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CLIMATE AND COMPANIES

Climate is the main and most uncertain variable behind changes in plans and consumer behavior. Day after day the weather determines what and how much is consumed. For example think about everyday issues ranging from from consumption of capital goods such as the purchase of equipment for air-conditioning in response to the persistence of a heat wave, even in the decision to spend a weekend outdoors, or go to the theatre or cinema in response to the conditions and the weather forecasts (when it is credible). The variability of climate is a key factor in consumers’ decisions and behaviors in general, and therefore has a great influence on the development of businesses.

At BerecoLabs we look forward to the impact of climate on sales, helping companies reduce breakdowns and the excesses of stock, and therefore to plan and invest better. Combining an extensive database with prediction algorithms based on Artificial Intelligence (AI) we can turn climate forecasts into sales’ forecasts.

We then present a case that demonstrates the use of our approach BCI (BerecoLabs Climate Intelligence) that based on forecasts of temperature and historical records of sales of a supermarket in the city of Junín, Buenos Aires province, estimates future sales and improves company’s performance indicators.

Figure 1. Temperature, estimated demand for product, stock of the product, and comparison of the results with and without the use of BCI. As you can see the use of BCI reduces breakdowns of stock and therefore the losses associated with a significant impact on the final outcome of the business.

Companies know the consequences of a breakdown of stock, losses due to the need to clean inventories or the uncertainty when investing for the next season. In line with the current trend at a global level, at BerecoLabs we develop the BCI approach (BerecoLabs Climate Intelligence) that reduces climate complexity in the decision-making process and results in a decrease in operating losses by stock breakdowns related to errors in climate forecasting. The uses of this approach can be applied to a variety of industries and have relevance in the decisions of investment or growth, operation, as the case presented here, and shares for sale on the consumption, for example in the development of internet digital marketing campaigns. With approaches such as BCI and the growing availability of data in the different industries, it is possible to imagine an evolution towards better decisions of business and higher margins in many industries.