In the previous blog post we looked at the concept of an Ecosystem Digital Twin and its necessity in articulating how the ecosystem works to regulators, investors, business partners and participants. Here we will look at how RegDefy as a methodology and tool allows you to do this. Continuing the model railway analogy, the tool is the rail infrastructure on which the trains run and the methodology is how you build it.
RegDefy: The Methodology
Knowing where to start a modelling a Digital Twin can be daunting: Which dimension do you start with? Do you start with Apps? or Processes? or Commitments? The RegDefy Methodology is an iterative approach which considers each dimension of the model to the level that is required for your stage in the journey. As an example you start with the supply chain diagram to tease out all the relevant organisations in the ecosystem, their products and services they offer each other, and their organisational capabilities. This is revisited in a subsequent iteration when considering Operational Resilience in the identification of Important Business Services (IBS); the capabilities becoming key to the mapping requirement of the regulation.
RegDefy: The Tool
When presented with an Digital Twin modelling problem the natural inclination is to start with a spreadsheet to keep track of the Processes, Offerings, Risks etc. Unfortunately, this rapidly grows becoming fragile and unwieldy; not only because many people need to contribute but also because of the many relationships between each of the dimensions. RegDefy takes care of both of these problems. As a SAAS it provides multi-user, role based access to a central store which manages the dimensions and the relationships between them preserving referential integrity.
RegDefy provides an out of the box solution to model your Ecosystem Digital Twin. However, it not only tracks the model but also meta information about the model. For example scheduling and prioritisation (which affects when each part of the model is going to be required) and rationales behind all the decisions that are made along the way. This meta information, along with the relationships between dimensions, help you determine whether parts of the model can be removed. For example answering “Do I still need this process?” is easier if you know the process is required for compliance with a particular clause or is essential for providing an IBS to a customer.
Once the model has reached sufficient maturity, extracts can be taken to satisfy the various stakeholders. This is safe in the knowledge that those extracts are fully consistent with each other.
Most operating model tools stop there. However, RegDefy allows you to use all that operational information to actually run the business. Two examples include Process and Risk Management.
Processes Management
Processes can be organised into runbooks that allow you to manage the cycles the ecosystem operates on i.e. daily, weekly, monthly, quarterly or yearly. For some of these processes it is critical that evidence is stored (i.e. you can demonstrate who performed it and what outputs were produced). Storing those next to the process definition makes for much more robust explanations later down the line.
Risk Management
Ideally, the first Line of Defence regularly collects Key Risk Indicators (KRIs); assesses the efficacy of the controls; and assesses the inherent and residual risks that the ecosystem is facing. This information is again stored next to the metric definitions, the risk registers, and the controls library.
Maintaining an Ecosystem Digital Twin requires the articulation of the model and its operation. RegDefy’s methodology and tool will accelerate getting you there.