Result
Partnering with Plavno, Pura Esencia received an AI-powered Demend Forcasting solution that increased first-week data forecasting accuracy by 25%, increased first-month data forecasting accuracy by 20%, reduced deviation from stable benchmarks to 1%, and reduced the time demand forecasters spend on generating analytics by 40%
Customer
Pura Esencia is a cosmetics and personal care brand from Spain. Pura Esencia's products are based on original, innovative solutions. The company employs 35,000 people. Pura Esencia has its own network of cosmetic boutiques with 92 stores in Spain and France. The company sells 400,000 products monthly. The demand forecasting department consists of 10 people
Challenges & solutions
Pura Esencia analysts used standard forecasting methods. They spent 60-70% of their working time only on calculating and making adjustments to the base forecast using standard methods, without taking into account new data. Manual forecasting has two shortcomings - forecasting is time-consuming and the accuracy of the data is low. The final results deviated from the estimated values by more than 30%
We started with conducting an exploratory data analysis (EDA). We identify deviations from the median values of past sales and data outliers. Exploratory data analysis was necessary to ensure that our model did not adjust for random, unpredictable occurrences that do not reflect real trends in demand forecasting. We developed a custom splitter to valid splitting the data for further AI model training and testing. Also we created a variety of statistical, weather, and calendar attributes to identify how demand might behave in different conditions
Demand for FMCG products is variable and depends on several factors: seasonality, promotions, macro environment, weather, competitors' activity and regional specifics. These factors are the basis for frequent mismatches in demand forecasts for Pura Esencia products. Incorrect demand forecasts led to overstocking or understocking of warehouses and higher storage and transportation costs
Plavno developed demand forecasting tool that can perform calculations in a reliable and automatic manner. Our solution has proven to be effective in automating the demand forecasting process and generate two types of demand forecasting: operational (short-term for 82 weeks) and strategic (for 5 years). These forecasts will enable to offer the optimal assortment of goods, control deliveries, use additional resources if necessary, and do other operations based on the obtained expert report
proccess
Agile methodology forms the cornerstone of our work philosophy. Through a seamless blend of innovative practices, including regular demos, comprehensive progress tracking, and a unique pay structure based on hours invested, we've constructed a workflow that ensures optimal outcomes and client satisfaction.
project team
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