Commute analysis has informed office location strategy for decades. What has changed is the range and weight of factors occupiers must now consider. Hybrid working has raised expectations of the office as a destination and workplace experience; changing workforce demographics are influencing how employees value time, cost, reliability and flexibility; and new transport infrastructure is opening potential locations while reinforcing the advantages of established centres in others.

At the same time, more sophisticated location data and journey-planning tools allow occupiers to measure accessibility with greater precision, compare real travel times across different modes and test future scenarios. Combined with growing attention to talent access, office attendance and Scope 3 emissions, these developments are reshaping the commute discussion from a simple measure of distance into a broader assessment of employee experience and business impact.

Commute analysis is not about identifying a single “correct” location. It gives leadership a clearer view of how each option may affect employees, talent access, office attendance and business objectives—so that trade-offs can be made deliberately."

Erik Thorbeck, Senior Insights & Data Lead, Asia Pacific

A recent example makes the case. When a major occupier in Bangalore was weighing two potential sites in Bangalore, commute analysis revealed that a non-central location would generate roughly 500,000 kg more CO2 per year than a central one — and that up to 85% of staff would face transit commutes of over an hour each way. Findings like these reshape a location decision well beyond rent and availability. Here is how occupiers can get ahead of that challenge.

Analysing Different Types of Transport

In many cities, employees can choose between several modes of transport to get to work..The four primary types are walking, driving, public transport, and cycling. While most employees in North America will drive to work, the picture is more mixed in APAC, with public transport usage varying widely depending on coverage and speed.  In Europe, it tends to be a mix of public transport, walking, and cycling. Still, in any given city, major differences are likely to exist between accessibility for different modes of transport, and choosing a site more accessible to a larger pool of talent has the potential to help or hinder a company’s growth, especially in markets with fierce competition for talent. 

Why Commute Time Often Matters More Than Distance

Distance alone can be misleading. A geographically closer office may take longer to reach because of congestion, limited road capacity, indirect public transport routes or poor last-mile connectivity. For most employees, the practical question is not simply how many kilometres they travel, but how long in terms of time, how costly and predictable the journey will be.

This is especially important in congested cities. Commute analysis should compare realistic travel times at relevant departure periods and, where possible, consider variability rather than relying exclusively on a single average. Median journey time, the proportion of employees within an agreed threshold, and the number facing particularly long journeys can provide a more useful picture than distance alone.

Defining Ideal Criteria

Setting ideal criteria for commute times, such as a specific range of minutes, is crucial. This helps determine what percentage of employees fall within this range, ensuring that the majority can reach the site comfortably and quickly. We generally advise clients to define an ideal range, such as 45 minutes, and see what percent of staff are within that range for each site.  Defining these criteria will help narrow down sites with an acceptable commute, and therefore access to skilled labour.

Looking at Expanding Transit Connectivity in Sydney: Are expanding transit lines supporting new districts, or is the reverse true?

As many cities expand their transport networks, decentralised options begin to look attractive to occupiers.  Take Sydney, which has been expanding its metro lines aggressively, connecting the North Shore to the CBD.  Looking at options in this district, compared to four options in the CBD, we found an average difference of around 3-4 minutes by public transport, indicating less of an impact to staff used to commuting to the CBD.  When looking at staff in range of a desirable commute (defined as 45 minutes or less by public transport), around 10% less were in range of options in North Sydney. 

Still, the new stations & line extension puts North Sydney within 3 minutes of Barangaroo, 5 minutes to Martin Place, and Central in around 9 minutes.  

In Sydney - 40% of a major occupier’s staff are within a 45 minute commute by public transport of CBD Locations. It is clear that a great majority of them live in and around the southern & eastern suburbs.

When you zoom out to 100% of staff, you get a sense for how spread out some employees are.  The median commute time by public transport rises to 54 minutes. 

Improvements to urban transport networks can change the relative accessibility of different office markets. However, the effect is not always to make decentralised locations more attractive.

In this case in Sydney, for example, the recent transport improvements have reduced the practical separation between the CBD and parts of the North Shore. This can support multiple location strategies. It may improve access to established office markets outside the CBD, but it can also make a move into the CBD less disruptive for employees already based elsewhere.

This is occurring alongside a broader flight to quality, with some occupiers consolidating or recentralising into higher-quality CBD accommodation. In effect, the transport investments are actually reinforcing the strength of the CBD, and removing barriers for staff to get to the office, which is particularly important in a market where office attendance still lags below pre-covid levels.

The lesson is that new infrastructure should not be viewed as automatically benefiting one submarket. Commute analysis helps occupiers understand how changes to the network affect their own workforce and location options.

Bangalore: Using Commute Analysis to Understand and Manage Trade-Offs

-  Site A: Centrally located in Bangalore: median commute distance: 13km or 67 mins median commute time 

-  Site B: Non-CBD location in Bangalore: 8km, or 77 mins median commute time

Public transport was not yet the primary commuting mode for this workforce. Fewer than 25 employees were using suburban rail and approximately 100 were using the Metro. Most employees remained dependent on the road network through cars, two-wheelers or company-provided transport. The most relevant question was therefore how the alternative location would affect road travel times and the overall employee commute experience.

