Case Study
Request a quote
Back to Blog
30 August 2021

Why Accenture Lists ‘Digital Twins’ in Top-Five Technology Trends in 2021

Accenture lists' digital twins'

Accenture lists’ digital twins’ in its top technology trends for 2021. It should come as no surprise that ‘digital twins’ are on that list. 

Digital twins allow companies to see how a new product will perform before releasing it to market by modeling it digitally with all its components, in days instead of months or years.  

By giving them the ability to test products virtually before releasing them to market, digital twins have reduced costly mistakes and increased revenues exponentially for numerous industries, including aerospace, manufacturing, and oil & gas production!

“Digital transformation” is the new way of thinking about coordinating product lifecycle management.  Recent advancement in data integration, AI and IoT has extended digital benefits into physical products. 

As mentioned by Accenture Technology Labs Managing director Michael Blitz, business owners acknowledge the benefits and embrace them across multiple departments. 

Accenture lists’ digital twins as one of the top five technology trends in 2021 because organizations have begun to figure out how to take advantage of the benefits of digital twins in terms of efficiency and convenience at scale.

Unilever sets up 8 Digital Twins in its Consumer Goods Factories: 

Unilever used an outdated control system for its machines, which can only provide essential monitoring of a machine’s performance, capabilities, and history of operation. The new digital twinning solution in Unilever factories will analyze their data in real-time to predict future issues with maximum accuracy. 

It provides them with greater transparency into how each piece of equipment works within the factory and consequently allows them to have better planning regarding maintenance needs. 

Unilever hopes that this transformation will help it double profits while simultaneously reducing operational costs through improved workforce productivity rates and increasing revenue from existing assets rather than investing in new facilities or services. 

Accenture lists' digital twins'

What Challenges do Enterprises face while using Digital Twins

Although the digital models themselves are becoming more advanced, sharing these creations across applications is still trickier.

PLM vendors optimize different types of applications for specific use cases. As a result, PLM vendors like Siemens have been buying up and building rich ecosystems that facilitate the exchange of digital twin data across product lifecycles.

Read more: What is Digital Twin Technology, and Why is It Essential for Businesses?

Passing digital twin models is difficult when enterprises buy tools from one vendor. In addition, the lack of integration between apps across different vendors makes the task more challenging.

Various standards groups have been working to help streamline this process. For example, the International Standards Organization has been developing multiple standards for digital twin manufacturing, reducing data loss during exchanges, and promoting business collaboration.

Michael Finocchiaro, a senior technologist at digital transformation consultancy Percall Group, said:

“Without practical implementations from industry leaders like Dassault’s 3DEXPERIENCE, PTC Windchill, and Siemens Teamcenter–it will be difficult for brands in various industries such as automotive manufacturing and oil & gas to take full advantage of their new capabilities.”

But the jury is still out on how committed vendors are to ensuring interoperability in practice. For example, Finocchiaro said that integrating bill-of-material data across platforms often requires extensive customization despite standards.”

Evaluation of this statement would be complete only after an impartial and independent research organization conducted a comprehensive survey with no bias towards any particular vendor or product line. 

Nevertheless, the results from such a study could shed light on whether there truly exists widespread commitment among suppliers toward achieving true cross-platform compatibility and what specific factors lead certain companies down different paths when implementing their unique design strategies.

Despite the rhetoric of openness from companies like Apple, Amazon, and Google when it comes to their customer base, digital twins are expected to put a bit of drag into standards adoption. However, digital twin integration is vital so that stakeholders who work on these platforms can better communicate how they should function in practice.

Industry collaborations like the Object Management Group’s (OMG) Digital Twin Consortium could help. Digital Twin Consortium CTO Dan Isaacs said, “While there is a lot more work to be done to enable digital twin interoperability, integration and standards that can support sharing, and common practices will provide a foundation.”

The group focuses on creating consistency in digital twin technology’s vocabulary, architecture, security, and interoperability. It does not develop standards directly but instead helps the different participants flesh out the requirements that will inform measures by organizations like ISO, the IEC, and the OMG.

The Digital Twin Consortium partners with an open-source community called FIWARE. The community curates digital twin reference components for smart cities, industry, agriculture, and energy. This partnership could make it easier to connect multiple digital twins to model city infrastructure or help businesses become more efficient by better understanding their processes.

Digital transformation is still in early adoption, but it’s gaining momentum. Seamless integration and best practices across software and hardware are needed to realize this full potential. Digital twin would need coordination of various technologies like AI/ML, modeling & simulation, IoT frameworks to reach their full potential, including industry-specific data protocols.

For example, these efforts involve using satellite imagery and point cloud scanning coupled with AI and ML to identify structures and anomalies tagged or associated with other assets or attributes. As a result, it helps enterprise teams improve pattern identification, giving them a competitive edge over others in their industry.

Isaac believes that the energy and utility sector will see significant adoption of digital twin technology due to its ability to accelerate the renewable transition. Challenges, however, exist in other industries like the medical industry due to harmonizing systems with different protocols.

To gain a competitive advantage, companies should build intelligent twin models of their products and structures. Accenture’s Technology Vision 2021 predicts that businesses that start building these twins now will be the ones pushing industries towards an agile future.

Four Technological Growths to Watch Out in 2021:  

In addition to digital twins, other technologies will continue to grow in 2021, including augmented reality (AR), Blockchain technology, and deep learning/artificial intelligence (AI). All three of these have already made waves throughout many industries, but as Accenture predicts, they will only get bigger over time. 

For example, industries use AR for training purposes, such as flight simulators that allow trainees or employees to practice their skills before deploying on actual missions or tasks. Not only does this save lives, but it’s also very cost-efficient because mistakes can happen while practicing. As a result, most companies don’t need to spend as much money on training instead of when it matters. 

Blockchain can track the movement of goods, whether physical or digital, like software uploaded onto a website. 

Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?

It increases transparency and makes it easier for users to see where their products come from – which can be especially important in specific industries such as food safety (think about how many people get sick every year because there was something wrong with the food they ate). 

In addition, since Blockchain records events in ‘blocks’ that cannot be changed once set, this technology prevents fraud and protects businesses and consumers alike. 

Finally, deep learning/artificial intelligence uses big data sets to perform tasks more accurately than humans would do alone by recognizing patterns within those data sets. 

For example, this technology increases accuracy in medical diagnoses, self-driving cars (which are already on the market), and various other industries where there’s a heavy reliance on data analysis, such as financial investment firms.

In 2021 we will continue to see these big four technologies become more integrated into our everyday lives.  

Accenture lists' digital twins'

Early Digital Twin Users will lead the Corporate Future: 

The US Air Force can be a great example to highlight a successful use case of the digital twin. The US Air Force has reduced the prototyping period of aircraft from decades to a few years. 

Chevron, an energy corporation, has claimed that the company can save millions of dollars by predicting failures and maintenance problems using digital twins. Companies like Chevron have already seen these great returns on their investments, so we’ll likely see more of them in the future. 

Accenture’s prediction on Digital Twin in 2021,  is not surprising because the benefits are tremendous: imagine how much money companies can save by knowing about failures before they happen and prevent them from happening altogether? 

There is no doubt that the digital twin is delivering on its promises. It has become an excellent asset for businesses as it is improving collaboration and workflows across different departments design, sales, and maintenance teams and engineering. 

Traditional processes have led to process and communication gaps that cause delayed product launches, lack of efficiency, and a high cost.

Digital twins will also allow companies to show consumers how their products work before they are released.