In the past few weeks, the world has witnessed the usefulness of predictive analytics and Big Data in making smart decisions.
Scientists tracked Hurricane Irma as it developed in the African rain forest before moving into the Atlantic Ocean, walloping the Caribbean and retaining enough punch to hit the American state of Florida.
These predictions were precise to the minute, enabling millions of people to relocate to safer grounds. By September 15, there were 42 and 39 deaths in the Caribbean and the US respectively.
Irma followed Hurricane Harvey, which also landed in the US causing 82 deaths. Estimated property damage from both hurricanes will be in excess of $300 billion, including damage in the Caribbean nations.
Death toll from these disasters would have been significantly higher if these hurricanes had landed without prior notice. In contrast, the recent Sierra Leone mudslide and flood left more than 1,000 dead.
The difference between the happenings in the US and Africa is lack of knowledge or failure to warn citizens of an impending disaster.
Yet, increasing knowledge around Big Data and predictive analytics has made it possible to manage the intense climatic changes we are witnessing today.
While the Americas are on the receiving end of hurricanes, Africa is experiencing her own climate change disasters such as heavy rain falls and persistent droughts.
As Irma pounded Florida, the discourse on whether climate change is real or not went into high gear.
What is not disputed is increasing evidence that the world is going through some changes where we are witnessing record temperatures, extreme weather events (read Sierra Leone, the Caribbean and the US), retreating glaciers and rising sea levels. The key point of contention is whether human activity is responsible for these changes.
In my view, the world must see beyond the emerging American policy towards climate change and implement the Paris Accord, invest in predictive analytics capability, proactively spread knowledge into rural areas on the predictability of weather patterns and help the poor leverage on knowledge to deal with food security.
There is a sense in which African policy makers have left everything to God. Yet God has given us the power and tools to predict and plan for impending climatic disruptions.
The current devastating drought in Kajiado was predicted two years ago, but never communicated to the people to plan for it. Despite great advances made in predictive analytics, people still think the future cannot be predicted.
Apps like aWhere are available, and with their product Farm Insight, they are able to help vulnerable smallholder farmers predict changes in weather that can adversely affect their crop or livestock.
This product delivers a short-term forecast for precipitation and temperature anywhere in the world, no matter how remote.
The capability to make smart decisions is there. But the most frustrating aspect of living in Africa is when you see a solution to a problem and the people including policy makers fail to see the same.
Yet the people are suffering. Africa’s agricultural productivity stands at a fifth of that of other countries around the world simply because the continent heavily relies on rain-fed agriculture that is subject to the vagaries of weather.
What is painful is the fact that the knowledge to make better decisions on productivity and improve on food security, is all around us.
Most countries have embraced the concept of open data, especially weather data, and have made it available for individuals to analyse and develop own use cases.
Local gatherers of data should also embrace open data. It is such data that a Nairobi/New York-based start-up company, Gro Intelligence, uses to develop predictive solutions and identify environmental factors that drive pricing of commodities.
Making smart decisions is imperative, but Africa’s greatest problem is how to make the policymaker and common man consume the massive data that is available in an era of changing climatic conditions.
Africa, therefore, must build capability in data science, predictive data analytics and data visualization/simplification to help the common person understand its impact in their lives.