and deletion of data post-contract termination)

Based on the results of the proof of concepts and aligned to the plan outlined in the Data Monetization Roadmap (refer to DM.1.1.7), the Entity shall conduct a full-scale development of the data products. The Entity shall, at a minimum:

• Ensure the developed data products are deployed on a production environment, ensuring alignment with the delivery and pricing models defined in DM.1.1.4 and DM.1.1.5 respectively
• Measure and publish the data quality score for each of the Entity’s deployed data products across all the data quality dimensions outlined in DQM.1.1.1. An overall data quality score shall also be assigned for each data product by averaging the data quality scores for each data quality dimension
• Define and publish SLAs for the deployed data products (e.g.: service uptime/ availability, response time and resolution time in incidents where the data source is unavailable or degraded, etc.)
• Define and publish metadata information for each of the deployed data products covering, for example, temporal granularity, update frequency, etc.
• Implement versioning for each of the deployed data products, highlighting the version number and a description of the changes