Providing Services for Developing an Algorithm for Calculating Sales Forecasts for Purchasing Goods and Replenishing Points of Sale Using Machine Learning Tools

• Country: Russia
• Summary: Providing Services for Developing an Algorithm for Calculating Sales Forecasts for Purchasing Goods and Replenishing Points of Sale Using Machine Learning Tools
• RUT Ref No: 90979998
• Deadline: 15 Nov 2023
• Financier: Self Financed
• Purchaser Ownership: Public
• Tender Value: Refer Document
• Notice Type: Tender
• Document Ref. No.: 3467106
• Purchaser's Detail:

Purchaser : JSC MELON FASHION GROUP
190103, Russia, St. Petersburg, st. 10-ya Krasnoarmeyskaya, 22 litera A room. 1-H 6th floor
Email :mfg_directline@kept.ru

• Description:
• Description :- Providing services for developing an algorithm for calculating a sales forecast for purchasing goods and replenishing points of sale using machine learning tools
  Comments : - The goal of the project is to implement an algorithm for constructing a sales forecast using machine learning toolsFor effective planning of the purchase of goods and replenishment of points of sale.
  As a result, it is necessary to provide a service/software that includes trainable models for calculating the forecast, or transfer the source code that performs the calculation.
  The technological solution may include only a forecasting model, or may includemaintain a full-fledged service (platform) with the ability to visualize or upload data in the form of tables.
  The sales forecast should be granular to Point of sale (Store/Partner) - day - SKU, planning horizon - 9 months.
  The forecast should take into account the influence of such factors, like the seasonness, weather forecast. When processing historical data, the calculation model must take into account the characteristics of periods that are abnormal for the industry (for example, Covid). This is an incomplete set of influencing factors; it is necessary to identify the rest during the implementation of the project.
  The forecast should take into account the characteristics of sales in differentchannels (retail offline, online partners, franchising).
  Forecast accuracy is at least 85%.
  Simultaneous access to forecast data for up to 15 users.
  Data consuming systems can be: 1C, Power BI, excel, DWH storage
  Closing Date. ..
• Documents:

 Tender Notice