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Home » Digital Twin Solves Burning Questions for Tobacco Giant Philip Morris

Digital Twin Solves Burning Questions for Tobacco Giant Philip Morris

November 8, 2021
Jess White, SupplyChainBrain

Philip Morris International employed a digital twin of its supply chain to manage product sourcing, capacity planning and a pool of “what if” scenarios.

On its journey to replace cigarettes with electronic and smoke-free alternatives, Philip Morris International Inc. realized early on a need for digital control of its supply chain that would allow the company to adapt to new market dynamics. 

The U.S.'s largest tobacco company needed support answering questions like: How much product capacity do we need, and for which product platforms? Where? And how fast? 

PMI sought a solution that would help grow and sustain its manufacturing network and competitive sourcing edge, and chose to leverage digital twin technology from supply chain software company River Logic Inc. The digital twin would offer end-to-end visibility of PMI’s global manufacturing network, enable scenario planning and what-if analysis, and ultimately drive strategic decision-making across global product sourcing operations. 

Building a Twin

From the start, it was essential to establish an accurate digital representation of PMI’s physical manufacturing network from an operational and financial perspective. Both PMI and River Logic took time to engage with key stakeholders and stress test a “base case” — validating the results through specific case studies. By feeding the model with factual inputs and making sure the outputs were correlated, PMI was able to validate the accuracy of its manufacturing digital twin as a reliable, exact model of the business. The solution uses 70 distinct sets of data. 

The two companies then designed a simple operating model around a lead scenario concept. Changes in lead scenario outputs are visualized against the previous lead, describing recommended changes in the course of action. Users can also set up individual what-if simulations based on the most up-to-date, shared version of the plan, while employing the lead scenario as “parent scenario” for their simulation.

Quantifiable Impact 

In less than a year, PMI began to experience a positive impact across its business in the following ways:

  • Process efficiency. The company cut its use of spreadsheets for analytics from more than 300 datasets to virtually none, and product sourcing studies can be completed within hours.
  • Strategic growth. Prompt and factual data-based options — with an unlimited number of what-if scenarios — drive faster decisions and improve product supply resilience. PMI has extended its strategic planning horizon up to 10 years. 
  • Business performance. The company established an optimum sourcing network, highlighting the fastest and most cost efficient way to supply markets at a global level, as well as a roadmap of how to improve asset utilization down to the factory and machine level.
  • Resource allocation. In general, PMI has shifted the focus of its Manufacturing Capacity and Footprint team from spreadsheet analysis to tasks that deliver greater value for the company. Today, more team members focus on generating strategic insights to facilitate decision-making. 

Going forward, PMI says it may expand the use of the technology to similar areas of its business, such as semi-final products capacity, sourcing and tobacco leaf purchasing, and inventory optimization.

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