Mission Critical Technologies 2018

Getting a clear picture on the front line

Towards an optimal dispatch decision

Benjamin Berhault

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Getting a clear picture on the front line

Towards an optimal dispatch decision

Benjamin Berhault

Hi everyone, I'm Benjamin Berhault. I've been working for the Paris Fire Brigade for 14 years now - first as a fire fighter and paramedic for 7 years, from simple fire fighter to watch manager, and I loved it, really loved it.

But then at some point I had to help in a different way, so I decided to go back to school, to get a master degree.
Still working for the Paris Fire Brigade, I'm now an IT person, Data programmer/analyst.

I still contribute in helping people but in a different way, from behind the scene, providing to managers meaningful information extracted from data produced by different systems used.

The reason why Jackson Szabo asked me to come and talk in front of you today is related to some work I've realised leading to a way to increase the effectiveness of emergency services.

So let's talk about efficiency.

Effectiveness of an emergency service

Good decision at the right time

Effectiveness of an emergency service

The optimal team for a rescue request

Nature of the emergency
Location of the request
Estimated time of transportation of the team

Immediate response
How long will it take for a first team to reach a location?
Response capacity
How many teams can be on site within a given timeframe?

Current systems do not specify to the operators, the consequence of their allocation decision. They do not show them the resulting coverage of the population at the time of the dispatch decision. They do not show them the population percentage covered below the threshold of quality of service. [Wait few seconds]

Before going further I need you to have in mind 2 important concepts of operations management for emergency services.
To effectively manage an emergency service the concept of coverage of the population is important ..., and we can split it into 2 types:

The immediate response relying on: How long will it take for a first team to reach a location?
And the response capacity: How many teams can be on site within a given timeframe? (for example, the target timeframe for London Ambulance Service is 8 minutes)

The latter is the most important and you will have a representation of it on the next slide.

With those notions in mind, let's see what might look like an effective dispatch application.

For this demonstration, let's say that we are about to send a team for a non-critical request while the operational coverage is suffering due to a strong demand of relief, leading to 30% of the units remaining available.

[next]This application has been setup to recover the first 3 fastest units (this is of course just a parameter modifiable, if needed).
The allocation options are now presented with 2 maps:

one showing the response capacity before allocation, at the top
and after allocation for the bottom one

The ambulances are represented by blue points of interest and the request by a red one.
For the road segments, red means that those segments are not reachable by a team under the 8 minutes quality of service threshold. For those reachable by 1 to 5 teams they are assigned a color from yellow to green, green if 5 teams are able to reach them under 8 minutes.
Cartographic representations are really great for quickly assessing the service situation,

But in some cases, things may not be so obvious, so for that, each allocation option is associated with an estimate of the population covered under 8 minutes.

Even if the interface could have been more exhaustive, I hope it’s made it obvious the benefits of such information in a dispatch application.

I hope I'm not the only one who finds that this is not a gadget but that this tool has a real interest in improving the quality of service for an emergency service.
And do not see this as an end in itself, but as a brick needed and suitable for outstanding future applications that will increase the capacity of the emergency services in terms of control of their coverage and responsiveness.

one showing the response capacity before allocation, at the top
and after allocation for the bottom one

The ambulances are represented by blue points of interest and the request by a red one.
For the road segments, red means that those segments are not reachable by a team under the 8 minutes quality of service threshold. For those reachable by 1 to 5 teams they are assigned a color from yellow to green, green if 5 teams are able to reach them under 8 minutes.
Cartographic representations are really great for quickly assessing the service situation,

But in some cases, things may not be so obvious, so for that, each allocation option is associated with an estimate of the population covered after dispatch under 8 minutes.

Even if the interface could have been more exhaustive, I hope it’s made it obvious the benefits of such information in a dispatch application.

I hope I'm not the only one who finds that this is not a gadget but that this tool has a real interest in improving the quality of service for an emergency service.
And do not see this as an end in itself, but as a brick needed and suitable for outstanding future applications that will increase the capacity of the emergency services in terms of control of their coverage and responsiveness.

one showing the response capacity before allocation, at the top
and after allocation for the bottom one

The ambulances are represented by blue points of interest and the request by a red one.
For the road segments, red means that those segments are not reachable by a team under the 8 minutes quality of service threshold. For those reachable by 1 to 5 teams they are assigned a color from yellow to green, green if 5 teams are able to reach them under 8 minutes.
Cartographic representations are really great for quickly assessing the service situation,

But in some cases, things may not be so obvious, so for that, each allocation option is associated with an estimate of the population covered after dispatch under 8 minutes.

Even if the interface could have been more exhaustive, I hope it’s made it obvious the benefits of such information in a dispatch application.

I hope I'm not the only one who finds that this is not a gadget but that this tool has a real interest in improving the quality of service for an emergency service.
And do not see this as an end in itself, but as a brick needed and suitable for outstanding future applications that will increase the capacity of the emergency services in terms of control of their coverage and responsiveness.

Because after being able to assess more accurately the transit of the rescue units, the current coverage and after dispatch.

Well ... It seems to me that any responsible, responsive and dedicated professional of an emergency service will have in mind to push the possibilities offered by geographic information systems further with the indoor mapping.

The exploitation of the internal cartography will be incredible for the emergency services if they really invest in it. The centres of management and coordination will no longer have to envy the management rooms of the Hollywood super productions ...
The next revolution of the control of emergency operations will not be the ability to predict [next] where an emergency call will take place, with 3 mediums floating in a pool as in the movie minority report.

No..

Questions ?

benjamin.berhault@hotmail.com

Getting a clear picture on the front line

Towards an optimal dispatch decision

Getting a clear picture on the front line

Towards an optimal dispatch decision

Effectiveness of an emergency service

Effectiveness of an emergency service

Immediate response

Response capacity

Questions ?