Last summer, the Court’s headline read: ‘Fighting environmental crime groping in the dark’. It seems difficult to make the correct data available to combat environmental crime. As a result, the approach to environmental crime, ie. corporate environmental violations, not sufficiently. The Court therefore recommends that work be done to improve data quality and accessibility.
This was already expressed in the publication ‘An invisible problem’, where the Court of Auditors pointed out that one of the reasons for the extent of environmental crime and violations is poor data quality. There is not enough quality data available to tackle environmental crime in a good and unambiguous way. But why is good data quality so important for this? And how does data help you further reduce environmental crime? In this article, we provide an answer to this.
A lot of data is stored in the licensing, supervision and enforcement process (VTH). These are, for example, the company’s address, the activities carried out here and various categorisations. This includes the type of company according to the Executive Order on Activities and possibly the BOR category from the Executive Order on the Environmental Act. This information is often already known as soon as the permission is given. Later, these companies will also be supervised, which in turn will lead to new insights and thus new data. Especially when violations are identified, it is important that the data is stored correctly so that it can be included in new controls and any enforcement processes. As more checks take place at a company, the amount of data known about that company grows.
When data from a large number of companies are stored, analyzes can be performed. Another option for using this data is risk-oriented supervision. In risk-oriented supervision, companies that are known to have committed infringements are visited more often than companies that have not yet committed infringements. The Court’s report showed that a large proportion of infringements occur in a small group of companies (see image below). Therefore, in order to combat environmental crime, it is more efficient to spend more time on this small group of companies compared to the other companies. For example, new violations are more likely to be detected more quickly, and companies that commit violations are more likely to have better visibility. Companies that commit fewer infringements are visited less via the above method.
However, if the data quality and management are not in order, it is not possible to analyze what the risky companies are. For example, when audits cannot be properly related to business information, or if insufficient data is stored after an audit, it becomes very difficult to perform risk-oriented audits. Data quality therefore plays a crucial role here.
Look at the shortcomings
But how do you ensure that you make this quality improvement? To do this, the first thing to do is look at the shortcomings in the data area. For example, the Court mentions that data is often incomplete or incorrect in the systems. The systems used for this purpose (Inspectieview and JDS) are also ‘inadequate’, according to the Court. So there is still a lot of work to be done in that area! Here, the executive department, such as a municipality or environmental department, can also play an active role. It is important that within the service, clear agreements are made on the storage of data in the various work processes. In this way, the problem of lack of data and the problem of data quality can be largely solved. Part of this is the appointment of one or more responsible persons. Who is responsible for filling in the data? And who then sends it in when the quality is not sufficient? Making such agreements in the work process will lead to better data quality because people are more aware of their role in data usage and storage. Ultimately, it is the way in which the available knowledge and information is properly transferred within the service.
Do you have the basics? Then take the next step towards risk-oriented supervision
Once a good foundation has been laid for the storage and handling of the data, the next step can be taken in the direction of a risk-oriented supervision. This is the development of reports where the available data on companies are visualized. Such reports can provide insight into which companies are often found to have (serious) violations and which do not. By reading, filtering and sorting data, insight can be given into the risky companies, which can then be included in the choice of which companies are to be monitored more frequently. Ultimately, therefore, this information can be used for risk-oriented supervision. Dashboarding therefore plays a major role in the development of risk-oriented supervision within a service.
In short, in order to get started with the pain points from the Court’s investigations, a good basis for the storage and use of data is necessary. Only when this foundation is in place can one begin to develop reports that show information about which companies often find infringements. The above steps can eventually be used to start performing risk-oriented supervision. Addressing environmental crime using data and analysis is a major but also important challenge for environmental services and municipalities.
Immerse yourself in this theme:
Have you also become interested in the importance of data-driven work and dashboarding? Then come to the Masterclass ‘Data-driven work in the VTH domain’ on 11 May or 15 September 2022. The above theme is also discussed.