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The Fieldcode Optimizer assists you in scheduling tickets in a smart way.

Fieldcode Optimizer essentially affects two areas inside the Fieldcode work place.

For one it directly schedules all dispatch-ready tickets for today, tomorrow, or a defined interval (up to one week) smartly with a simple press of one button which is called Optimize Now. This button has its’ home in the Timeline.

On the other hand, the Fieldcode Optimizer continuously assists you in the background when you’re using the Scheduling Assistant by giving you smart suggestions when scheduling an appointment with the customer.

You will notice a green message on top of the Scheduling Assistant telling you that the Optimizer was already active in the background.
Chips that are highlighted display the best option for this ticket.
Selecting the suggested day, time, and engineer preferences means picking the smartest choice for this particular ticket.

The “Optimize Now” and “Optimize Timeline” buttons initiate the actual optimization process of tickets inside the Dispatch group or inside the Timeline.
It is the part of the Optimizer that assists you in the foreground. Inside the Optimizer Preview, you will see precisely what is currently happening to your tickets on the Dispatch tab or the Timeline and how they will be placed on the Timeline.

The Optimization is based on one of the three available Presets that are selectable inside Fieldcode Admin Panel -> Dispatch -> Service Delivery
Please scroll down in this FAQ to learn what each of the Presets means.

You will notice that tickets from the Ticket Pool inside the Dispatch tab will move to the Timeline.
The tickets auto-move to spots in the Timeline where it makes the most sense depending on the desired preset you select inside the Fieldcode Admin Panel.

The following tickets benefit from the “Optimize Now” functionality:

  • Tickets inside the Dispatch tab (ready for Dispatch)
  • Tickets with the status APPOINTMENT.
  • You will still have to schedule tickets with the end-user manually.
  • Tickets within a 300 km range of the particular dispatch group area.

Most common reasons:

  • You may not have the matching permissions granted. Please contact your local admin, if you need permissions for the Optimizer.
  • Partner users are currently not able to use the Optimizer.

The following tickets are excluded from the “Optimize Now” functionality:

  • Locked tickets are not affected by the Fieldcode Optimizer as you still should have the possibility to decide on certain tickets for yourself.
  • Tickets with a proposed or fixed time in the past cannot get optimized.
  • Tickets outside a 300 km range of the particular dispatch group area.

In this case, the “first come, first served” rule would apply.

  • The second user would see the optimization results of the first user.
  • The second user would also be notified when the first user takes over the optimization results.

The warning messages will teach you why particular tickets were ignored by the Optimizer.
You should try to manually schedule them or fix the reason in this case.

The main goal of the Fieldcode Optimizer is to find smart ticket assignments taking into account company-relevant criteria like:

  1. Minimize spent time:
    Use this setting if you are paying your work force for their spent time per day. We will optimize the schedule to reduce driving times per engineer which might lead to higher CO2 footprint
  2. Reduce CO2 emissions:
    We will optimize your work force schedules to reduce the maximum amount of CO2.
  3. Maximize engineer utilization:
    This setting is recommended for organizations who want to maximize the engineer utilization. Our opitimizer will try to schedule as much tickets as possible per head count which might leave engineers without any assignment for the day.

By tackling given parameters inside Fieldcode such as:

  • Working engineers
    considering their locations
    considering their availabilities
    considering their skillset
  • Combined ticket challenges (Ticket challenges + PUDO challenges)
    considering the end user’s location
    considering the ticket lock status (time + engineer)
    considering the ticket priorities (ticket scoring)
    considering dependencies
    considering availabilities
  • Time interval (Optimization interval) the user selects
  • Track matrix
    considering distances between the engineer and the tickets
    considering durations between engineer and tickets
  • Algorithm parameters
    considering Optimizer objective
    considering the pc clock time
    considering other relevant algorithm parameters

To fulfill one of the following goals in the best possible way:

  1. Minimize spent time:
    Use this setting if you are paying your work force for their spent time per day. We will optimize the schedule to reduce driving times per engineer which might lead to higher CO2 footprint
  2. Reduce CO2 emissions:
    We will optimize your work force schedules to reduce the maximum amount of CO2.
  3. Maximize engineer utilization:
    This setting is recommended for organizations who want to maximize the engineer utilization. Our opitimizer will try to schedule as much tickets as possible per head count which might leave engineers without any assignment for the day.

The Optimizer operation is dependent on the Optimizer interval first. After that, it starts taking location constraints into account. A location constraint consists of various dependencies such as driving times, absent times, idle times, and more. All these factors are considered for an efficient route calculation for tickets that will be optimized.

Or in one sentence: Location constraints help to define the ticket order.

The Fieldcode Optimizer tries to schedule the optimal calendar for the overall group and not just a single ticket. The complexity exponentially grows with more engineers and more stops on the route (eg. customer appointments and PUDO visits).

Our sophisticated algorithm is able to handle engineer data, ticket data (including PUDOS), optimization intervals, track matrices, and a lot more for the future.

The following results are to be expected:

  • Minimized transport efforts. Considering driving durations, driving distances, idle times, etc. pp
  • Best engineer availabilities for the tickets are considered
  • Matching skills between engineer and ticket are considered
  • Nearby engineer location is considered for the tickets
  • LSDT/ETA of the ticket is observed
  • Tickets with priority get scheduled faster
  • Other dependencies that are considered
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