Today almost all enterprises use digital technology in some way or another. But the development of true “digital enterprises”, where digital technology lies at the heart of how the business operates, generates revenue, seizes competitive advantage and produces value, is now an increasingly ubiquitous and disruptive feature of Industry 4.0.
Advancing technology means that information has become the most lucrative asset a business can own. To generate and leverage such information, digital enterprises must deploy new tools, communities, ecosystems and technology platforms that enable rapid information sharing. Such a transformation can then be used to gain a competitive edge and boost productivity through automation, analytics, machine learning and self-healing.
Paul Haimes, a senior vice president at Boston-based computer software and services company PTC, believes that enterprises derive the biggest benefit from digital transformation through enhanced analytics and responsiveness.
“Data can already be collected that enables better decision making, but the real value comes when you start to drive an analytical model that allows the business to react to situations in a more efficient and agile way.”
For Dan Hushon, chief technology officer at Virginia-based ITC services company DXC Technology,
“We are now experiencing a second wave of digital disruption (the first being the internet). Analytics, coupled with The Cloud and apps, will usher in unprecedented levels of productivity that could make or break firms that choose to transform.”
Digital twinning, the simulation of a physical asset on a digital platform, is one of the latest technologies to emerge from Industry 4.0. It uses data from sensors embedded into such assets to analyse efficiency, condition and real-time status. According to a recent report by market research firm Orbis Research, up to 85% of all IoT platforms will feature some form of digital twinning by 2022.
Computer gamers are accustomed to creating avatars of themselves within video games, which then react to inputs from the real world. A digital twin operates in much same way, existing in a fully functioning way in its own virtual environment. By inputting data, the twin can be tested, generating outputs that can then be used to guide decision making and refine or revolutionize processes.
For most enterprises, the use of digital twinning begins by using metadata to help model time, flow, participants, values and other highly complex, dynamic variables. Digital twin simulations can help enterprises generate ‘what if’ scenarios to test new products and services, accelerate time to market, and increase productivity, explains DXC Technology’s Hushon:
“Most frequently, this so-called ‘atoms to bits’ replication enables the cross-linking of important data with many more dimensions than can be reasoned by people. Digital twinning enables hyperdimensional information correlations that wouldn’t otherwise be possible, because there are simply too many factors for the human brain to consider.”
Going forward, artificial intelligence (AI) will play an increasingly important role in the functioning of the digital enterprise. With AI technology still in its infancy, there are many business areas where AI solutions aren’t yet applicable, or the information and knowledge required for leveraging AI still aren’t available. As enterprises progress digitally, however, opportunities for increasingly sophisticated AI-based solutions to deliver value are burgeoning.
Jim Newman is senior director for asset performance marketing programs at software development company Bentley Systems. For him,
“Applications for AI in the digital enterprise environment are already broad. These range from using image and advanced object recognition to automatically classify objects in a 3D model, to moving from reactive and proactive reliability towards true predictive resilience and reliability projections.”
Digital enterprises need to understand that AI-based solutions in their current form typically represent very narrow intelligence, trained to do one specific task. We are now seeing AI enhance clinical advisement and operations in healthcare; improve manufacturing inventory management; and improve regulatory compliance and risk assessment in the banking industry.
“When it comes to AI, think small and the little things will add up to increased productivity and human creativity,” says Newman. “Machine learning is only starting to deliver real value, but over the next few years applications will rapidly multiply as digital enterprises find the right problems to attack.”