Controlling and risk oriented demand planning
Data analyses and demand planning
You want to make your departments demand planning on your own? Our consultants will support you in this process and provide all required data analyses for fire and rescue demand planning. Especially for the transition from paper documents to digital data, we offer extensive solutions for digitalizing old documents.
We automize your controlling and produce self-learning risk models (aka. Predictive Firefighting) for your operations and demand planning. Also, it is our pleasure to assess your current and desired condition. By request, we support you in the whole process of demand and development planning, as well as emergency response and rescue services planning.
Furthermore, the universal modelling of your risk models can for example be applied to typical hazards of a chemical plant or the operating range of a factory fire brigade, within the measures of emergency response. We also support you assuring the availability and assessment of GPS signales within BOS digital radio.
Risk oriented demand planning
We use state of the art self learning algorithms for risk modelling and establish corresponding risk factors, based on historical operation protocols, preparative operation data, and data from fire prevention. Furthermore we include sociodemographic data. As a result, you get a predictive model for your department’s future workload (aka. Predictive Firefighting).
We cooperate with one of the leading companies in digitalization and text recognition, to support the transition from paper to digital data. Once digitalized, documents undergo a pattern analysis, in which they are processed and categorized. This way ortographic mistakes and alterning definition can be identified, which leads to an improved data quality via computer based algorithms. Therefore each department can be equiped with scan stations, so that protocols can immediately be added to a database.
On request, we also implement real time models in order to predict the expected workload. These self learning models improve their predictions, based on the latest data and circumstances. By combining real time models with geo information systems you will be provided with controlling, planning tools and risk models for your department’s demand planning (The depicted data has without engagement been provided by the city of Seattle, as part of an Open-Data-Licence).
Daily updated automatic analyses of operations are made possible by connecting the mission control server to each workstation in the network. Subsequent analyses are easily possible thanks to using multiple data sources (aka. polyglot data storage). We either integrate already existing indicator systems or establish corresponding indicator in cooperation with your departments. Among others the following indicator and reports for quality management and demand planning can be achieved just using data from the mission control server:
- Time limits for rescue services according to federal legislation
- Customisable time series analyses on the operation quantities and workload including prognosis.
- Displaying the workload of public-safety answering points, call volume, dispatchers of roster creation, as well as the occupancy rate of employees
- Profitability and cost coverage
- Statistics of coroners and resource workload, including make-ready times
- GIS analyses of sites (see also, Predictive Firefighting with Premergency)
- Emergency response rates for firefighting in combination with mission protocls
- Frequency analysis of operations (also those occuring simultaneously) according to parameters such as daytime, district, weekday (see also, District optimization with Premergency)
- automatic reporting of missing time stamps
- Implementation of self-service reports for coverage and further indicators of fire and rescue services
- Optimization of your controlling, regarding demand planning
- Analyses of travel times via test drives and isochrones
- Automation of your fire and rescue services statistics
- Digitalisation of your paper documents and IT based data quality improvement
- Availability analyses of helpers
- Site analyses and optimization via risk models
- Accessability analyses of sites
- Strain prognosis for employees and sites as well as possible relief through personell planning and disposition