Supply Chain Analytics for Data-Driven Supply Chain Planning, Optimization and Risk Management

Supply Chain Analytics for Data-Driven Supply Chain Planning, Optimization and Risk Management

Supply Chain Data Analytics Solution in Brief

Supply chain data analytics helps plan and optimize supply chain operations based on analytical insights. Supply chain analytics software integrates with ERP, CRM, a procurement management system, an order management system, etc. Solution costs vary from $200,000 to $400,000 for a midsize company.

The Architecture of a Supply Chain Analytics Solution

Supply chain analytics solution usually comprises the following elements:

Core Functionality for a Supply Chain Analytics Solution

With 33 years in data analytics, and 10 years – in supply chain management, Pine Analytical designs and builds supply chain analytics solutions with customers’ business needs at the core. Still, we reveal some common features, which such solutions include.

Key Integrations for Supply Chain Analytics Software


At Pine Analytical, we don’t see a supply chain analytics solution as a stand-alone system. To enable it provide valuable insights, Pine Analytical integrates supply chain analytics with the following systems:

  • Procurement management system – for spend monitoring and analysis, purchasing trends analysis, spend forecasting, etc.
  • Supplier management system – for supplier performance monitoring and analysis, supplier risk analysis, bid analysis, payment terms analysis, AI-based recommendations on supplier assignment to purchase orders, etc.
  • Inventory management system – for data-driven inventory allocation across different storage locations, inventory demand planning, lead times prediction, etc.
  • Transportation management system – for the overall freight spend analysis, route schedules planning, transportation costs analysis, carrier analysis, shipping method analysis, etc.
  • Order management system – for order execution analysis, returned order analysis, delayed order analysis, etc.
  • Enterprise resource planning (ERP) system – for analyzing procurement, storage, transportation, etc. costs, identifying how the disruptions in the supply chain influence the bottom line, devise strategies for reducing the end-to-end supply chain costs; for leveraging supply chain analytics insights at all levels of enterprise planning (operational and business planning).
  • Customer relationship management (CRM) system – for comprehensive customer demand forecasting and planning.

Factors Determining Supply Chain Analytics Success

Pine Analytical’s consultants have defined important factors that should be covered to ensure the success of supply chain analytics solutions: 

Cost Factors and Benefits of Supply Chain Analytics Implementation


The cost of a supply chain analytics project, which involves developing a data warehouse, OLAP cubes, and self-service reports and dashboards may range as follows:

  • $70,000 – $200,000* – for companies with 200 – 500 employees.
  • $200,000 – $400,000* – for companies with 500 – 1,000 employees.
  • $400,000 – $1,000,000* – for companies with 1,000+ employees.

*Monthly software license fees are NOT included


The cost of supply chain analytics implementation varies greatly depending on a number of factors, such as:

  • Number of data sources for integration (ERP, CRM, order management system, supplier management system, logistics management system, etc.).
  • Data complexity (structured, semi-structured, unstructured, real-time, etc.).
  • Data volume.
  • Complexity of supply chain data cleansing.
  • Complexity of data analysis, ML and AI capabilities.
  • Data security requirements.
  • User training, if necessary.

The major financial outcomes include:

Minimized supply chain risks and optimized product flow

Early identification of supply chain disruptions and prediction of the future risks (e.g., extreme price swings due to interruptions in the flow of raw goods) for quick risk assessment and mitigation.

Enhanced supply chain planning

End-to-end visibility into and analysis of each component of the supply chain to achieve consistency in procurement planning, production planning, sales planning, etc. and fulfill the demand cost-efficiently.

Maximized ability to meet demand and up to 20-30% fewer inventory costs

Accurate demand forecasting, identification of an optimal inventory level, and optimal shipping frequency and quantity help plan capacity and minimize stockouts and overstocks.