When the Plan Meets Reality
A good plan is in place. Then operations begin.
DispoClean originated from a specific operational challenge in railway cleaning. Trains need to be cleaned within defined time windows, cleaning tasks must be assigned and teams need clear tour sequences.
The initial plan may appear straightforward:
- interior cleaning at 4:30,
- washroom cleaning at 5:00,
- an additional on-demand cleaning task at 5:30,
- and the start of operations at 6:00.
But once the operational day begins, the conditions behind that plan can change quickly.
Planning under changing conditions
A delay may shorten the available cleaning window. An additional cleaning requirement may emerge at short notice. Resources may become unavailable, while operational rules and priorities still need to be respected.
The challenge is therefore not simply to create an optimised plan. It is to keep that plan useful as the situation changes.
Before tasks can be rescheduled or reassigned, the system needs to understand:
- which change is operationally relevant,
- which tasks and resources are affected,
- which dependencies must be considered,
- and whether a recommendation is sufficiently clear.
Some of these rules are stored in systems. Others only become visible through conversations with experienced operational staff.
What DispoClean has taught us
Our work on DispoClean has shown that effective operational decision support begins with understanding the real process—including its constraints, exceptions and informal rules.
Only then can current operational data be translated into useful recommendations. Plans can be adjusted, priorities reassessed and affected teams provided with a transparent basis for action.
The aim is not to eliminate operational expertise. It is to make that expertise available when the original plan no longer matches reality.
In the next article, we look beyond railway operations and explore where the same operational pattern appears in other industries.
