Frequently Asked Questions
What is Predictive Modeling
Predictive Modeling is the process of using known results to create, process, and validate a model that can be used to forecast future outcomes. Deccan runs a thorough analysis of the client’s historical data and then leverages that historical performance to predict how the agency will perform under variable future conditions.
Why is Predictive Modeling Important?
Predictive Modeling is important because it allows clients to demonstrate or simulate their performance before future conditions occur. For example, if a developer plans to build 1000 new homes in a particular part of the community, they can analyze how their current resources will respond over the proposed road network and to the increased call volume the new development will bring. Predictive Modeling applications graphically depict the impact of growth on response times and the ability to meet community emergency services needs. Additionally, analysis can be run to ensure that any new stations offered as part of the development are placed in a way to benefit the entire community.
Contrary to modeling community growth, analysis can also be run to demonstrate the operational impacts of funding/staffing reductions. Response capabilities can be simulated without the resources in question, visually demonstrating what the impacts of funding reductions will be, along with who will be impacted by those reductions.
What is the Difference Between Predictive and Prescriptive Analytics?
While predictive analytics describes a set of conditions in the future based on historical analysis, prescriptive analytics provides recommendations on the appropriate action to take for optimal outcomes. Deccan clients benefit from prescriptive analytics through real-time analysis of their operational deployment, along with recommendations on where to locate remaining resources for optimal coverage at any given time. Such prescriptive analysis monitors operational deployment 24 hours a day, seven days a week, to ensure the best deployment coverage. This is critically important as it can shave minutes off response times to emergencies.
What Type of Data is Used for Predictive Analytics/Modeling?
Predictive and prescriptive analytics leverage historical response data to build an algorithm that can simulate agency response based on a given set of conditions. The algorithm considers response times, road network, traffic speeds, historical traffic conditions, and historical unit availability to create simulations based on client queries.
Operational Intelligence is leveraging data and analytics in a way that generates real-time and relevant information that guides decisions in the emergency services environment.
What Are Run Cards?
Run cards or “run orders” are a sequence of resources designated to respond to a particular type of emergency in a specific geographic space. The run cards are loaded into the dispatch software (CAD) for public safety dispatch entities.
How Do You Update Run Cards?
Manually updating a set of run cards can be a very tedious process. It requires staff to manually consider each set of call types for each geographic response zone listed in the CAD. Manual configuration of run cards can take weeks, if not months, to update and are subject to human error. Deccan clients use analytics to automate this process by verifying street networks, historical traffic conditions and predicted response times to automate the selection of each resource for each call type. This analysis saves tremendous time for staff and eliminates the opportunity for human error.