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Why should I use geospatial technology when planning my office relocation?
Finding new talent can be time consuming and expensive. When considering locations for your office move, staff retention is an important factor. The move will most likely affect staff commute times and costs. Geospatial technology can help you plan for these changes.
By mapping your move using geospatial technology you can:
- Visualise your employees’ home addresses on a map
- Analyse commute times to different locations by different modes of transport
- Layer other important information onto the map, like amenities
- Discover the best location for your new office
How do I use geospatial technology to plan my office relocation?
Geospatial technology allows you to visualise the office locations you are researching and the impact of the move on your staff.
Let’s take a look at an example using the TravelTime Analyticstool.
Using TravelTime Analytics to plan an office relocation
Tom runs a creative agency in London. Business is going well and he has recently hired five new members of staff to meet the demand. This brings the total number of people in the office to 25. His current office only seats 20.
Tom needs to move. But he is concerned that changing location might disrupt his team. Tom can minimise this disruption by finding a great location for all his staff.
1. Map staff postcodes
Tom has a list of his team’s postcodes.
| Employee Name | Employee Postcode |
|---|---|
| Andrea | EC2N 2SF |
| Phil | EC3N 4DH |
| Ellis | EC4Y 7HR |
| Deepak | EC1R 0EX |
| Shane | EC1M 5TX |
| Jamie | EC1V 4NW |
| Olivia | EC1V 7HU |
| Tom | SE6 4UR |
| Fiona | SE7 7RN |
| Ben | SE19 2RP |
| Kate | SE16 5UN |
| Idris | SE5 7RQ |
| Michelle | SE9 5DR |
| Katya | WC1X 9EA |
| Maureen | WC1H 8LG |
| Francesca | WC1H 9RA |
| Arnav | WC1H 0JW |
| Erica | WC1N 1DX |
| Matthew | WC1X 8QH |
| Gabriella | WC1X 8QH |
| Julie | WC2H 7JS |
| Peter | NW1 7ST |
| Darnell | NW1 9AH |
Tom can plot his employees’ addresses on a map using geospatial technology. The image below shows all employee locations plotted on a map.
2. Analyse staff travel times
Now that Tom can visualise where his staff live, he can start to explore potential office locations.
Tom sent out a survey to his staff to help him decide the search parameters for his analysis. Looking at the survey he can see that most of his staff would like to commute for no more than 45 minutes.
Tom sets the maximum travel time to 45 minutes and sets the mode of transport to ‘driving’. He sets the time of day to ‘ARRIVE by 9am’, as this is when his staff get into the office.
The heat map below shows all the areas that staff that can reach within the maximum travel time by driving.
Tom can see that 100% of staff can reach the yellow area within 45 minutes driving.
3. Compare modes of transport
Tom reviews the survey again and realises that most of his employees prefer to travel by public transport. So, he keeps the arrival time as 9am, but changes the mode of transport to ‘public transport’.
The heat map below shows the areas that staff that can reach within the maximum travel time by public transport.
4. Layer the map
Tom can now export KML files for these areas so that he can view the layer on Google Maps or another mapping provider or GIS software. This will allow him to analyse the area in relation to other factors, such as:
- Average rent
- Proximity to amenities
- Proximity to existing clients
- Proximity to potential clients
After taking everything into account, Tom decides that the best location for his office is Barnsbury, which falls within the pink area on the map.
5. Plan for negative impact
Tom checks the effect this location will have on staff. He realises that his preferred location will suit almost everyone. But it will mean that Michelle, Ben and Idris will have to travel for over an hour to get to work.
Tom looks at their surveys again. He notes that all three have listed ‘cost of commute’ as their primary concern. Tom decides to implement a season ticket loan scheme to help with payment.
He also notes that Michelle and Idris don’t mind travelling for over an hour, but Ben does. Tom runs the analysis again but changes Ben’s start time to 9.45am. With the new start time, Ben can get into the office in under an hour. So Tom decides to offer Ben the option to start work later.
In addition to visualising staff commute times using geospatial technology, you can analyse the change in commute times and costsusing TravelTime.
To try TravelTime for yourself, sign up for a free API key .