Today, predicting weather patterns is important not only for agribusiness, but also for cosmetics, construction, and other industries. Let's break down how weather data helps optimize business processes.
Data from numerous modern scientific studies show that changes in weather - daily, seasonal, and multi-year - have a definite impact on cycles of world economic development, surges in population morbidity, and the reproduction or extinction of insects, animals, and plants.
It is important for business to understand exactly how the climate, and with it the weather, changes directly in the areas where the company's production facilities and key markets are located.
Having reliable information about the weather, on top of the lack of availability of this information, turns into a critical competitive advantage, and miscalculations and lack of awareness can even lead to full-scale disasters, remember for example the energy crisis of 2021 in Texas, which left people without heat and light due to frozen wind turbines.
The most obvious problem that more accurate predictions of weather changes can solve under current conditions is the marked decline in crop yields in many countries. According to experts, the growing demand for food, along with a reduction in supply, will make food even less available to the world's poorest people, in whose expenditure structure food accounts for the largest share.
If there are more hungry people in the world than there are now, this could lead to additional social tensions - Sri Lanka's recent food crisis are telling.
Just in these cases, the use of fundamentally different quality weather forecasts can directly affect the productivity and economics of agriculture through the reservation of farm machinery, the purchase of necessary tools for the sowing campaign, and the selection of the most resistant crop varieties for sowing. Therefore, meteorology plays a critical role in food security around the world.
Businesses have numerous tasks that require accurate forecasting of weather conditions, both now and in the foreseeable future. For example, a change in air temperature by just one degree in either direction stimulates a noticeable increase in sales of a whole range of goods, from climate control equipment to beverages and skin care cosmetics.
Cab services are directly affected by changes in weather conditions. For example, when it rains, people use cab services more often. If a cab service has access to quality predictive weather analytics, it can predict the deterioration of weather in a certain area of the city and send additional cars there in advance. This will ensure sufficient supply and normal price.
The deterioration of weather conditions directly affects people's desire to go out and shop offline. Similar to the cab service, a service with accurate operational data can send additional couriers to the most popular locations - and if the competing service has no such information, it is obvious whose side has the advantage.
Longer-term forecasts can also affect in complex areas such as construction, for example. For example, adverse weather can lead to damage or destruction of foundations and walls at construction sites.