Written by 5:44 pm analytics, Big data supply chains

Philip Morris Drives Manufacturing Insights Using A Digital Twin

 

Supply chains quickly move through fads and buzz words. Over and over again, organizations fall in love with shiny objects moving from concept to concept. Unfortunately, shiny object love fests abound, but they do not drive value. The goal is to transition from fads to drive true innovation.

Today, entangled in digital supply chain discussions is the concept of the digital twin. The term digital twin, while used frequently, all too often, is over-hyped and without meaning.

In our pandemic research, we interviewed thirty manufacturers. All struggled, during the initial supply chain COVID-19 response, to run effective “what-if analysis” in their supply processes. While only thirty percent of companies have what-if capabilities today, it was not sufficient. The reason? The applications were too hard-wired into the IT architectures making ad-hoc analysis impossible. To help readers sort through the hype, we are writing articles on digital twin use cases to help companies gain a competitive advantage.

Here we share the case study of Philip Morris using a digital twin deployment. To gain insights, we interviewed Alexandros Skandalakis, Director of Manufacturing Capacity, reporting to operations/manufacturing globally within Philip Morris. This case study is written in a Q&A format. My questions to Alexandros are in bold and his answers follow.

The Use of the Digital Twin at Philip Morris

What can you tell me about your supply chain?

We are transforming from a cigarette manufacturer to a science- and a technology-led company that commercializes smoke-free alternatives to cigarettes for adults who would otherwise continue to smoke. With over 12 million estimated users who made the switch and stopped smoking, smoke-free products represent today almost one-quarter of our total net revenues.

As we are shifting our resources to replace cigarettes with smoke-free alternatives. We needed a technology that would enable us to adapt quickly to the new market dynamics.

Different leaders use terms very differently; for you, what is a digital twin?

A digital twin replicates the business conditions to test them and understand their impact. For us, it is a what-if simulator to test options. We use it to test and learn. For example, as we study the effect of Covid spending or the shift in consumer patterns, we can refine our network.

  • How much smoke-free product capacity does the company need to have?
  • For which product platforms? Where? And how fast?
  • What are the implications for our conventional products’ capacity?

The model needed to be robust: the focus is to include demand, product portfolio, machinery performance, trade rules, and taxation in the same model. We share the model in Figure 1.

Figure 1. The Philip Morris Digital Twin Model

Philip Morris Digital Twin Model

For you, what is an end-to-end supply chain?

We focus on our manufacturing processes and distributing our products to a market entry point. We avoid big buzz words. Let’s take some examples. A member of my team is a member of global sourcing. The person looks at alternative sourcing over ten years. In the past, sourcing was a manual activity. Now we go into the solution and click on Mexico. The model runs and quickly gives us the second level of costs. In the past, it took days. Now we simulate the options and output in hours. Our focus is long-term analysis for ten years. 

Tell me about your reporting structure and your work.

We report to the Operations leadership team.

When we joined this department 2.5 years ago, the analysis of ten years of data would take a month. With the investment in the digital twin, this has all changed.

How did you manage the project?

The process involved several steps, broken down into three main categories. The first focused on model development and data input. The second entailed the user interface and training. The third was deploying the new ways of working that we needed to deploy to ensure that the system remains operational, as shown in Figure 2. After three months of work with RiverLogic, the plan was live.

What did you learn?

Our initial learning was not to focus on the project as an implementation of an IT system but instead view it as a change management process. The definition of our digital twin project was system agnostic.

Secondly, we underestimated the data requirements. Data cleaning and data assessment took longer than we planned. Initially, we believed that data collection would take a couple of months. We were wrong: it took double the time.

To ensure data completeness and accuracy, we employed the data owner concept behind each of the 70+ data sets used in the model. We used variance reporting to highlight and correct any data inaccuracies. Once cleaned, the updated master data was often adjusted back at source to ensure accuracy for the upcoming use.

To ensure data completeness and accuracy, we employed the data owner concept behind each of the 70+ data sets used in the model. We used variance reporting to highlight and correct any data inaccuracies. Once cleaned, the updated master data was often adjusted back at source to ensure accuracy for the upcoming use.

System validation is critical. We tackled this issue quickly by building scenarios to build confidence. This validation took close to a month.

My final learning is change management. For me, it is in my nature. We should not be doing something for the sake of doing it. We don’t have one model a year now: our updates can be more frequent.

We chose to act like a start-up, unafraid of disrupting our processes. We had to completely abandon our old ways of working and “learn to unlearn, to learn again.” We’ve set about phasing-out traditional practices and over-hauling how we work, implementing the latest digital optimization technology.

How did you get funding?

We started by defining the need, and then we needed to go with the solution for the most value. The digital twin project was fun. It moved the team’s understanding closer to the markets and the consumer.

Business Impact?

To date, we’ve realized considerable benefits, including the identification of optimization opportunities, massive reduction in processing time, not to mention the ability to accurately navigate through a real-world scenario shaped by a global pandemic. In implementing this solution, we’ve demonstrated how multi-functional collaborative scenario planning processes combined with digital technology add value that transcends simple supply-chain management, impacting the business’s operational, financial, and strategic aspects. 

Summary

The Philip Morris team’s approach drove success. By tackling the project as a test and learn project focused on change management, the team gained confidence in the model which drove acceptance and value. If the team had approached this project as a technology implementation, the project would not have been as successful.

Preparing for the Supply Chain Insights Global Summit

We are taking the risk that everyone can get COVID shots/ tests to enable an in-person event in September. We will also have a virtual feed for those unable to travel. The goal of the conference is to Imagine the supply chain of the future. The conference is in Franklin, TN on September 7th-10th, 2021.

In preparation, I am handpicking the speakers and finishing up the Supply Chains to Admire analysis for 2021. The agenda will publish in April.

If you have a story you would like to share at the conference; please drop me an email at lora.cecere@supplychaininsights.com.
Please mark your calendars to join us to think differently and Imagine the Supply Chain of the Future.

In addition, we are heads down on research to share. Our current research project is understanding analytics. We would love to have your input on the study.

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