Digital Twins Will Aid Digital Transformation In 2020

IBA Group
Mark Hillary

I wrote recently on this blog about the use of SAP to create Digital Twins, a digital representation of a real system so it can be more easily monitored and controlled. As I mentioned earlier, this has been a common practice in aviation for several years. Engine manufacturers will always maintain a digital version of every engine they sell and ensure that the digital version is updated in real-time using sensors on the real engine.

In aviation the advantage of doing this is obvious – it allows for more efficient maintenance and safety procedures when the digital engine allows engineers to monitor real engines remotely. But I believe that the launch of SAP’s Leonardo system last year will really start accelerating the use of Digital Twins as a common business strategy.

It is a combination of technologies and strategies that are creating this possibility, but the three important ones are:

1. The Internet of Things (IoT); as the real world fills with sensors and connectivity as standard for almost every electronic device we will reach a point where systems such as a Digital Twin are essential just to stay on top of what is connected and what information it is reporting. In the home, this may only be devices such as a Kindle, iPad, Echo, phone, lightbulbs, or heating thermostat, but in the industrial environment it can easily be more complex and difficult to control.

2. Artificial Intelligence (AI); with so much data being created constantly by sensors we will need to apply AI principles to the data just to make sense of it all. For example, if your home thermostat detects patterns in the way that you prefer your home to be heated then it should be able to anticipate what you want before you change the settings.

3. Machine Learning (ML); the ability to look at every action and outcome by every sensor inside a network will allow the system to learn about the ideal outcomes and then to suggest recommendations in future based on earlier learning.

It is really the IoT that is at the heart of this development. Imagine the complexity of a modern industrial facility – a large brewery or car factory for example. Across the entire property will be doors, windows, pumps, and various robots that all need to be coordinated. Most companies with these facilities will already have some sort of control mechanism, but the Digital Twin makes an assumption that every component (pump, door, assembly-line robot) has in-built sensors. By taking a feed from all of these sensors we can build a complete virtual mirror of the plant.

The IoT facilitates this by ensuring that the real-time sensor data is available, then the AI system goes to work on spotting potential problems or just process flows that are unusual and alerting workers to places they need to check.

I have seen this type of system deployed for an office management system where every light, heater, door, and window is modelled in the system. I believe that we will see the Digital Twin concept growing much faster as companies find that they can create enormous efficiencies by improving what they do and spotting problems before they happen.

As Forbes magazine recently suggested, it will soon be impossible to plan any kind of digital transformation for your business without creating a digital twin first. The processes will be simply too complex for any one manager to understand from start to end. Not only do you need to map out all the existing components, you need to apply AI to oversee how the entire system is working.

Without these deep insights into the way your business functions at present any transformation plans will be impossible. Digital Twins are not just for those obsessed with being able to manage their existing IoT infrastructure, they are becoming an essential tool for managers who want to see how the future of their business might look.

Digital twins will aid digital transformation in 2020

Business Application Support With Artificial Intelligence

IBA Group
Mark Hillary

I mentioned in my last blog that the very nature of jobs and employment is changing today because of emerging technologies such as Artificial Intelligence (AI). Tools such as AI in business application support, are fundamentally changing how corporate processes function – and this changes the skills that people in professional jobs need. This change is prevalent throughout many parts of the modern organisational structure, but the most important area of change is probably enterprise decision support.

The problem is, how do we get from here to there? Many organisations are overrun with data. They have so much that they just don’t know what to do with it all. Some have tried to focus on data analysis, creating a data-driven approach to their business, but even those who have moved in this direction need to rely on the skills of their data scientists to try turning data into information.

As data analytics evolved, it was clear that enterprises were changing from a backwards-facing approach where they analysed past events and described what happened, to an ability to be predictive – trends and patterns that help to predict future behaviour could be found. A similar change needs to take place in enterprises using AI today.

Today, the possibilities for AI-enabled decision-making are more prescriptive, with AI providing enterprises not just a look into the future, but also key diagnostics and suggestions on potential decision options and their payoffs. Such highly evolved applications of AI can help businesses make decisions that can potentially exploit more business opportunities, while averting potential threats much earlier.

This is the real opportunity for AI in the enterprise. To create the opportunity for automated decision-making, but where the system is designed to learn, unlearn, and relearn as often as required. Insights from automated AI business application support should be powerful because the system is trained to learn where insights may be found.

I believe we will be seeing many more AI business application support systems in future – its no longer a technology of the future. These are systems that are already installed and in use in enterprises globally – have you explored what AI can do for you and your decision-making processes?