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Digital twin. Sounds quite sci-fi cool, doesn’t it? And in the world of business processes, it is seriously cool stuff.
The concept of the digital twin has been around in various forms for decades. In 2002 the term was first used in its current meaning by Michael Grieves at the University of Michigan. Since the explosion of the Internet of Things (IoT), artificial intelligence (AI), and machine learning in recent years, the technology for bringing the digital twin to the mainstream is coming into its own.
According to a report by Gartner, by 2020 50% of major enterprises will use digital twin technologies to optimize their business processes, cutting overhead costs and increasing efficiency. Process Mining is an indisputable part of this story and forms the foundation upon which a digital twin of an organization is built.
At a basic level, a digital twin is a digital representation of a physical object or process. The objective is to use this model to gain a better understanding of what’s working and what’s not, across your business structure, or to run “what-if” scenarios, letting you see the effects of changing one variable at a time, with no impact on current operations.
Digital twins have been in use in manufacturing for years, modeling new prototypes of products and monitoring the machinery used in that production. This allows production lines to operate more smoothly, end-product quality to increase, and machine downtime to decrease.
Benefits of a digital twin in any organization
When a digital twin is deployed in a non-manufacturing scenario, it’s referred to as a Digital Twin of an Organization (DTO). This indicates that the twin represents business processes and assets across the corporation, rather than a production line or specific output product.
One of the primary benefits in this situation is that multiple constituencies, both inside and outside the company, can use the data provided. Because they’re built out of pure data, digital twins can easily have multiple access points so each stakeholder can pull the pieces they need. This allows a company, for example, to give their operations team, auditing team, and sales team the specific access they need to gain insights into the processes relevant to their role.
Digital twin technology can be implemented across diverse areas to produce dramatic results, but they have proven particularly beneficial in manufacturing and in ecommerce.
Digital twins in manufacturing
The starting point for any digital twin project in this sector is to deploy sensors throughout the production line. These IoT-enabled sensors report back to the cloud-based digital twin software. This real-time reporting is what allows the technology to provide both initial modeling and continual monitoring of your production line.
The model building accomplished in this initial stage allows changes to be tested on the digital twin, before making changes to the line itself. This eliminates possibly costly damage or unnecessarily intrusive alterations to production machinery, not to mention eliminating unnecessary downtime.
Alongside this modeling ability, the monitoring features of digital twin software allow your technicians to be notified of maintenance issues before something breaks down and causes downtime on the line. Predictive maintenance is cheaper and less disruptive to production schedules, allowing the line to continue working efficiently.
Digital twins also allow for fast and easy prototyping of new products. Since you have a computerized model of your production facility, you can test new designs on the fly without interrupting current production. Then, once you have the product finalized, you only have to retool once and you’ll be back up and running at full speed.
This high-speed prototyping ability is what is allowing mass customization to come to the forefront of manufacturing. By modeling in your digital twin, you can set up your production line to be able to accept customizations to things like color, design, or even shape, to be added without increasing your costs.
An additional benefit to the real-time nature of digital twin monitoring is that as you make changes based on what you see in the digital twin, the model will update itself. This means that further recommendations made by the software’s AI will take into account the new, improved state of your systems, making further recommendations that allow for even better gains in productivity and quality.
Additional areas in manufacturing where digital twins can help:
- Optimize supply chains by modeling different distribution networks digitally first.
- Train new employees without downtime on the floor or risk to existing machinery.
- Model and test new plant processes or equipment without disrupting operations.
That last example is worth digging into a bit. By employing process mining software, you can quickly assess the as-is state of any of your business processes that involve IT systems. With the increasing use of AI, IoT, and machine learning in manufacturing, this increasingly applies to this sector. Once you have your baseline process map, you can employ your digital twin to model changes to these processes, without disrupting the real-world process.
Digital twins in ecommerce
Ecommerce companies have to be flexible and to pivot as market forces dictate. A DTO allows them to test these pivots before making the process changes on the ground. By taking the results of a process mining operation as inputs, the digital twin software can create and analyze outputs that mimic the real-world outcomes of each scenario.
Because there are simply so many processes involved in running an ecommerce business, this is an advanced level of deployment. A digital twin will have to include everything from customer databases, trouble ticket systems (internal IT as well as external customer service), inventory tracking, returns processing, network operations, and HR systems, for starters. Since daily business operations rely on all of these systems and how well they integrate with each other, the DTO will need to include all of these systems to be effective.
Once deployed, a DTO can allow you to model changes to your returns process (for example) to streamline the customer experience by combining data from those two systems. This same DTO may also let you quickly see if a network bottleneck is affecting your inventory tracking, so you can dispatch a technician to quickly remedy the situation.
Implementing a DTO in your ecommerce organization will also allow you to:
- Quickly communicate business process status and the impact of proposed changes to all involved stakeholders
- Identify bottlenecks and roadblocks, and then develop and test solutions before deploying in the real world
- Sync up strategy with operational execution
- Easily produce graphical representations of your existing business processes for use in board meetings, investor presentations, or marketing materials
Here at Minit, we’ve partnered with Mavim, a recognized leader in the digital transformation field, to bring the added power of digital twins to our customers. The combination of Minit’s process mining and Mavim’s digital twin technologies is paving the way forward for businesses of all sizes, across sectors and at every stage of the digital transformation process to lower their overhead costs and improve overall organizational efficiency.