SMIS provides the rail industry with a rich evidence base that it draws on to better understand risk and take safety-related decisions. It is developing a similar evidence base to improve health and wellbeing. Many risk management activities, models and tools draw on information from the system.
The new SMIS went live in 2017, replacing a system that was first built in the late 1990s. RSSB, steered by its members in industry, continues to improve SMIS to make it easier to use and to get more value from the information in it.
SMIS Business Intelligence Designed for Company Reports and Analysis
RSSB provides all members access to SMIS data via Jaspersoft which is used to query, design and schedule reports using data held in the SMIS data warehouse. It cannot change any of the data held there.
Jaspersoft can be used to pull ad-hoc data on a topic of interest. For example, all incidents that have happened at a particular location, or all company workforce injuries in a given period.
This is done by selecting the most appropriate data domain, applying the relevant filters, and specifying the required fields. This can be done either as a table of events or as a count of relevant events per unit of time. These outputs can then be turned into charts to include in safety performance reports.
For regular reporting, once it has been designed, a report can be scheduled to run automatically. For example, every four weeks or every month for KPI reporting.
We have unlimited accounts in Jaspersoft, and access can be given to members who do not input to SMIS, to see the resulting business intelligence. To request additional accounts please raise a ticket in the Industry System Service Desk.
In addition, RSSB can prepare bespoke company dashboards in Power BI that report on live SMIS data. An example is shown below of one prepared for Abellio group. Some organisations use these dashboards in place of, or to support, their reports, and will use live dashboard in their meetings. The interactive nature enables views of the events that populate each period, and then down to the individual SMIS entry.
Review of the data at this level of detail quickly identifies errors and omissions, which ultimately leads to better data quality.