Defining Digital Development
'Digital transformation' is not a destination, but a journey. It is about using digital and technology to improve the lives and livelihoods of individuals, communities, and countries. This ranges from improving public services, to tackling issues of marginalisation.
UNDP advocates for inclusive, whole-of-society digital transformation. It is a coordinated approach between government, civil society and the private sector to build ownership, support human-centred design, mitigate risks, and establish accountability. To support this strategy, UNDP has implemented the Digital Transformation Framework to discover & compare progress across a range of key issues.
Overview of the Digital Transformation framework
The Digital Development Compass (DDC) is constructed based on the Inclusive Whole-Of-Society Digital Transformation framework endorsed by UNDP. The Digital Transformation Framework serves as a guide for stakeholders to align their efforts regarding inclusive digital transformation and supports countries in their transformation process. It enables stakeholders to identify, structure, and prioritise their national digital transformation initiatives and agendas effectively.
The framework represents the encompassing structure for Digital Development within the UNDP. It is the result of an extensive study that examines various frameworks, implementation strategies, and methodologies employed by diverse organisations, including those in the private sector, public sector, and international development agencies. Through this framework, UNDP aims to provide countries with a valuable resource for assessing and advancing their digital development journey, while considering the unique challenges and opportunities they may encounter along the way.
The Digital Transformation Framework is structured into seven pillars, with each pillar being further subdivided into 25 sub-pillars. Each sub-pillar corresponds to a specific element of digital transformation. The sub-pillars encompass various individual indicators, which are used to calculate a country's Digital Transformation Score. These scores are then aligned with corresponding stages of digital transformation.
Overview of The Digital Transformation Framework
Pillars and sub-pillar
The following section provides a list of the pillars and the underlying sub-pillars constituting UNDP’s Inclusive Whole-of-Society Digital Transformation Framework that form the basis of the Digital Development Compass.
Table 1. UNDP’s Inclusive Whole-of-Society Digital Transformation Framework. Pillars and sub-pillars
Measuring Digital Development
Stages of digital development
Each country's digital readiness is assessed across five stages of digital development, which encompass every pillar and sub-pillar.
UNDP's five stages of digital development
Further enhancement of countries' digital readiness can be achieved by providing individual support to each component of the transformation framework.
Digital Development Score Methodology
The software and data that are used to put together the DDC are open source and in the process of becoming Digital Public Goods. The script and datasets can all be found on UNDP’s GitHub. UNDP is partnered with GitHub’s volunteer programme and volunteers have helped to develop the novel scripts used in the process.
1. Indicator Selection
Indicators were identified by conducting desk research online into the public data available relating to the sub-pillars and pillars of the digital development framework.
These indicators are compiled into an Open Digital Development Data Exchange that includes 189 publicly available datasets and is available on GitHub. Sources of the data sets include:
- World Bank: World Development
- ITU: Digital Development Compass
- GSMA: Mobile Connectivity Index
- University of Oxford: Our World in Data
- World Economic Forum: Global Competitiveness Index
- Sustainable Development Report
- UN: E-Government Survey
- Packet Clearing House: Internet Exchange Directory
- Ookla: Speedtest Intelligence
- Universal Postal Union: Postal Statistics
- World Bank: Logistics Performance Index
- e-Governance Academy Foundation: National Cyber Security Index
- ITU: Global Cybersecurity Index
- The Global Entrepreneurship and Development Institute: Digital Platform Economy Index
- World Bank/LinkedIn: Digital Data For Development
Of the identified datasets, those where the data could be accessed and processed using the below data collection methods are included in the DDC.
2. Data Collection
The methodology used for data collection depends on the format the data is published in. Links to data sources are collected in a spreadsheet and automation is used to scrape spreadsheets, PDFs, and documents and convert them into a machine-readable format.
The below diagram visualises how updates in the source data triggers a change in the DDC webpage.
When any of the links to source data expire, an automated email notification is sent to administrators, and new links are updated manually.
3. Data Processing
Data that has been retrieved is then matched with a UN-defined list of countries, regions, sub-regions, income groups, and territorial borders.
Raw data and data from other indexes is converted to values within the DDC’s 1-5.99 range. The method used to perform this conversion depends on the type of indicator.
4. Score Calculation
Indicator level scores are weighted and averaged into sub-pillar scores. Presently, all indicators are weighted equally. Alongside the sub-pillar score, a data availability rate is calculated. This is the percentage of indicators in the sub-pillar for which there is data available for a country.
Sub-pillar level scores are then weighted and averaged into pillar scores. All sub-pillars are also weighted equally.
Where data for a country is not available for an indicator, this indicator is omitted from the calculation of a sub-pillar score. Instead, an average of the indicator data that is available is used. Similarly, where no data is available for a sub-pillar, this sub-pillar is omitted from the calculation of the overall pillar score.