HOW IT WORKS
1. Data Planning and Modelling.
Depending on the project objectives we align necessity and existence of the company data. We assist in arranging not available data.
3. Regression Modelling.
We forecast values based on factor variables. For example, we identify effects of elasticity, substitution, cannibalization and quantify them.
5. Machine Learning.
We determine a mathematical model based on sample data using Akaike Information Criterion to make predictions. For example, we estimate future sales.
7. Prescriptive analytics.
We generate recommendations and make decisions based on the computational findings of algorithmic models. For example, we simulate various scenarios and estimate sales, gross margin, inventory turnover, out of stock, shelf stock.
2. Statistical analysis.
We collect, examine, summarize, manipulate, and interpret quantitative data to discover its underlying causes, patterns, relationships, seasonality, and trends.
4. Statistical Hypothesis Testing.
We determine whether the hypothesis assumed for the sample of data stands true for the entire population or not. For example, we determine promo effects.
We identify the best use of a resource. For example, we determine facings of SKUs on the shelf.
8. Output of Information.
We return information for decision making into client’s back office applications, like inventory order systems for further processing or Business Intelligence for user reporting.
SUMATUS is an advanced analytics tool created specifically for retail industry that fastens assortment management decisions and improves their accuracy.
We have combined our more than 20 years of experience and knowledge in retail, FMCG and Category Management with advanced analytics methods, such as Data Mining, Machine Learning, Predictive Modelling, Prescriptive Modelling, Clustering, Simulation & Optimization, and developed algorithms which enable retailers to convert data into insights and fact based decisions in assortment management in order to ensure customer satisfaction and profitable growth of stores.
Our tool is versatile and can be implemented at any stage of retail chain development despite how much data a client has and how well data storage is organized. Our team is ready to design a suitable cooperation model (collecting data from a client, analyzing, modelling, and presenting it) that requires minimum involvement from the client's management team and personnel. We provide information in a way a client can immediately start making decisions using business intelligence systems or via interface with back office applications.
We are confident that cooperation with us will allow our clients to gain competitive advantage, which ensures more satisfied customers, saves technical – not value-added employee time, makes assortment management process transparent and ultimately leads to a higher sales and profits.