One standard, twenty-four hours of operation
A service station can have a clearly defined standard for greeting the vehicle, serving customers at the pump, offering complementary services, handling payment, maintaining the store, and closing out the interaction.
That standard is usually the same throughout the day. However, the conditions under which it has to be carried out change.
At night there may be fewer staff on hand, a different volume of customers, different shift leads, and a different operating rhythm altogether. Night shifts also tend to receive fewer supervision visits and administrative checks.
So the question is a concrete one:
Does the standard hold up the same way across every shift?
The standard is the same; the conditions can change
Greeting a vehicle at 11 a.m. and at 11 p.m. should follow the same criteria set by the company.
That doesn't mean both shifts operate under the same conditions.
A station might run with three staff members during the day and scale down to a smaller team at night. The store may have fewer people available for restocking. A shift supervisor might be present during certain hours and not others. Even the type and frequency of customers can shift.
These differences matter because a standard needs conditions that make it possible to carry it out.
When gaps appear between shifts, the problem isn't necessarily the standard itself. It can also lie in the conditions under which people are expected to meet it.
Where the differences tend to show up
There are specific points in the customer experience where variability between shifts tends to become more visible.
Greeting the vehicle. A reduced staff count can increase wait times or lead to a simplified greeting when several tasks come up at once.
Service at the pump. Checking the oil, tire pressure, cleaning the windshield, or other complementary services require time and availability during the interaction.
Add-on sales. A product recommendation or an invitation to visit the store can be part of the process, but it tends to drop off when attention is focused on quickly handling the fill-up and the payment.
Store and restrooms. Cleaning, restocking, and maintenance compete with other tasks when fewer people have to cover multiple areas at once.
Payment and closing. Communicating promotions, loyalty programs, saying goodbye, and other closing steps can also play out differently depending on the shift's conditions.
The existence of these sensitive points doesn't prove that the night shift performs worse. It simply indicates what's worth observing and comparing.
The brand also sets its own compliance conditions
At many stations, part of the standard comes from the brand, or flag, under which the location operates. This adds another dimension to the problem.
Brand audits typically review service, image, restrooms, the store, add-on sales, and other aspects that affect the customer experience. Meeting them can also be tied to commercial terms, brand programs, and the continuity of the relationship between the parties.
But an audit carried out at a given moment offers a snapshot of that moment.
A station can perform well in checks carried out during standard hours and show more variability during other stretches of the day.
That's why, when an operation runs 24 hours, when you measure also matters.
Finding a difference doesn't explain the cause yet
Suppose the measurements show lower compliance at night. The quickest explanation might be to attribute it to lighter supervision. But other variables are also possible.
Staffing may be insufficient to carry out every task at once. Demand volume or type may differ. There may be different shift leadership. Some procedures may have been designed mainly with daytime operations in mind. There may also be content that needs reinforcing through training.
That's why it helps to keep two things separate:
"This criterion is met less often at night" is a finding.
"It's met less often for this reason" is a diagnosis.
Getting from one to the other requires additional information. A difference between shifts can have operational, knowledge-related, organizational, leadership, or execution-related causes.
Measure first, then intervene
To find out whether variability between shifts genuinely exists, execution has to be compared using equivalent criteria.
Mystery shopping is a useful tool for observing the experience under normal conditions. It allows different moments and times of day to be assessed without the interaction being altered by the visible presence of a supervisor or auditor.
An operational audit can add another perspective: the condition of the service area, availability, cleanliness, restocking, and compliance with procedures.
The two methods answer different questions.
One observes the experience from the customer's interaction. The other allows conditions and operational criteria to be assessed in a structured way.
Used across different shifts and with comparable criteria, together they make it possible to identify where variability shows up and how often.
An example: when the problem looked like it was the team
Consider a network that found lower add-on sales and more restocking issues during the night shift.
A first read might point to the team working that shift.
But a closer look at the operation revealed something else: during the day, two or three people were on staff, while at night there was only one.
That one person had to handle the pump, manage payments, and look after the store all at once. When customers or tasks overlapped, something had to give.
Under those conditions, offering an extra service, making a cross-sell, or restocking a product right away becomes harder to pull off.
The intervention changes completely.
Instead of increasing oversight or explaining the same standard again, the right move may be to review staffing levels, redistribute tasks differently, or adapt certain procedures to the real conditions of that shift.
That's the value of diagnosing before deciding on an action. The case shows precisely how a difference initially chalked up to the team's commitment could actually be explained by the staffing levels available.
Training also depends on the cause
Training can be part of the solution when there's a gap in knowledge, understanding, or how certain criteria are applied.
For example, a team might need to reinforce how to make an add-on sale, how to handle certain situations, or which steps of the standard need to hold even during busier periods.
But if someone already knows the procedure perfectly and the operating conditions make it impossible to carry out, repeating the training is unlikely to solve the problem.
The intervention should match the cause that was identified.
It might involve training, procedural changes, staffing adjustments, task reorganization, shift leadership, or a combination of several measures.
Measuring again closes the loop
After intervening, one question remains open:
Did the difference between shifts shrink?
Answering it requires going back and observing the operation using comparable criteria.
That's how you can tell whether the change produced the expected result, whether the gap persists, or whether a different problem has emerged.
The sequence is fairly straightforward:
Standard → measurement by shift → gap identification → root-cause analysis → intervention → re-measurement
Continuous improvement shows up precisely in that repetition. A decision stops being judged by the intent behind it and starts being judged by what actually happens in the operation afterward.
A 24-hour standard needs to be observed across 24 hours
A station may show consistent execution for most of the day and still show differences at certain hours.
That doesn't automatically turn the night shift into a problem. It shows that a continuous operation needs to be observed with an eye to the different contexts in which it runs.
Consistency depends on having a clearly defined standard, but also on having procedures, staffing, training, and leadership that fit the conditions of each shift.
For a network of stations, understanding these differences makes it possible to work on specific problems instead of applying the same response to every gap.
How we approach this at GestorCX
In projects involving operations that run across multiple shifts, we combine mystery shopping, structured audits, and periodic measurement to compare execution against common criteria. Based on the results, we identify the gaps that call for further analysis and define the type of intervention that fits. Follow-up measurements make it possible to see whether the changes implemented actually hold up in the operation.
