Data-Driven Enterprises in Africa

Evaluation of Winners and Losers

EXECUTIVE SUMMARY

This report provides insights on the status quo of data analytics in data-driven enterprises in Africa's digital economy. Data-Driven enterprises refer to, broadly speaking, firms that adopt a business approach of using insights from data analysis to create business value or improve processes. In this regard, the focus of this report is the indigenous businesses in the private sector in Africa.

This report identified that data analytics in indigenous firms in Africa is in its nascent stages. Hence, it would be far-fetched to say that one industry or sector has taken a differential leadership. It looks promising in sectors like manufacturing (distribution), health, agriculture, and online platforms like social media, with enterprises deriving economic and symbolic value from data analytics. Likewise, the growing need to innovate around data in these industries and the proliferation of automated tools and applications have made data analytics more friendly to indigenous firms. Technically, a combination of proprietary (e.g. Salesforce), open-source applications (Open Data ToolKit), bespoke applications (Rx Insurance), and social media analytic applications are used in data-driven activities among indigenous firms in Africa. These data-driven activities among indigenous firms tend to be often directly or indirectly enabled by the quest of multinational companies, who seek to mutually maximise their value-generating activities as their business partners or collaborators. Thus, these multinational companies or institutions play a key role in creating awareness of the value of data and providing the motivation, and sometimes the technical and human resources, to enable indigenous firms to develop data analytics capabilities.

However, despite the promise, this growth is stifled by the scarcity of skilled personnel and expertise, coupled with a missing link in collaboration between industry and academia, limited formal educational training opportunities, lack of a proper enabling environment for the practice of data analytics, lack of awareness or limited knowledge on the value of data analytics in these firms and the government, weaknesses in our data governance institutions (not much done in monitoring and advocacy), generally limited resources to IT investment in indigenous firms, and lack of a national drive for data analytics in many countries of the Africa Sub-region.

As a result, the convenience and way data are collected and handled leaves room for possible exploitation. Additionally, while national data governance strategy and regulatory frameworks are increasingly developing across Africa, they have primarily been slow due to considerable policy gaps.

The fact is that indigenous firms are still struggling to manage resources to invest in basic IT infrastructure. Hence data analytics adoption, which requires both human personnel and technical infrastructure, is often yet to be strategically considered, shelved for the future, or even when outsourced, it is often poorly managed and under-resourced. Others are also driven by the visibility and immediacy of results or value, which is not a characteristic of data analytics. Data analytics often requires a more intentional strategic alignment to business processes, and otherwise, its value may not be realised.

Further, for innovation to occur, data analytics processes must be sustainable. It is often a long-term value realisation activity, which many indigenous firms tend to shy away from due to limited resources and understanding.

The report argues for the need to enhance data analytics use at the national and regional levels. It proposes fifteen recommendations for creating an all-inclusive enabling environment for indigenous businesses. These recommendations are categorised into three:

• Awareness (educational curriculum development, academia and industry collaboration, and enhancing women’s participation in the data economy);

• Accessibility (incentivising stakeholders to collaborate and integrate efforts and establishing common open data banks within countries and across countries);

• Adoption (institutionalising a data culture).

We also advocate that for Africa to realise the value of data analytics, data stakeholders (governments, the private sector, and the international development institutions) need to set an agenda to strengthen institutions that regulate data enterprises and create the right or appropriate technical model for channelling and sharing data within agreed ethical principles and legal mechanisms. Likewise, it is necessary to increase the readiness of indigenous businesses (awareness and enabling resources) for data analytics in order to drive uptake and expansion of the digital economy. Notably, significant data policy gaps exist across countries in the sub-region, coupled with Africa's lack of institutional capacity to enable a well-functioning data analytics adoption and usage environment. Therefore, regional efforts and multi-stakeholder participation are required to address these relatively persistent constraints. However, though regional efforts are prime, these constraints tend to send a caution that African governments, the private sector, and development agencies have to be realistic and measured in seeking a data-driven agenda. It could take more time and more effort to achieve substantial gains across the entire continent. 

The report was commissioned by the Centre for Study of the Economies of Africa and was funded by The William and Flora Hewlett Foundation.