Data revolution needs decision science for sustainable development

Never in the history of humankind has so much data been available; from research and surveillance data to crowd-sourced and citizen data, a staggering and growing number of digital datasets are

available, often free online.

Photo from India by Amber Peterman, IFPRI. See original

But according to World Agroforestry Centre (ICRAF) research leader Dr Keith Shepherd, for this surfeit of data to serve sustainable development, robotic data mining to will not do; the data must be translated—using decision science—into useful knowledge that helps guide decision making, from the farm to policy-making levels.

Decision science can also be used to decide what type and how much data to collect to answer particular questions, thus saving time and resources.

In a commentary published the high-level global opinion platform Project Syndicate, Shepherd says for sustainable development, “Gathering data is not enough.”

“The information must also be managed and evaluated – and doing this properly can be far more complicated and expensive than the effort to collect it.”

“If the decisions to be improved are not first properly identified and analyzed, there is a high risk that much of the collection effort could be wasted or misdirected,” he adds.

The commentary offers a lucid justification and overview of the practice of decision science, in a language accessible to the expert and layperson alike.

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Read full commentary by Keith Shepherd, on Project Syndicate: How Much Development Data Is Enough?

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