Caption: Interactive map presenting country specific data, including universities and incubators contacted for the study and the digital innovations identified at the time of the study
Full Country Report (PDF)
Madagascar Ranked 12 out of 16 Countries in the Benchmark
The benchmark assessment reflects the extent to which Madagascar is unlocking positive pathways towards a digital economy and supporting a vibrant ecosystem of different actors.
Caption: Results from Benchmark Assessment for Madagascar
Madagascar ranked 12 out of 16 in the benchmark assessment which suggests that it may be lacking in some key foundational pillars necessary for a robust digital economy, such as digital skills and infrastructure.
Madagascar’s highest ranking was in the digital business pillar where it ranked 7 out of 16. This pillar identifies the development of a robust marketplace for digital trade, digital financial services, and digital content.
Madagascar ranked lowest, and behind the African median, in ICT infrastructure (which identifies the availability of affordable, accessible, resilient, and reliable infrastructure).
| Group | Country | Benchmark Index Score (Adjusted) | Overall Benchmark Ranking |
|---|---|---|---|
| 1 | South Africa | 0.5891 | 1 |
| Mauritius | 0.5839 | 2 | |
| Seychelles | 0.5155 | 3 | |
| Global Median | 0.5064 | ||
| 2 | Eswatini | 0.4222 | 4 |
| Tanzania | 0.4138 | 5 | |
| Botswana | 0.4114 | 6 | |
| 3 | Zimbabwe | 0.3895 | 7 |
| Namibia | 0.3809 | 8 | |
| Lesotho | 0.3802 | 9 | |
| African Median | 0.3595 | ||
| Zambia | 0.3506 | 10 | |
| Malawi | 0.3483 | 11 | |
| Madagascar | 0.3005 | 12 | |
| 4 | Angola | 0.2985 | 13 |
| Mozambique | 0.2919 | 14 | |
| DR Congo | 0.2782 | 15 | |
| Comoros | 0.2497 | 16 |
Caption: Overall Benchmark Assessment Results and Rank for all SADC member states
For further information on the benchmark results and regional trends please read the Situational Analysis Report.
Digitalization Does Not Seem to be Prioritized or Embraced in Policies or Strategies of Madagascar
The benchmark assessment suggested that Madagascar’s digital economy is lacking key foundational elements and may be lagging the region.
The baseline of national policies, strategies and legislation suggests little focus or presence of digitalization in national plans or policies. No clear national digital plan or strategy was available.
No specific sectoral strategy or policy on digitalization within agriculture was identified.
Digitalization within the agriculture sector in Madagascar is at the embryonic stage and this is a key barrier for further economic development.
23 Innovations were Identified in Madagascar
The high number of innovations was unexpected due to the benchmark rankings and limited findings from the policy baseline which suggested Madagascar is lagging in digital transformation.
All use cases were present in Madagascar: digital advisory, agri-digital financial services, digital procurement, agri e-commerce and smart farming. However, there was a clear gap around agri-digital financial services with these being the least common.
Caption: Diagram illustrating number of identified innovations and their sub use case solutions.
Innovations in Madagascar are present in all stages of the value chain, with the most common providing solutions in planning, on-farm production, and access to markets.
Caption: Diagram illustrating number of innovations identified in each phase of the value chain.
The results from Madagascar suggest there is a clear challenge for innovations to reach scale and financial sustainability. 44% of respondents were in the early stages of development and were largely made up of innovations operational only in Madagascar. Many of these were reliant on donor grants for funding and required further subsidies to remain sustainable.
Digital Agricultural Courses Must Be Integrated into the Curriculum and Greater Access to Digital Agriculture Technologies is Required
The university targeted in Madagascar does provide some digital agriculture training courses, including Artificial Intelligence for agriculture, coding for agricultural systems, and developing solutions for weather forecasting for farmers. Digital entrepreneurship training is also provided on topics such as Smart Farming, and ICT-enabled advisory services.
Despite teaching several courses, universities lack the appropriate tools and technologies for much of the content. For example, they teach students about drones but do not have a drone. General ICT infrastructure is also weak or limited which limits the breadth of courses.
Unlike universities, incubators do not seem to have integrated digital agricultural courses into their curricula. Raising awareness about the importance of digital agriculture for the future development of the agriculture sector and entrepreneurship space should be a priority.
Icons - credit to NounProject https://thenounproject.com/
