What’s a Rich Text element?
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
Static and dynamic content editing
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
- This is it.
With the widespread adoption of Digital Twins to optimise operations and enhance decision-making, an increasing number of large enterprises are setting their sights on harnessing the same advantages by creating Digital Twins for their Organisations (DTO). However, the journey to achieving these benefits is often fraught with challenges and slow progress.
In this blog, we will provide valuable insights into the background and advantages of Digital Twins, shed light on the common hurdles that impede their development, and showcase how Silico's Business Process Simulation (BPS) methodology can pave the way for unlocking the true value of DTOs. Through an iterative approach that involves building, connecting, and expanding Digital Twins over time, organisations can overcome the obstacles and embark on a transformative path towards operational excellence and resilience.
The Emergence and Value of Digital Twins
Digital Twins have become widely adopted in various industries as virtual replicas that mimic real-world systems. They serve as valuable tools for monitoring and simulating physical assets, such as manufacturing equipment, in real time.
Let's use the example of a jet engine to look at the three elements of a Digital Twin in further detail: (1) data that feeds into (2) virtual models to (3) generate insights and value through decision support. Data is continuously collected through sensors during the engine's operation and integrated into the Digital Twin to synchronise it. This data can be visualised to monitor the engine's current state, and the virtual model can forecast and predict the engine's future performance.
By acting upon the performance forecast provided by the Digital Twin, companies can unlock significant value, for example, through predictive maintenance. When the Digital Twin alerts the company to potential deterioration and future repair requirements, it can proactively plan and initiate maintenance processes. This planned and orderly approach minimises disruptive repairs. Companies can ensure that a replacement aircraft is available, leading to uninterrupted revenue generation, improved customer satisfaction, and the prevention of cascading effects on flight schedules. Moreover, companies can avoid the costs of sending replacement parts and staff to remote locations and instead maintain the aircraft in their regular hub.
Considering the benefits of Digital Twins and the increasing digitisation of equipment and machinery, it becomes evident that utilising the collected data to derive forward-looking insights is a logical and advantageous choice.
Applying the Concept to Digital Twins of the Organisation
A Digital Twin of the Organisation takes the principles of Digital Twins and applies them to entire organisations. While a Digital Twin of a physical asset mirrors a specific object, a DTO aims to replicate an entire enterprise in a virtual, software-based representation. This scope necessitates adjustments to the three elements of a Digital Twin:
- Data Integration: Instead of sourcing data from IoT sensors, a DTO collects data from enterprise IT systems, such as ERP or CRM systems. These systems serve as the primary data sources for the DTO, providing information about different aspects of the organisation's operations.
- Virtual Model: Unlike statistical models based on data, a DTO's model should accurately reflect what is happening throughout the organisation. The model needs to encompass the interrelationships between different departments, processes, assets, and the overall environment in which the organisation operates.
- Decision Support: Rather than focusing on monitoring and predictive maintenance of a specific piece of equipment, a DTO enables the monitoring and analysis of the organisation's assets, processes, and environment. This comprehensive approach allows for forecasting and testing decisions before implementing them in the real world, providing valuable insights and enhancing decision-making processes.
A DTO provides an invaluable single source of truth for monitoring the organisation, enabling more accurate forecasts, bolstering scenario planning, and improving decision resilience and alignment throughout the organisation. The applications of DTOs span various domains, including performance and cost optimisation, enhancing customer experience, driving business transformation, achieving operational excellence, and optimising logistics and manufacturing.
By embracing the concept of DTOs, organisations can gain deeper insights, drive informed decision-making, and achieve greater operational efficiency across their entire enterprise.
Why you don’t have a Digital Twin of the Organisation yet
Although a DTO holds immense value for large enterprises, many organisations have yet to develop even parts of their DTOs. This missed opportunity can be attributed to several key factors. At Silico, we have identified three primary reasons for this hesitation:
1. Siloed Data: Models and data reside in various tools such as ERP systems, CRMs, data warehouses, and spreadsheets. They are often maintained within separate organisational silos. This fragmentation makes integrating and synchronising the data required to build a comprehensive DTO challenging.
