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SIOP Transformation for a Supply Chain Mfg.

SIOP Transformation for a Supply Chain Mfg.

Project Overview

A leading European renewable energy supply chain manufacturer undergoing organizational transformation needed to strengthen its Sales, Inventory, and Operations Planning (SIOP) capabilities across multiple regions. The existing planning process lacked standardization, analytical support, and cross functional alignment, creating inefficiencies in decision making and operational risk.

We partnered with leadership, engineering, sourcing, sales, finance, and operations teams across 4 countries to redesign and operationalize a scalable SIOP framework. The engagement included process diagnosis, analytical tool development, forecasting improvement, governance redesign, KPI management, and phased pilot execution to create a faster and more data driven planning process.

Challenge Icon

The Challenge

Inefficient process and lack of collaboration

  • Inefficient Process: The existing SIOP process was hindered by long planning cycles, data inaccuracies, and weak accountability, resulting in low organizational trust in the process.
  • Low Accuracy: Demand planning lacked a structured forecasting framework and did not incorporate supply chain intelligence, resulting in low forecast accuracy.
  • Limited Planning Visibility: The Capacity Planning function lacked a standardized framework and analytical tools to identify sourcing, inventory, and production bottlenecks, limiting its ability to make effective investment and contingency decisions.
  • Lack of collaboration: Engineering inputs such as product changes, phase ins, and phase outs were not integrated into planning, leading to poor visibility and missed customer orders.

Our Approach

Redesigned the end-to-end SIOP process through a new operating model, structured demand and capacity planning frameworks, and 20+ analytical tools that automated manual work, improved visibility, and enabled faster, data driven decisions across functions.

Operating Model Redesign

Redefined the SIOP operating model with clear roles, responsibilities, governance cadences, standardized workflows, and centralized data management, supported by onboarding and alignment workshops across functions and geographies.

Demand Planning

Built a structured demand planning framework in collaboration with KAMs supported by detailed forecasting methodologies and automated analytical tools that integrated demand trends with supply chain intelligence and KPI monitoring.

Capacity Planning

Built a detailed capacity planning process and tool customized to the client’s production lines and IT infrastructure, enabling visibility into manufacturing and sourcing bottlenecks to support proactive operational and investment planning.

Pilot and implementation

Ran numerous pilots and supported implementation for over a year by constantly evolving the process and developing new tools.

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VARKA Support

End-to-end SIOP transformation and implementation support

Process & Planning Transformation

  • Established SIOP governance framework
  • Standardized demand and capacity planning processes

Analytics & Decision Support

  • Developed forecasting and planning analytical tools
  • Improved KPI visibility and planning coordination

Pilot & Implementation

  • Conducted pilots and supported phased implementation
  • Continuously evolved processes and developed new tools over one year
Outcomes & Impact

Outcomes & Impact

Measurable results and lasting improvements

The redesigned SIOP process drove significant operational excellence by streamlining workflows and improving forecast accuracy to enable proactive investment decisions through a faster, cross functionally integrated planning framework.

60% Reduction in process time
50% Improvement in Forecast Accuracy
40+ Proactive Planning
60% Improved Collaboration
  • Faster Planning Cycles:
    Reduced SIOP process cycle time by 60% through governance redesign, workflow simplification, and automation of manual planning activities.
  • Improved Forecast Accuracy:
    Improved demand forecast accuracy by 50% by implementing structured forecasting methodologies and analytical planning tools across commercial and supply chain teams.
  • Proactive Planning:
    Enabled proactive sourcing, production, and investment planning through the implementation of standardized capacity planning frameworks and tools, including support for a $150K machinery investment decision.
  • Improved Collaboration:
    Improved coordination between engineering, operations, and supply chain teams by integrating product changes and lifecycle inputs into planning, reducing order fulfillment risks.