From Personal Travel Plans (PTPs) to workplace travel intelligence: What can employers learn?

A Personal Travel Plan answers a very personal question: “Given my current commute, what realistic choices do I have?”

But repeat that analysis across hundreds or thousands of employees and a different set of questions, and answers, start to emerge. How are people travelling today? How many actually have realistic alternatives? Where are those opportunities concentrated? Where is driving still the only practical option? And where might an employer get the greatest value from limited time, budget and workplace-travel resources?

That is the point where Personal Travel Planning starts to become workplace travel intelligence.

A Personal Travel Plan helps one employee understand their options. Analyse those journeys across a workforce, and you start to understand where the organisation’s real travel opportunities are.

One commute tells you something. Hundreds reveal patterns.

At an individual level, the useful information might be fairly straightforward: how somebody currently travels, how long their journey takes, what it costs and whether realistic alternatives exist. At organisational level, those individual journeys become a much richer evidence base.

An employer can begin to understand current mode share, commuting patterns, emissions, travel distances and the distribution of different journey types across its workforce. That baseline matters. If an organisation wants to reduce parking pressure, support active travel, improve access to work or reduce commuting emissions, it first needs to understand what people are actually doing.

But descriptive data is only the beginning.

One of the lessons from workplace travel planning is that organisations rarely need more data simply for the sake of having it. They need evidence, confidence and priorities that help them decide what to do next. CalCommuter's experience has increasingly reinforced that distinction: measuring commuting is useful, but understanding where the practical opportunities are is considerably more valuable.

The question therefore moves from “How do our staff commute?” towards “Where are the realistic opportunities to do something differently?”

How many employees actually have viable alternatives?

Traditional staff travel surveys can tell an employer how people currently commute and may ask whether employees would consider another mode. Useful as that can be, it does not necessarily tell you whether another journey actually works.

An employee might be interested in travelling by bus, for example, but the available service might take several times longer than driving or fail to match their working hours. Someone else may never have seriously considered cycling even though the journey itself is relatively short and can be done on a quite route.

Analysing actual journeys adds another layer. Rather than simply measuring attitudes, an employer can start to understand how many staff have an identified public transport, walking or cycling alternative that falls within sensible viability criteria for their commute.

That does not mean those employees will change how they travel. As we explored in the previous article, a viable alternative represents an opportunity, not a prediction of behaviour.

But the distinction is important. There is a significant difference between a workforce where relatively few people have practical alternatives and one where a sizeable group does. The appropriate workplace travel response should be different too.

A single large workplace can contain very different travel opportunities

This analysis does not require an organisation to have lots of different worksites.

Consider one large hospital employing several thousand people. Everyone may be travelling to broadly the same destination, but their commutes could still look completely different.

Some employees may live close enough to walk or cycle. Others may live along strong bus or rail corridors. Some may have a public transport journey that works well for a daytime shift but not for an early start or late finish. Others may commute from rural areas where driving remains the only realistic option.

Looking only at the hospital's overall mode share could hide much of that variation. The more useful insight comes from understanding which opportunities exist within different parts of the workforce.

A hospital might discover, for example, that there is a concentration of employees living within realistic cycling distance in one area, another sizeable group with practical public transport connections along a particular corridor, and a substantial number of staff for whom those options simply do not work.

The organisation has not changed. The destination has not changed. But the travel opportunities within that single workforce are very different.

Large organisations such as NHS bodies are particularly interesting in this respect because large workforces and shift patterns create considerable commuting complexity even before multiple worksites are considered.

Geography can reveal where the opportunity sits

This is why workforce-wide percentages can sometimes conceal as much as they reveal.

Imagine an employer finds that 20% of its staff have an identified viable public transport alternative. That is useful information, but the next question is: where are those employees?

They could be scattered across a large region, with little else in common. Or a substantial proportion could live along the same bus or rail corridor. The same applies to walking and cycling opportunities. A relatively modest organisation-wide percentage could represent a very significant opportunity if many of those employees are clustered around the same neighbourhoods or transport routes. These clusters of staff are also potential candidates for car share: on all days they commure, or sometimes only for some commute days they have in common.

Experience from CalCommuter deployments has shown that viable travel opportunities are rarely spread evenly across a workforce. Geography can be one of the most important clues to understanding where an intervention might have the greatest relevance.

