RS.SCM

Artificial intelligence & Big Data technologies for supply chain optimization

ASTOR > Solutions map > Supply Chain Optimization

One of the vital tasks in the retail business is to provide continuous stock availability on the store shelves. There should be a balance between stock and logistics cost.

Retail Suite. Supply Chain Management

  • BigData&AI based SaaS-solution designed to automate retailer’s supply chain management.
  • RS.SCM demand forecasting and replenishment system is designed for the retail chain of any size, format and product range requiring the fast improvement of their supply chain quality.
  • Activate RS.SCM subscription with minimal initial investment. No additional hardware servers infrastructure required.
  • RS.SCM is compatible with any ERP-solution used by retailers. No changes in merchandising, store management system or WMS.

Powerful supply chain analisys. The system is a powerful decision support tool. The system assesses the impact of supplier’s service level and safety stock balance across the supply chain. It helps to research trends and mutual correlations to find the most optimal replenishment options.

Optimized Demand Forecasting. Artificial intelligence chooses the most effective forecasting method and the optimal parameters for particular products.

Minimise manual corrections with automated ordering. The system calculates replenishment based on sales forecast and demand variability, considering all supply chain constraints.

Usually more commercially valuable products are introduced into the range.  The inconstant presence of products on shelves leads to lost sales. This decreases the replenishment volume of these products (especially if these products have limited shelf life). As a result, products are increasingly more absent on shelves and this process continues until they are completely washed out from the range. Lack of products on shelves leads to lost sales. RS.SCM decreases lost sales.


If customers don’t find products on shelves, a part of them will irreversibly leave for competitors. It is hard to overestimate the damage this may cause. RS.SCM is designed to prevent this scenario from happening.

Overstock decrease

Decrease in logistics costs

Decrease in amount and labor intensity of manual corrections

RS.SCM features

1 Forecasting based on demand, not sales

  • Accurate demand forecasts based on cleaned sales statistics. RS.SCM takes into consideration absence of products on shelves, anomalies in sales, promos, seasons, and holidays.
  • Various forecasting methods developed by renowned mathematicians and employed by best retailers are used for forecasting of different product groups.
  • RS.SCM forecasting mechanisms are designed to address retail specifics. It can sense trends and seasonality for rarely sold products or products with sales history based on aggregated data on different hierarchy levels.
  • Forecasting algorithms are chosen automatically to decrease the labor-intensity.

User does not need to think about the correct grouping of goods and stores to determine seasonality and trends.

RS.SCM will calculate all the options and choose the best one

2Tools focused on big data and retail business specifics

Artificial intelligence chooses the optimal replenishment method

Specialized methods capable of calculating optimal safety stock are used for the replenishment of various product groups.

Systems utilizes retailer’s advantages for the SC with one or more DCs

Product ordering for promos in several waves with DC serving as a buffer to even out forecast deviations for separate stores.

Comprehensive supply chain KPI analysis with “drill down” option

During the analysis linked parameters of replenishment can be corrected on the fly in the same interface 

3Supply Chain Analysis based on Big Data technologies

To make informed decisions regarding the company’s stock and availability, find insights and optimise the supply chain it is necessary to analyze large amounts of diverse data.

Big Data analytics provides:

  • Real time transparency of logistics processes
  • Formation of a lean supply chain;
  • Improve customer / supplier satisfaction;
  • Build effective relationships with suppliers;
  • Better understand product performance to optimize range and decrease waste;
  • Unified and modern communications system for operational decision making.

Integration

SOA of the solution enables you to create full functioning, reliable and easy structured integration with other systems. It allows quick, trouble free and secure data exchange implementation.

RS.SCM position within Retail Chain Management System

Recent posts about RS.SCM

Benefits of AI based automated ordering

Most demanded products generate up to 80% of the retail chain’s revenue. These products must always be present on shelves. Even one hour of product’s absence from the shelf leads to lost sales. Systematic Out-of-stock distorts sales statistics and leads to more errors in orders.   That may lead to the gradual outflow of demanded… Read More »Benefits of AI based automated ordering

How to correctly forecast demand for new products?

In the process of introducing new products into the range category managers have to consider how much of a new product should be ordered to have it all sold before the replenishment. Most retailers are trying to calculate the demand in Excel. ASTOR clients employ forecasting benefits of RS.SCM artificial intelligence. Typical solution The most… Read More »How to correctly forecast demand for new products?

Supply chains automatization in SPAR Tula

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