2. Limitations of Tools: Existing tools cannot develop the virtual model that serves as the foundation for a DTO in an iterative manner and scale up to simulate the entire enterprise, hindering the effective implementation of a DTO.
3. Backward-Looking Decision-Making: Many parts of the organisation rely on historical data to generate forward-looking decisions, considering it sufficient. This approach fails to leverage the benefits of real-time and predictive insights provided by a DTO, impeding its adoption.
For organisations implementing a DTO, starting small and gradually scaling up the Digital Twin is widely recommended. This is the core of Silico's Business Process Simulation methodology to enable the Digital Twin of the Organisation: Rapidly developing valuable Digital Twins of individual processes and connecting them over time to create a full DTO.
Rapid development of Process Twins
Embarking on a project to create a Digital Twin of an entire large enterprise can be perceived as risky, time-consuming, and costly. During a long project, stakeholders and sponsors may lose interest and patience before completion. To address this challenge, it is crucial to showcase the concept and usefulness of a Digital Twin rapidly by focusing on smaller-scale implementations. Silico's BPS methodology enables the iterative development of Digital Twins for individual processes, minimising costs, time, and effort to get to value.
Silico's BPS methodology can generate a Digital Twin of a specific process within four weeks. We utilise our advanced yet user-friendly technology platform and build on your existing process assets, such as process maps, process mining data, discussions with your team, business intelligence tools, and spreadsheets.
By following this streamlined and expedited development process, Silico's BPS methodology guarantees that your Digital Twin initiative remains on track and delivers value quickly. This approach helps maintain stakeholder interest, support, and engagement throughout the journey, ultimately showcasing the tangible benefits and paving the way for further expansion and integration of the DTO within your organisation.
These rapidly-developed Process Twins are incredibly valuable. They allow transformation teams to iterate through the DMAIC cycle in minutes rather than months. They allow improvement specialists to stress-test processes and identify issues before they affect the business. Teams can then redesign the process virtually to test potential improvements and maximise the ROI of their changes. Process owners and operations can also use the Digital Twin of the process to optimise, for example, capacity and inventory management.
Connecting and expanding Process Twins
However, a collection of Process Twins falls short of fully realising the vision of a DTO that captures the complexity and interconnectedness of your entire enterprise. To achieve this, expanding and connecting the individual Digital Twins is essential to unlock synergistic effects with additional value.
For instance, consider expanding an existing Order-to-Cash Twin by connecting it to a Lead-to-Order Twin. Each individual Digital Twin already provides valuable insights for their respective process. However, additional transformative impact occurs when the two processes are interconnected. This integration enables enhanced forecasting of new orders, improved capacity management within the Order-to-Cash process, and more resilient decision-making by avoiding shifting bottlenecks and backlogs from the Lead-to-Order to the Order-to-Cash process. An example of these connected Digital Twins and potential use cases they unlock is provided in the picture below.
Silico's flexible Digital Twin platform catalyses expanding and connecting these Digital Twins. With our platform, the seamless integration and interlinking of multiple Digital Twins become feasible. This allows for a comprehensive representation of the organisation's processes, assets, and interdependencies, providing a holistic understanding of how various components interact and impact each other.
Start using Business Process Simulation to build your Digital Twin of the Organisation incrementally
By leveraging Silico's capabilities, organisations can unlock the full potential of a DTO. Large enterprises can avoid the risks of large, long, and costly Digital Twin projects that are bound to fail and leave stakeholders dissatisfied. Using Silico, your company can rapidly build valuable Digital Twins of individual processes and expand, connect, and scale them over time to develop an entire DTO. Start unlocking data-driven decisions, optimised processes, and continuous organisational improvements at speed and with scalability.