That changes the type of question an employer can ask. Rather than simply asking “How do we encourage more people to cycle?”, it can ask why a particular geographic cluster has a concentration of employees with realistic cycling journeys, and what might help that group.

Similarly, instead of a generic objective to increase public transport use, the organisation can investigate which employees already have a practical public transport journey, where those employees live and whether there are common barriers preventing greater use.

That is a much stronger starting point for targeted intervention.

Multiple worksites add another layer

For organisations with several worksites, there is an additional dimension.

Different workplaces may have completely different transport contexts. One could sit next to a railway station with strong bus connections. Another might be on the edge of town with limited public transport but a large number of employees living within cycling distance. A third might draw staff from a wide rural catchment where driving remains the realistic option for most people.

Organisation-wide mode share can mask those differences too. Worksite-level analysis can help explain why commuting behaviour varies and, importantly, why the same intervention may not make sense everywhere.

A public transport initiative that is highly relevant at one location could have very little value at another. Additional cycle facilities could have considerably greater potential at one worksite than another, while parking pressures may arise for entirely different reasons at different locations.

The objective is not to find one workplace travel solution and apply it everywhere. It is to understand the pattern of opportunities first and then decide what response is appropriate.

Knowing where driving remains the only realistic option is useful too

Workplace travel analysis should not only identify where people could change. It should also help show where realistic alternatives are limited.

That matters for employees, because repeatedly encouraging somebody to use an option that does not work for their journey can quickly undermine trust. But it is equally valuable information for the employer.

If a substantial group of employees have no practical alternative to driving, that tells the organisation something about the nature of the problem. Public transport provision may be weak, working hours may not match available services, the workplace may draw people from a large rural area, or the geography of the labour market may simply make alternatives difficult.

Those employees should not automatically be treated as failed behaviour-change opportunities.

Sometimes the useful conclusion from the analysis is that driving remains the realistic option under current conditions. That gives the organisation a much more credible picture of what can and cannot reasonably be influenced through workplace travel activity.

Commute data can help employers understand parking demand

Parking is a particularly useful example of why this distinction matters.

An employer may already know that its car park is under pressure. A simple staff travel survey can tell it how many employees drive, but that does not necessarily explain how much of that demand could realistically change.

Journey analysis provides more context. How many regular drivers have an identified viable alternative? Are there groups of drivers living along strong public transport corridors? How many are within realistic walking or cycling distance? Are there particular working patterns or attendance days associated with greater parking demand?

For a large worksite, this could be especially valuable. A single site might have thousands of employees arriving across different shifts, as well as substantial competition for limited parking space. Understanding that 1,000 people drive is useful; understanding which parts of that demand appear relatively fixed and which parts may be more open to influence is much more actionable.

That does not automatically tell the employer what its parking policy should be. But it helps distinguish between different parts of the problem.

Some parking demand may come from employees with strong alternatives who simply prefer to drive. Some may come from people with practical alternatives but relatively small barriers that an employer could help address. Other demand may come from journeys where driving is currently very difficult to replace.

CalCommuter's experience has also indicated that parking availability and convenience can influence commuting behaviour alongside parking cost, reinforcing the value of looking at parking as part of the wider travel picture rather than as an isolated issue.

Some opportunities only appear when journeys are analysed together

Car sharing provides another example of something that only really becomes visible at workforce level.

An individual Personal Travel Plan cannot tell somebody that a suitable colleague will necessarily be available to share their journey. Potential matches emerge only when one employee's journey can be compared with others travelling to the same workplace, at similar times, from nearby areas and on at least some of the same days.

That is why potential car-sharing opportunities are better analysed at an organisational level rather than presented within an individual's Personal Travel Plan.

For a single large workplace, there could potentially be hundreds or thousands of journeys to compare. Analysing those together may reveal clusters of employees whose travel patterns are sufficiently similar to represent a potential car-sharing opportunity.

For a multi-site organisation, the same principle applies separately within the relevant workplaces.

Identifying a potential match does not mean employees will choose to share a journey, and whether they do so remains their decision. But without workforce-level analysis, the employer may not know where the opportunity exists at all.

