Digital supply chain twin: use cases and benefits

How to stress-test supply chain resilience

Digital Twin

What is a Digital Twin?

In the last 10 months, their CEOs asked many supply chain executives: “Are our global supply chains resilient?”. Is a Digital Supply Chain Twin the answer to this?

After entering Gartner’s Hype Cycle of Emerging Technologies in 2017, the “Digital Twin” is back in focus in 2020, and the interest has been continuously rising. So, what is “Digital Twin” - similar to the physical twins like the replica of the Apollo capsule that stayed on earth during the mission, the digital twin’s purpose comprises forecasting, analysis, and risk management. The digital twin is a virtual image of a real object, which can be a single component or a whole system and ideally has a live connection to the real object. Now, optimization and simulation can be applied to this virtual image.

The digital twin's relevance becomes even more apparent when you look at the definition of Industry 4.0. The main component of Industry 4.0 – the cyber-physical systems – connects all people, objects, and systems of the value chain in real-time to enable an autonomously optimized production and distribution network. Sounds pretty similar, right? We dare to say that digital twins are a prerequisite of Industry 4.0 and, thus, an obligatory step on the way to tomorrow’s supply chains.

Why a Digital Twin for Supply Chains?

Digital Supply Chain Twins mirror the whole supply chain while achieving a sufficient level of detail in warehouse or production facilities. However, it is lower compared to the one achieved by Digital Twins of single products or production lines such as the General Electric D11 steam turbine Digital Twin that comprises the complete 3D-structure of the turbine, including sensor data.

German retailer dm-drogerie markt selling cosmetics, healthcare, household products, and health food via more than 3700 stores in twelve European countries, yielding 11.2 billion Euros sales, recently won the German Logistics prize 2020 with their Digital Supply Chain Twin. For their new logistics hub near Berlin, dm created Digital Twins of 2000 assigned stores, including the detailed shelf placement and SKU locations. This real-time data enabled dmto optimize the new logistics hub processes, ranging from de-palletizing to pick & pack while optimizing the mixed pallet for efficient restocking at each store. In addition, employees at the stores were equipped with smartphones that led through the store on the optimal “restocking path.”

Motivation

Nearly all companies globally were impacted in some way during the first Covid-19 lock-down during spring 2020. Some companies felt disruptions on the demand side (retailers, shops, etc.), others on the supply side (automotive suppliers, chemical manufacturer, etc.), and many on both angles. As a result, we received a lot of requests to do stress-tests of existing supply chains.

Customer case

“How to stress-test your Supply Chain when disrupted by Corona pandemic” - example of a life sciences supply chain

One urgent customer request came from a globally operating biopharmaceutical company. This enterprise sources API (Active Pharmaceutical Ingredient) primarily from China, where Covid-19 impact was high at the start of the year. So, we were asked to stress-test their supply chain capabilities with regards to supply chain resilience.

We took a representative range of product brands produced and sold by the life sciences company for that purpose.

The client network modeled in the Digital Twin contains the following nodes:

  • 8 manufacturing sites (including 4 Contract Manufacturing Organization sites; based in Europe and Asia)
  • 38 global distribution centers
  • 41 markets/affiliates

The manufacturing network of the company contains two stages:

  • Bulk operations (sourcing API from China) can be done in-house or via an external contract manufacturer
  • Packaging (primary and secondary) operations can also be done inhouse (in Europe and USA) or via an external contract manufacturer

The finished packaged goods are directly shipped to local distribution centers and warehouses.

Disruption scenarios

To provide a robust and holistic assessment of the client’s supply chain resilience of the company, four key scenarios were defined:

Baseline

This scenario focuses on evaluating the initial setup of the respective supply chain containing all distribution and manufacturing stages. As a result, potential optimization areas (e.g., decoupling points, inventory right-sizing) can already be detected.

API site shutdown

This scenario shows the impact of a strategic manufacturing site's shutdown for supplying the key input material API. Within this scenario, the length of the shutdown can be simulated. The Digital Twin highlights the impact of downstream operations (bulk manufacturing and packaging performed in Europe and the USA). In conclusion, this scenario pinpoints when certain markets cannot be delivered any longer with finished packed goods and the financial impact of lost sales.

2nd API source

This scenario simulates one mid-term countermeasure to minimize API supply disruptions. Introducing a second complementary API supplier into the sourcing network shows the impact when one API supplier has a site shutdown and extends the second supplier to compensate for this shortage.

Logistics services shortage

This scenario illustrates the effect of a limitation of transportation capabilities to ship the finished goods from the packaging sites in Europe to the receiving European markets. This specific case has become more relevant in December 2020 as global distribution capacities (in particular shipping) have become shorter and shorter.

Impacts of the disruptions

Compared to the client’s baseline scenario

  • The API site shutdown reduces customer service-level by 8% points. Due to the inventory buffers for the API and bulk products, finished goods inventories are affected and delayed, as shown in the, e.g., in Figure below of a sample product’s simulated stock history.
  • Having a second source available helps counter the disruptive event and regular demand peaks that overload the supply chain. This is reflected in a service-level increase of 2% points compared to the baseline or 10% compared to the shutdown scenario.
Inventory of a sample product affected by the API shortage
Inventory of a sample product affected by the API shortage

Conclusions

The client’s Digital Supply Chain Twin builds the basis for many different analyses ranging from inventory right-sizing to strategic issues such as second sourcing. In the presented customer case, we found that the service-level significantly decreases depending on the disruption length and existing inventory buffers. A second source will benefit the service-level in the supply chain with or without disruptive events and help our case.

How to stress-test your Supply Chain

A Digital Twin is an ideal way to simulate the disruptions we have been facing in many enterprise supply-chains in the last 10 months.

A Digital Supply Chain Twin can be set up within two to four weeks without impacting your operational planning and execution environment managed in APS and ERP systems.

The beauty of a Digital Twin is that it easily simulates multiple scenarios and helps derive tactical and strategic decisions (like introducing alternative suppliers or introducing another production line). As another benefit, comprehensive business cases for investment decisions can be built on Digital Twin results.

Please reach out to our supply chain experts to find out more about the benefits of Digital Twins.

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Patrick Wolf

written by

Patrick Wolf

Partner

Prof. Dr. Robert Grüter

Robert Grüter

Professor for Logistics and Supply Chain Management

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