Driving scale
Big data analytics and AI solutions, have demonstrated their value to create impact for a better society, by enabling data-driven decision making and mitigating risks in a wide range of use cases across the world. We have highlighted some of the best solutions developed in the Portfolio section of the Toolkit.
The challenge now is to set up the right business model to encourage the adoption of these solutions in an economically viable way across the world. This will drive scale, encourage more innovation in the market, and ultimately create greater impact.
There are two ways to scale up and create a greater impact:
- The solution can be easily replicated – which involves applying a solution multiple times or applying it to multiple use cases.
For instance, a solution developed to combat a malaria epidemic could also be used for another mosquito-transmitted disease by changing some parameters in the algorithm (such as Zika, for instance).
- The solution can be easily expanded – a solution can grow its footprint within a country – and include more regions or cities – and impact more of the population.
For instance, a solution developed to measure the mobility flows of the population of Jakarta can be easily implemented in another city or country.
What factors facilitate the process of scaling up?
To successfully scale up a big data and AI solution, there are a number of challenges to overcome and to transform into drivers of growth. These factors are reflected in the structure of this Toolkit:
- The Ecosystem (people, processes and partnerships);
- The Technical Capabilities;
- The Privacy framework agreed by all involved in policy and regulation;
- Responsible AI by design.