The analysis indicated the potential scale and distribution of the impact, but it did not determine the property decision on its own. The occupier had broader business reasons for proceeding, including the expansion of an existing operation at the location. The findings instead allowed leadership to make an informed trade-off and consider measures to mitigate employee disruption, including transport support and employee benefits.

Bangalore’s public transport network is expanding, with further connections to key office markets expected in 2027–28. As the network and last-mile connectivity improve, public transport accessibility is likely to become a more influential part of location analysis. For now, road travel time and reliability remain central considerations for many occupiers.

Estimating Employee-Commute Emissions

Employee-commute emissions can provide an additional lens for occupiers with ESG reporting requirements or portfolio-level sustainability targets. By taking several assumptions into mind, occupiers can make reasonably accurate estimates for emissions for an entire workforce.

The methodology typically combines estimated journey distance with emissions factors for different modes of transport. Its reliability depends on the quality of the underlying data and assumptions:

• Primary and secondary transport modes
• Vehicle type and fuel source
• Vehicle occupancy
• Office attendance frequency
• Route and departure time
• Use of company-provided transport
• First- and last-mile travel
• Changes in employee behaviour following a move

Where employee-level information is unavailable, the analysis can model a range of scenarios. Results should be presented with the assumptions clearly stated and, where appropriate, as a range rather than a single definitive figure.

For many occupiers, particularly in India, employee-commute emissions are still not widely discussed as part of real estate decision making. Cost, business requirements, talent access and commute time generally carry greater weight. Nevertheless, emissions analysis can provide a useful portfolio-level metric for regional or global occupiers seeking to understand how locations perform across accessibility, employee travel and ESG considerations.

In the Bangalore case study, under the modelled travel-mode, attendance and vehicle-occupancy assumptions, one location was estimated to generate approximately 500,000 kg more employee-commute CO₂ emissions per year than the other. The result was not the determining factor in the occupier’s decision, but it provided an additional measure of the trade-off between the two locations.

Looking at this chart, we can generally infer that driving produces 3-4x more emissions per km than public transport.  Expanded to a hypothetical analysis of how 1200 employees might commute to 2 different sites, the difference in emissions is quite stark.  

When looking at commutes from an emissions perspective, the analysis starts to become a tool for clients measuring and comparing impacts across their wider portfolios.

Singapore: A smaller marginal impact, and a case against decentralising

An occupier’s recent decision to remain centrally located in Singapore was not a foregone conclusion.  Their search included several central locations, but also decentralized options, one further east, and one further west.  After learning that the large majority of their staff lived in the east of Singapore, making the shortlist was considerably easier.

While the difference between the highest and lowest scoring asset, in median commute times, was only around 11 minutes by public transport, zooming out, it would have meant that 42% of staff would have seen their commutes rise to between 1-2 hours, up from 20% with a more central location.  In this case, with differences in terms of median range much smaller, a better approach was to define an “ideal” criteria, of 45 minutes by public transport, and see which option contained the highest proportion of staff in range.  When looking at this angle, options catering to where the majority of staff lived in the east covered nearly double the amount of staff.  Looking at it another way, with the lowest scoring option, around 80% of staff would have been “out of range” of an ideal commute, which is sure to have downstream effects on morale, retention, and talent attraction.

The analysis fundamentally changed the trajectory of the search. Before undertaking the study, there was active debate around locations across Singapore. By mapping where employees lived and measuring the impact on commuting times, we demonstrated that an east-focused strategy would provide materially better outcomes for a significantly larger proportion of staff.

The analysis gave stakeholders the confidence to narrow the shortlist, ensuring location decisions were driven by workforce data rather than intuition."

– Colin Jones, Senior Director, Commercial, Singapore

Using Location Data from APIs to Build More Realistic Scenarios

What was once more the realm of logistics planning, 3rd party data tools are making the gathering of data for this exercise more consistent and scalable. They can estimate journeys between employee locations and potential offices using different modes, routes and departure times.

These tools improve the quality of the analysis, but they do not remove the need for assumptions. Modelled travel times may differ from employees’ lived experience, particularly where journeys involve informal transport, company shuttles, complex interchanges or unreliable last-mile connections. API results are therefore most useful when combined with local market knowledge and, where appropriate, employee survey data.

Rather than presenting a single forecast, occupiers can test several scenarios—for example, peak and off-peak departures, different attendance patterns, alternative transport modes and planned future infrastructure.

From Analysis to Action

The purpose of commute analysis is not simply to rank sites. It is to identify the practical consequences of a location decision and the measures that may be needed to support it. The analysis can help occupiers ask:

• How many employees would experience a materially longer or shorter journey?
• Which teams or workforce groups would be most affected?
• How would the move influence office attendance?
• Would the location expand or reduce access to key talent pools?
• Would employees face additional travel costs?
• Is public transport genuinely usable from end to end?
• Are parking, shuttle services or other transport support required?
• How might the move affect employees following a merger or consolidation?
• What assumptions underpin any emissions estimate?
• How could planned transport infrastructure change the result in future?

The answers allow organisations to move from a property comparison to a broader workplace and workforce strategy.

Why It Matters

As occupiers balance cost, talent and sustainability objectives, commute analysis is becoming an increasingly important part of workplace strategy. Organisations that understand how their employees travel can make more informed location decisions, improve accessibility for staff, and support broader business and ESG goals. In competitive talent markets, that understanding is increasingly a source of competitive advantage.