From travel data, to business cases, to targeted intervention

This is where workplace travel intelligence becomes particularly useful.

Most organisations have finite budgets, finite staff time and limited capacity for workplace travel initiatives. They cannot provide intensive support to every employee, fund every possible intervention or promote every travel option with equal intensity.

Prioritisation therefore matters.

Once an organisation understands its existing commuting patterns and where realistic alternatives exist, it can begin to distinguish between different types of opportunity.

There may be employees with strong alternatives who need little more than relevant information. Another group might have a practical option but face a relatively small barrier that training, an incentive, improved facilities or targeted support could help address. A geographic concentration of public transport opportunities might justify engagement with a transport operator. A cluster of employees with realistic cycling journeys might strengthen the case for better cycle facilities. Elsewhere, the evidence may show that the barrier is structural and cannot realistically be addressed through individual behaviour-change activity.

The important progression is from data to opportunity to intervention.

CalCommuter's product and partnership philosophy has increasingly developed around that idea. Rather than a dashboard simply describing what has already happened, workplace travel intelligence, combined with the expertise of our partners, should increasingly help answer where effort should be focused, which groups are relevant and which types of intervention justify further attention.

In other words:

“Here are your choices.” — employee

“Where are the realistic opportunities across our workforce?” — employer

“What should we do about them?” — workplace travel planning

The intervention should follow the opportunity

That final question matters because workplace travel programmes can easily default to broad communications.

An organisation wants more active travel and sends everyone a message about cycling. Or it wants to reduce car use and sends the entire workforce information about public transport.

Some employees may find that highly relevant. Many will not.

A stronger approach is to understand the opportunity first and then decide what intervention fits it. That could mean identifying:

• a group with realistic cycling journeys who might benefit from better facilities, training or support;

• employees along a strong public transport corridor who could receive relevant service or ticket information;

• a geographic cluster where car-sharing potential appears particularly strong;

• drivers whose journeys suggest that parking demand may be more open to influence;

• or employees for whom there is currently no realistic alternative, where repeated travel-behaviour messaging is unlikely to achieve much.

The principle is the same one that applies to the individual Personal Travel Plan: the intervention should follow the opportunity.

That does not mean data should replace professional judgement. Quite the opposite. Good analysis gives transport planners, advisers and behaviour-change practitioners a stronger starting point for deciding where their expertise is likely to add most value.

CalCommuter's development has increasingly focused on this progression from analysis towards prioritisation: identifying who, where and why so organisations can direct limited resources more deliberately.

Workplace travel intelligence is about decisions, not dashboards

There is a temptation to think of workforce travel analysis primarily as reporting. Mode-share charts are useful. Emissions totals are useful. Maps, worksite comparisons and journey statistics are useful.

But their real value comes when they help somebody make a decision.

• Should we focus more attention on public transport for this group of employees?

• Is there enough cycling potential around this hospital to justify further investment?

• Which employees might benefit from targeted information?

• Is there a meaningful car-sharing opportunity?

• Is parking pressure partly addressable through workplace travel activity, or are most drivers currently dependent on their cars?

And where the evidence reveals clusters of employees with similar barriers, is there something the organisation, a transport operator, local authority or delivery partner could do about it?

That is the distinction between workplace travel data and workplace travel intelligence.

The first tells you what is happening. The second helps you understand where the opportunities are, which ones matter and where to focus next.

From the individual journey to the organisational opportunity

Personal Travel Plans remain important because the employee should receive something useful from taking part. For the individual, that means understanding their own commute and the realistic choices available to them.

But those same journey analyses have another value when viewed collectively.

Within one large workplace, they can reveal patterns across thousands of employees: where realistic alternatives exist, where they cluster, which travel modes appear practical for different groups, where parking demand may be more open to influence, where potential car-sharing opportunities exist and where driving remains the only realistic option.

Across a multi-site organisation, the same analysis can also reveal how those patterns differ from one workplace to another.

Most importantly, workplace travel intelligence can help an organisation decide where limited travel-planning resources are most likely to be useful.

That is the progression from Personal Travel Planning to workplace travel intelligence.

Not simply:

“How are our employees travelling?”

But:

“Where are the realistic opportunities — and what should we do next?”

That is where the next stage of workplace travel planning begins.