Business Situation
Suboptimal Supply Chain and Processes
Production, warehousing, logistics, and sales achieve their operational goals, but decisions made in individual areas are not always coordinated across the entire system.
Local optimizations can lead to:
underutilized production capacity
costly schedule adjustments
How This Situation Manifests in Practice
Each stage of the supply chain has its own performance indicators and reporting mechanisms. However, there is a lack of a cohesive analytical model that:
- considers the dependencies between demand, production, and inventory,
- analyzes the impact of decisions in one area on other system components,
- allows for the simulation of change scenarios over time,
- supports allocation decisions under conditions of limited resources.
As a result, decisions are correct within individual departments, but their combined effect is not always optimal from the perspective of the entire organization.
excessive inventory or insufficient product availability
underutilized production capacity
increased warehousing and transportation costs
frequent schedule adjustments
limited cost transparency across the board
Lack of systemic optimization reduces operational efficiency and hinders long-term planning.
Our Approach to Diagnosis
We begin the diagnosis by tracing the flow of goods and data throughout the entire supply chain.
demand structure and its variability
lead times and production constraints
inventory levels and their turnover
interdependencies between the performance indicators of individual departments
The goal is to identify areas where improved forecasting, planning, or resource allocation can yield measurable results across the entire system.
Technology and Solution Architecture
In supply chain optimization projects, we utilize predictive and optimization models that integrate data from multiple operational areas.
A typical architecture includes:
Input Data
sales, production, and logistics data
Layers
data integration and standardization layer
Models
forecasting and optimization models
Planning Scenarios and Recommendations
integration with ERP and planning systems.
The solution is designed to be scalable and adaptable to changing market conditions, as well as regular updates resulting from organizational strategic changes or market dynamics.
Sales Forecasting
Pharmaceutical Supply Chain Model
Production and sales decisions were based on manual estimations, generating significant deviations from actual demand.
A forecasting model covering the entire value chain was designed, based on historical data and econometric and ML algorithms.
Reduction of the average forecast error by 25% compared to the client’s previous predictions, and minimization of losses by reducing out-of-stock items.
Contact
A conversation is the first step to identifying the organization’s needs and assessing the project’s feasibility.
Schedule a consultation
