3 Digital Twins myths debunked
From Skepticism to Necessity: How Digital Twins Are Following in the Footsteps of Cars, Telephones, and Credit Cards
"We are not a fancy company like Amazon to use digital twins for our omnichannel fulfillment needs."
"We are doing good with what we have, so why fix something that's not broken?"
"It is such an advanced concept that even if we set up one, we will never put it to use. So why bother? "
These are the top 3 excuses I have heard when someone hires me to consult in their digital transformation journey. I empathize with them.
It reminds me of my first KitchenAid mixer. I love baked goods and had vowed to learn baking. After 2 weeks of staring at the KitchenAid box, I realized baking was too cumbersome, so I returned the pretty pastel pink mixer.
After all, who would want to buy an expensive system if they didn't know how to use it?
Here is my attempt to debunk these myths.
As a bonus, I reveal how I manage my craving for baked goods.
Myth 1:- Digital twins are the perfect solution for e-commerce giants like Amazon and Walmart.
Digital twins are often seen as ideal for e-commerce giants like Amazon and Walmart. While larger organizations must innovate to stay profitable, the innovation is delayed by the complexity of their supply chain networks. But that's not the case with smaller companies. Consider a regional grocery chain with five stores aiming to optimize omnichannel fulfillment without stockouts. With simpler supply chain networks, they can experiment with digital twins incrementally and achieve results faster in frequent iterations. Smaller organizations can see more pronounced benefits, optimizing operations, reducing costs, and quickly enhancing customer experiences with real-time data and insights.
Implementing digital twins is now more accessible, with scalable solutions for various budgets and skill levels. It's not about the size of your company but leveraging technology to stay competitive and drive growth. Investing in digital twins levels the playing field, enabling data-driven decisions and improved supply chain efficiency without massive resources.
Myth 2: "We already have a data analytics platform with AI. We don't want to divest out of my current systems. Wouldn't it be redundant to have a DT ?"
Short answer: A DT would be a centralized repository that integrates data from all your current systems—both hardware systems like automated guided vehicles in your warehouses, RFID, electronic shelf labels, etc., and information systems like pricing, inventory, and Point Of Sale etc offering a comprehensive, real-time view of your supply chain. While traditional analytics platforms analyze historical data, DTs allow you to simulate and optimize future scenarios. So it is not redundant.
Calling digital twins an AI-based analytics platform is like saying a supercomputer is just a calculator. It’s reductive.
Digital twins provide a dynamic, real-time virtual representation of physical assets and processes, offering predictive insights and proactive decision-making capabilities that traditional analytics platforms cannot match.
Limiting digital twins to just sensors, simulators, or AI applications overlooks their full potential. Digital twins are a comprehensive technology comprising various components that can grow with the addition of enablers like cloud computing, edge computing, 3D modeling, visualization, and augmented reality. Effective implementation of digital twins demands a commitment to data availability, granularity, and harmonization with core supply chain functions they want to mimic, which KPIs need improvement, and what analytical capabilities and data sources are currently available.
Myth 3: It sounds too futuristic and can take years to build a DT for my supply chain workflows.
Building a DT doesn't mean you must create a complete digital replica of your entire supply chain at once. Start small by focusing on an area like inventory management or logistics. Identify the key pain points you want to address and prioritize them. This incremental approach will help you achieve quick wins while working towards a more comprehensive DT. They can also help identify potential risks and opportunities within the supply chain, enabling proactive decision-making. Organizations can test strategies and optimize their operations by simulating different scenarios without disrupting their supply chain. This proactive approach reduces the likelihood of errors, saves time, and increases overall efficiency.
P.S.: I indulge in my neighborhood French bakery every 3 weeks. It's working well so far, and there's no messy kitchen to clean up!