Across Africa, most large-scale surveys funded by donors have ground to a halt.1 Large, commercial platforms like IQVIA often struggle to offer granular data in Africa at low enough costs. New mechanisms that aggregate granular data across public and private sectors to inform decision-making are required. Recent conversations with 5 startups offering health data-as-a-service reveal that a commercial market for ‘data-as-a-service’ is slowly emerging in Africa.
Data sales are emerging – mostly to pharma companies
Of the 5 executives we spoke to, 3 are currently monetizing data on product movement, consumption, and pharmacy sales.
The pharmaceutical industry is their main customer, purchasing data to monitor product consumption, track new product launches, and conduct targeted campaigns across high-priority markets. Most data sales are tied to specific use cases (consumption trends for high-priority products across selected cities) or offered via subscription models that provide ongoing access to pharmacy-level data.
Pricing varies, but even the most valuable datasets are typically sold at low rates compared to global benchmarks, as African datasets are often perceived as less valuable.
Executives noted that with several multinational pharmaceutical companies exiting African markets, the buyer pool is shrinking. Few generic drug manufacturers have expressed willingness to pay to date.
Donors and governments are not yet major customers.
On the donor side, two challenges surfaced: First, donor and global health agencies often want to purchase data through short-term grants, versus purchasing data on longer-term contracts. Second, global-access requirements can inadvertently erode the commercial value of proprietary datasets if they’re not managed carefully. However, startups may lack the knowledge or interest to adapt their business models to the purchasing patterns of the public sectors, and/or negotiate with donor customers to find “win-wins” for all parties.
With respect to governments, startups noted that procurement hurdles, limited budget allocations, data privacy concerns, and the complexity of integrating new data streams into existing systems all act as barriers to establishing paid, ongoing partnerships.
What’s Needed to Foster More Partnerships for Data?
While still nascent, the data being generated by African healthtech startups digitizing supply chains and service delivery holds enormous promise. Reliable, granular, low-cost data from startups could play a transformative role in optimizing resource allocation, responding to emerging pandemics, strengthening supply chain resiliency, hastening new product introduction, and more. Four ideas to grow the nascent markets for data-as-a-service emerged in discussion:
1. Demonstrate Clear Return on Investment, in the Language of Customers
Executives noted that startups that can develop compelling, ROI-driven use cases that show how actionable insights directly reduce costs, improve procurement efficiency, reduce stockouts, or enhance patient outcomes are going to be best positioned to succeed.
2. Standardize Data Governance
Executives noted that establishing clear, standardized policies on data sovereignty, privacy, and sharing protocols across regions and the continent can help grow the market of providers building data systems. Standardized policies will enable the private sector to build systems for larger markets and ease the process of integrating into national systems.
3. Adapt Business Models & Design Contracts That Protect Value
Startups interested in expanding into public sectors would need to adapt business models to the purchasing structures of donors and governments, which can be very expensive and risky. On the flip side, public buyers could adjust contracting structures by, for example, offering time-bound exclusivity arrangements or longer-term vendor contracts. Enabling some flexibility in contracting can help make partnerships more feasible for commercial players to sign.
4. Foster Long-Term Demand & Integrate Data into Decision-Making
For governments to purchase data, they may need additional capacity to price data-as-a-service, procure the data, protect it, analyze it, and use it to inform decision-making. This may require investments in data literacy, procurement reform, budget and pricing, and cross-agency coordination to fully embed data into routine decision-making.
As health markets become increasingly digitized, AI develops, and computing power grows, we’re excited to see new models for collecting, aggregating, analyzing, and using health data to power patient impact grow.
