Humans first evolved to survive on the Rift Valley savannah and make quick snap decisions to survive and thrive.
Our ancient challenges as a species involved deciding whether to run, hide, or fight an attacking lion, elephant, or buffalo, along with were to hunt food and drink water.
In so doing, as danger approached our ancestors, the speed at which they made decisions literally determined whether they lived or perished.
Therefore, humans gained knowledge of not just learning from prior experiences, but also gaining understanding from fellow people who could pass down frameworks, suggestions, and cultures to keep us safe through individual actions and in cohesion and coordination through with others to find strength in numbers without ever having to experience a danger or obstacle to know how to overcome it.
Unfortunately, we take that ancient survival technique with us into our modern workplaces, businesses, and farms to rely on frameworks and non-experientially learned knowledge. The sad part of the equation: our unconscious and learned assumptions are often wrong.
These assumptions confound the schism between what science knows and what businesses and agricultural practices actually do.
As examples, science knows that annual employee appraisals hurt individual and organisational performance, yet nearly every organisation conducts them.
Science also knows that intrinsic rewards that employees feel when working in employment comprise the majority of motivation in job settings. Science additionally understands that bottom-up product development planning yields superior entrepreneurial performance.
At the same time, most entrepreneurs feel like they retain a brilliant idea, share it within their echo chamber of family and friends, and then proceed confidently without focus groups, surveys, prototypes, or soft launch modifications to pinpoint and develop the best most user-centric products and services that delight customers and earn the most profits.
Agricultural growers and industry support entities also make often tragic assumptions without thoroughly investigating the facts of their industry.
The African Union Commission’s agriculture science, technology, and innovation arm, the Forum for Agricultural Research in Africa (FARA), recently held a Trade, Business, and Economic Transformation Opportunities in Postharvest Solutions session as part of the 3rd All Africa Post-Harvest Congress and Exhibition.
It showcased cutting-edge research on reducing post-harvest loss across the continent. One particular paper that was presented highlighted the dangers of making business decisions based off of conventional wisdom really rooted in assumptions and not backed by scientific facts.
Lila Cardell and Hope Michelson from the University of Illinois at Urbana-Champaign investigated price fluctuations in post-harvest grain sales and commensurate grain storage returns across Africa.
The new research looks at a vast 5,099 market-year observations for primary maize seasons in 506 markets.
The study ponders whether grain storage can even out the price of grains or actually end up harming farmers with lower returns due to fluctuations in seasonal prices.
Their research contradicts numerous earlier studies that advocated for providing credit to farmers for grain storage, distribute storage equipment to farmers or local centres, encourage communal storage, or combinations of these three.
However, the earlier research typical made the incorrect assumption that lean season pricing will always be higher than prices immediately after harvest.
Conversely, this new research found that in 21.6percent of all market-years, the lean season price is actually lower than the harvest price.
During such instances, the lean season price can be substantially worse than harvest prices in staggering ranges of six percent to 23 percent less.
While overall positive returns dominate the grain storage results, negative returns to storage shockingly occur periodically in all years in almost all markets and in all months post-harvest.
Therefore, grain storage is not an optimal decision for all farmers in all markets. To overcome the quick decisions that come with a lifetime of learning frameworks and information, break free from conventional wisdom and bias and do not look at average returns across markets to determine storage appropriateness since significant standard deviations hide vast differences whereby farmers can be harmed by post-harvest grain storage.
The lean season price will always be higher than the harvest season price. Instead, data must be analysed with average seasonal differences considered in policy decisions.
Interestingly, country-level yields do not prove to be good predictors of negative returns from storing grain. The study shows that farmers and supporting organisations should look at sub-national or local yields.
Also, higher harvest prices than usual often, though not always, are associated with an increased likelihood of negative returns from grain storage.
So, farmers can frequently, but not continuously, predict positive or negative returns from storage.
In conclusion, do not make blanket assumptions. Put in the extra time to gather and investigate data and make the right scientific decisions for your business venture whether in a sector that comprises agriculture as the backbone of our food security or even in the most high technology firm or financial institution.