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Modelling Regulation
All regulations are the same?

How can you compare the issue of a TV licence to regulating care homes or environmental impacts of a major oil refinery? Clearly they are different domains but stripping away the domain, there are remarkable similarities.Similarities that are exploited by regulys for reducing burdens on both the regulator and regulated, and to inform those forming and monitoring policy.

Common underlying processes

Decomposing the processes that are undertaken to deliver a regulation shows that there is a large amount of overlap between regulations and organisations.So documenting processes in further regulations becomes progressively easier to the point when no new processes or services are needed to implement a new regulation.

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A “Rosetta Stone” for regulatory language?

By studying a range of regulations we have established a “domain specific language” - a set of concepts and relationships that exist in regulations but are called different things. For example, a chemical works company is called an “operator” and the owner of a reservoir is called an “undertaker”, but they mean the same things. The end result is a computer model for regulation.

So what?

By combining the processes and the model regulys produces software code. In the time it takes to drink a cup of coffee it can build a database and many of the services that are needed to administer the administration of the regulation. Minutes not months.

Ultimate re-use

This “model driven” approach can deliver for any regulation – if the regime has some new features then the model is amended to include them. Changes to already implemented regulations become quick and inexpensive.

Automation – saving time and effort

Regulatory processes can be manual or automated. Low risk activities can simply be licensed immediately by the system without any administration overhead. The same system can be used to gather monitoring requirements from all your activities – no data duplication and all from the same interface..