What is Predictive Simulation?
Today’s businesses are facing increasingly difficult and complex decisions. Markets are changing constantly, competition is fierce, and customers are demanding creative and technical innovation as well as high service levels. Add to this the rise of digitisation, the Internet of Things (IoT) and servitisation of products, businesses are being driven to explore new operating models that embrace connectivity, data analytics and evolving customer expectations.
Predictive simulation simplifies this complexity. By creating a predictive digital twin of your business model, the technology provides businesses with future state data, demystifying much of the analytical process by providing an interactive visual experience. This helps both analysts and business decision-makers understand their processes, data and how they affect one another and ultimately how change with affect their future.
Predictive simulation helps both analysts and decision-makers understand their business processes, data and how they affect one another.
New Data and Process Insight
Proponents of big data claim that all data must somehow be valuable. The reality is that most companies either don’t know what to do with their data, or are still working out what questions they need to ask of it.
The structured approach used by Lanner to create predictive digital twin (model) is in itself a powerful analytical methodology. We call this the Lanner Simulation Methodology™. It raises key process management questions to ensure that stakeholders understand the dynamic and interconnected nature of their business. This results in new insights into how processes are run, how policy is applied and highlights areas of particularly valuable yet missing data.
New Data and Process Foresight
Once a predictive model of the business process is created, businesses can ask ‘what-if?’ questions by changing the model and simulating scenarios. This allows them to understand the future impact and consequence of business change, without incurring any risk or cost. This foresight can prove invaluable to all business planning cycles, regardless if their horizons are measured in decades, months, days or hours.
The ability to test different options in a virtual world, prior to deciding which path to take, delivers powerful decision clarity across areas such as capital investments, resource planning, process design or even service policies. Simulation leads to smarter business decisions and drives higher return on investments.
Predictive Simulation – The Basics
Predictive simulation, using software, is the science of creating statistically accurate models to represent the behaviour of real life systems and processes.
There are different types of simulation modelling. Lanner specialises in Discrete Event Simulation techniques but also offers a range of other simulation approaches. Discrete Event Simulation (DES) works by modelling individual events that occur using a time-based engine, taking into account resources, constraints, and interaction with other events. This technique can easily reflect the process rules, randomness and variability that affects the behaviour of real life systems and complex operating environments. In this way, models can mirror complex, dynamic processes of real businesses, such as a manufacturing facility, a bank or an airport.
When to use Predictive Simulation
Processes that involve high connectivity, variability, disruptions and interaction complexity are ideal for simulation. Other techniques for measuring processes, such as Excel spreadsheets and Value Stream Maps, often ignore or treat these factors as static averages, with critical implications for decision-making. As companies become more digitally complex and connected with Industry 4.0, these implications can become game-changers.
Predictive simulation modelling provides compelling advantages over testing options in real life both in terms of cost, time and repeatability. This is particularly significant when variability, disruption and complexity exist. Imagine experimenting with ‘what if?’ options on a real production line, or within a functioning A&E unit. It would be impractical and possibly dangerous.
There are many examples showing how we at Lanner have contributed to process improvement. For example, we have helped design some of the world’s largest and most complex hospitals, for which design awards have been won.
Our service is flexible too. Lanner WITNESS can be used for general modelling, and can be extended into end-user applications. We regularly create problem-specific simulation assets for organisations needing to make frequent, repeatable decisions. These assets are designed to be user-friendly, configured for the correct data, and programmed with appropriate logic to explore the most relevant ‘what if’ questions.
For more information follow the link: www.lanner.com