17.03.25 (inclusive)

payment

Idea

ICT tasks

медицина

Processing and storage of Big Data

Software/ IS

A problem for developing an automated order generation system: Currently, there is no single warehouse in the pharmacy network, so each pharmacy has its own pharmacist, who manually generates an order from distributors by looking through a list of 5,000-6,000 items alphabetically. Because of this, the process takes 3-4 days, and items at the end of the list may sell out before they are processed, leading to shortages and rejections at the checkout. In addition, manual input often causes errors, from mechanically entering the wrong quantity (for example, 100 packages are ordered instead of 10) to skipping positions. The specifics of logistics (for example, the remoteness of Aktau from the central cities) require the maintenance of a two-month inventory, which freezes working capital. When switching from one season to another, forecasting errors occur: seasonal goods (for example, cold powders) are ordered based on data from previous periods, without taking into account seasonal fluctuations and price changes (goods may be more expensive in winter and cheaper in summer), which leads to excessive or insufficient purchases. """1C" generates a statement with the columns "expenses" and "balance", where "expenses" include not only actual sales through the cashier, but also write-offs (for example, due to expiration) and transfers between pharmacies, which distorts the calculation of needs. If you only take into account sales through yandex. checkout, the data will be correct, but there will be no information about the current balance. The system should also take into account rare abnormal peaks (for example, a one-time wholesale purchase) so that they do not affect the predicted demand. It is required to develop an automated system that: Data integration: Collects and cleans data from 1C (sales for the last 5 years) and information about balances, excluding write-offs and transfers, leaving only data on cash sales. Integrates with the Pharmcenter platform.kz to get up-to-date price lists with prices and expiration dates. Forecasting demand: Analyzes historical data, seasonally adjusted, for each of the 5,000-6,000 items. It uses methods to filter out abnormal emissions (for example, one-time large sales) so that they do not distort the forecast. Calculating the need: Calculates the required quantity of goods based on projected sales, current balance, and target inventory level (reducing inventory from two months to one month), optimizing working capital. Automating the order process: Generates an automatic order that does not depend on alphabetical order, but is based on objective calculations of needs. Ensures the selection of optimal suppliers, taking into account current prices and expiration dates.

Expected effect of the system implementation: Reducing errors and costs: Automation of order generation will eliminate manual data entry, which will significantly reduce the number of errors (for example, incorrect number of packages or missed items). Optimization of the procurement process will reduce the salary pool by reducing the burden on pharmaceutical purchasers. Reducing the time required to form orders: The automated system will generate orders in real time, which will eliminate delays associated with sequentially going through the list of 5,000-6,000 items and ensure timely replenishment of stocks. Inventory optimization: Accurate demand forecasting, taking into account seasonality, will reduce inventory levels from two months to one month, which will free up working capital and reduce storage costs. Improving customer service: Timely replenishment of stocks will ensure the availability of high-demand products in pharmacies, reduce the likelihood of failures at the checkout and increase customer satisfaction. Improving work efficiency: The system should analyze sales, filter out abnormal peaks and take into account up-to-date data on prices and expiration dates, which will increase the accuracy of purchases and improve management decision-making. Together, the introduction of an automated order generation system should significantly optimize the procurement process, reduce operating costs, improve inventory management and improve the quality of service in the pharmacy network.

Khosova Madina