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Measuring the efficiency of a fragmented calendar


I looking for a measure of fragmentation, and occupancy of a calendar.

This is to assist in managing calendar events in order to reduce gaps between events and increase overall efficiency.

Attached is an example calendar, the grey bars are events. Each row is a resource. The events can sometimes be moved to different resources, and it can be helpful to quantify the benefit of a move.

What kinds of analysis techniques exist in this area?

Are there any analogies to other systems that could be helpful. eg if the calendar were a river, the bars islands, maybe efficiency might be the average flow rate of the river?

Thanks for your thoughts here.

example calendar
ConsultingOutlook* shared calendarAlgorithms* Scheduling

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Chinmay Patel

8/22/2022 - Mon

Calendar events are items in a mail file. A calendar event today may be adjacent to one created today but two years hence. So realistically calendar events do not fragment any more that normal mail fragmentation. In a local system, you can Compact the mail file.

I am not sure that Exchange would care, but calendars there do not especially fragment
Chinmay Patel

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Thanks for your comments.

John i'm referring to another kind of fragmentation so not sure your comment is relevant in this case.

Chinmay, that sounds reasonable. I think the first challenge is defining a useful metric of what is "good" so that any kind of solver can work towards that. Maybe i need to provide more info to get to that, but for now was wandering if there are any standards out there.

One metric is occupancy - what % of the resource is being scheduled to become occupied. This is straightforward. But another measure is fragmentation.

The context is serviced accommodation. eg an advanced sale for only a few days can have negative value if the opportunity cost of a "better" fit exceeds the sale price.

Sorry that's a terrible explanation I'll try to give a better example later.

Thanks again
Chinmay Patel

Hi Xenium,

Optimized (Manual, Algorithm based, AI Assisted) Scheduling is a technique that can help you mitigate fragmentation. I understand when you say fragmentation it means the gaps in the adjacent bookings for a resource(A room in this case). However, there are other questions, would you move / cancel shorter bookings in favor of long term bookings? if so, what are the thresholds?

In addition, we can calculate the gaps of individual room (over a period of time) and then call that value fragmentation and get the percent value.

Your thoughts?

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hi Chinmay,

Thank you that's right.
I guess some kind of model is needed since there is no easy answer to those questions.
I have some data i could use to test and tune a model (resource, start date, end date, value)

Any other thoughts let me know else i'll close the question soon, and add any comments in due course if i'm able to progress this.


ps additional data includes demand (start date, end date, market price)
Chinmay Patel

Hmmm your second comment I think it will actually complicate your first step. Eventually, yes you would want to forecast(That's why field services uses a little bit of AI to predict the scheduling aspect) but the first step should be getting existing schedules less fragmented (I suppose).
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Thank you for your input, good points.
Chinmay Patel

Glad I could help :)