Fast Forward to the Future with Digital Twins
Digital twin technology has the power to transform your business. Here’s how to get started.
By Krissy Johnsen and Izaiha Ellis
Visualize the future made possible by digital twin technology. Athletes of all kinds—both professional and recreational—have training regimens tailored to their own bodies, past injuries, and activities. Data is gathered for everyone in real time to predict not only the risk of injury, but the seriousness of the injury. Gone are the days of "one size fits all" training and recovery plans. Doctors, trainers, and athletes alike benefit from an enhanced view: the digital athlete.
Digital twin technology sparks a paradigm shift for individuals and organizations across industries. In healthcare, patients are tracked individually and monitored at the molecular level, not only giving accurate depictions of their current state, but also predicting individual changes over time. Disease response and treatment now rely on predictive modeling to establish efficacious and personalized treatment programs. With an ever-increasing store of healthcare data, epidemiologists can accurately predict macro health changes in communities and — in time — populations.
What is a digital twin?
A digital twin is a digital representation of a physical object, process, service, or system. In essence, the human body is a system of many objects, processes, and services all working constantly to keep us in motion.
Digital twins can be virtual replicas of objects in the physical world, such as engines, wind turbines, medical devices, or even supermarkets. The technology can be used to replicate processes, collect data to monitor efficiency, and even predict performance.
In summary, a digital twin uses real-world data to create simulations that can predict how something will statistically behave. This seemingly basic concept can be applied across industries in many ways, resulting in a tremendous impact.
Potential or reality? The answer is both.
Digital twin technology is expected to revolutionize how we interact with the physical world and will have disruptive effects across all industries. The examples below are just a taste of what’s happening now and what’s to come.
Future benefits in healthcare:
- Creating complex, personalized medical devices that are compatible with an individual’s unique anatomical and physiological systems.
- Accelerating the design and testing process of new medicines.
- Minimizing the need for human and/or animal testing.
What’s happening now?
Although big data and simulations have played a role in medical research for decades, recent applications of digital twin technologies represent a new level of maturity. Healthcare simulations usually don’t offer real-time, dynamic data. Digital twins on the other-hand, benefit from a two-way flow of data between the virtual and physical world. This allows scientists to study diseases from a much wider vantage point. An exciting illustration of how these capabilities can be applied is recent research on Virtual hearts. These virtual organs have the potential to drastically improve our understanding of heart diseases and refine treatment methods. Both Siemens Healthineers and EFops are two early pioneers of this technology.
Future benefits in retail:
- Optimizing inventory to anticipate bottlenecks, supply shortages, and demand curves.
- Improving margins for product-specific sales strategies, increasing targeting effectiveness for advertisements, and minimizing wasted cost on broader campaigns.
- Avoiding supply chain disruptions by allowing retailers to combine supply chain models with external, real-time data.
- Reducing brick-and-mortar costs and fueling ecommerce sales by creating personalized, virtual replacements for in-person shopping.
What’s happening now?
Traditional retail experiences are on the verge of massive transformation, as brick-and-mortar stores take to the metaverse while streamlining operations in their physical stores. For example, Kroger — one of the world’s largest food retailers — recently announced a partnership with Nvidia to create an AI lab that tests applications of digital twin technology. Kroger plans to use the technology to identify earlier when produce is losing freshness and use dynamic routing for last-mile delivery to ensure product quality. The retailer is also considering creating digital twins of brick-and-mortar stores based on data from IoT-enabled shelves and sales systems, enabling store managers to manage inventory and test the effectiveness of different store layouts virtually.
Four steps to get started
The benefits of digital twin technology are numerous, but there are some barriers to entry to consider, particularly when it comes to technology advancement and scoping. By following the four-step approach below, you can navigate your team toward new insights and the expanded opportunities presented by digital twin technology.
1. Identify the opportunities
Reassess how your position in the market (relative to competitors) might be improved with various levels of maturity in digital twin technology. While this assessment will vary by industry, below are a few simple questions to get started.
- Are any competitors leveraging this technology? If so, how? How mature are their capabilities?
- How might digital twin technology compound your company’s strengths?
- Can it be used to close opportunity gaps compared to competitors?
- What operational costs can be saved?
- What revenue channels might the technology unlock?
- What are the traditional pain points in your industry, and can this technology address it?
2. Define the future state
Regardless of your starting point, you can use the opportunities you’ve identified to develop a future state vision, define how your company can apply digital twin technology to deliver business value, and move toward specific outcomes.
3. Determine maturity level
After defining where you’re headed with your future state, you’ll need to assess the current state of your enterprise and determine your place in the digital twin maturity model. Review your current data acquisition and platform architecture, data quality, and overall data capabilities. Assess previous success levels using automation or machine learning. Examine the technology skillsets and resources within your company and identify gaps and assets to leverage. With clarity on your company’s starting point, you can determine the next step toward digital twin maturity.
- Level 1: Cloud-based data foundation
Digital twins are dependent on timely access to quality data. An important first step is to ensure relevant data meets quality standards and is supported with a cloud-based data foundation. - Level 2: Asset monitoring
Once relevant, quality data is available for all components of an asset or a process, this data must be consolidated into a real-time snapshot that allows stakeholders to visualize, access, and monitor operational data. - Level 3: Dynamic virtual model
Once all elements of an asset are consolidated, they must be linked together with a model that reflects how the various parts of the asset interact and are inter-connected in real-life. This model can also be further enriched by external or environmental data (like weather) to mirror the real-world object most accurately. This process results in a dynamic virtual model of the existing process or physical asset, which is an up to date “mirror” of the real thing. - Level 4: Scenario simulation
After successfully mirroring existing assets or processes, an AI learning model can be applied to run scenarios. Over time, the models collect information about how assets work together and can simulate scenarios virtually. - Level 5: Prescriptive and probabilistic solutions
With a highly -tuned capability for scenario simulation, your company can begin to add digital twin models trained to test options for achieving targeted business outcomes. These models can simultaneously run hundreds of thousands of scenarios, predicting the impact of hundreds of decisions at once, and determining the optimal course of action. Probability models can be stacked on top of digital twin models to enhance levels of certainty and decision-making confidence.
4. Build your roadmap
Take a look at the future state you’ve defined and compare it to where your company currently sits amongst the five levels of digital twin maturity. Estimate the investment required in people, processes, and technology to get you to your North Star. Develop a timeline-based roadmap that has a clear scope and includes ample investment in technology enhancements for an effective digital twin deployment. With a clear understanding of maturity and the lift it would take to help fully realize where you want to be, the roadmap can be used as a guiding light to help your company achieve its vision.
Applying digital twin technology represents real and quantifiable value for businesses — even more so for early adopters who start now and use it to gain a competitive advantage. To learn more about how to realize the power of digital twin technology for your business, let’s talk.
Slalom is a global consulting firm focused on strategy, technology, and business transformation. Learn more and reach out today.
