Digital checklists for store operational audits and self-check
We are happy to share good news. Our team has developed a new tool – SUMATUS digital checklists, that allows replace paper forms,...
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Turn data into fact-based decisions
Two in one – Advanced Analytics solutions for retailers in combination with state-of-the-art category management consulting
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.
6. Optimization.
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 information technology & services company developing AI powered assortment and inventory management solutions exclusively for retail industry.
We combined our more than 20-year experience and knowledge of retail, FMCG and category management with data science methods, such as Data Mining, Machine Learning, Predictive Modelling, Clustering, Simulation & Optimization, and developed algorithms which enable retailers convert data into insights and fact-based decisions to ensure customer satisfaction and profitable store growth.
Our tools are 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 personnel. We provide information in a way the client can immediately start making informative decisions.
We are confident that cooperation with us will allow our clients to gain competitive advantage, ensure more satisfied customers, save technical – not value-added employee time, make assortment management process transparent and ultimately lead to a higher sales and profits.
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