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Demand Forecasting

Demand forecasting

We built a sales forecasting system and optimized the volume of goods in the warehouse and the range of goods in different locations, considering each outlet’s specifics. We set up a system that has processed more than 8 TB of sales data. These have helped the retail business increase revenue, improve logistics planning, and achieve other business goals.

88%

forecasting accuracy

0.9%

out-of-stock reduced

About the client

Retail trading company focused on production of luxury goods, available in more than 3,000 stores worldwide.

Tech stack

ReactJS

Django

Pandas

Pyspark

Redis

Revolutionize your Demand Forecasting and Inventory Management Now

Transform your sales data with our solution that achieved 88% forecasting accuracy, and reduced stockouts by 0.9%. Don’t miss out—secure your advantage today!

Challenges & solutions

Challenge

Optimize the volume of goods in the warehouse by location.

Solution

Built clusters of stores taking into account customer behavior.

Built a basic model based on time series forecasting.

Built a refined model based on the neural network taking into account additional factors such as holidays, economical indicators of countries where stores are located, weather conditions, etc.

Challenge

Optimize the assortment of goods in various locations taking into account specifics of each outlet.

Solution

8TB/24month sales data processed.

19%/$142mln reduced the volume of residues in warehouses.

Challenge

Build a sales forecasting system.

Solution

88% accuracy of forecasting.

0.9%/from 4% decreased the out of stock level.

I think what is really special about the VOLTERA service is its flexibility, openness, and level of quality and expertise.

Andrew M.

CEO
Luxury Goods Retail

The way we deal with your task and help achieve results

Step 1 of 5
Free consultation

It’s a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5
Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

In Data Science, there are numerous models and approaches, so at this stage we perform a set of interviews in order to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create solution architecture, a project plan, and a list of insights or features that we have to achieve.

Step 3 of 5
Solution development

The work starts with data gathering, data cleaning and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for the further development. Ultimately, we interpret the results. Nevertheless, data modeling is about a process that requires lots of back and forth iterations. We are result focused, as it’s one of our core values as well.

Step 4 of 5
Solution delivery

Data Science solutions can be a list of insights or a variety of different models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5
Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Success stories

Check out a few case studies that show why VOLTERA will meet your business needs.

Healthcare

Data Science

Data Insights & Forecasting

Stock relocation solution

The client was faced with the challenge of creating an optimal assortment list for more than 2,000 drugstores located in 30 different regions. They turned to us for a solution. We used a mathematical model and AI algorithms that considered location, housing density and proximity to key locations to determine an optimal assortment list for each store. By integrating with POS terminals, we were able to improve sales and help the client to streamline its product offerings.

10% productivity boost 7% increase in sales

Mark S.

Partner Pharmacy network,

View case study →

Client Identification

The client wanted to provide the highest quality service to its customers. To achieve this, they needed to find the best way to collect information about customer preferences and build an optimal tracking system for customer behavior. To solve this challenge, we built a recommendation and customer behavior tracking system using advanced analytics, Face Recognition, Computer Vision, and AI technologies. This system helped the club staff to build customer loyalty and create a top-notch experience for their customers.

Christopher Loss

CEO Dayrize Co, Restaurant chain,

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Performance Measurement

The Retail company struggled with controlling sales and monitoring employees’ performance. We implemented a software solution that tracks sales, customer service, and employee performance in real-time. The system also provides recommendations for improvements, helping the company increase profits and improve customer service.

Amir R.

CEO, CEO Fashion Retailer

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Supply chain dashboard

The client needed to optimize the work of employees by building a data source integration and reporting system to use at different management levels. Ultimately, we developed a system that unifies relevant data from all sources and stores them in a structured form, which saves more than 900 hours of manual work monthly.