A blueprint defines the structure before anything is built. It determines sequence, flow and relationships between components. If the blueprint is flawed, a flawed product will be produced, even when the contractors are competent and well-intentioned.

In Thinking in Systems, Donella Meadows argues that systems produce the results they are designed to produce. When outcomes appear persistent or surprising, the explanation is usually structural rather than behavioural.

Caroline Criado Perez recounts a clear illustration of this in Invisible Women. A Swedish municipality, Karlskoga, began reviewing its policies through a gender equality initiative. During a council discussion, two men reportedly joked that at least snow-clearing would be safe from the gendered scrutiny initiative. No one could accuse snow-ploughing of being sexist.

The municipality’s winter maintenance policy appeared straightforward. Major roads were cleared first. Smaller roads followed. Pedestrian paths and cycle routes were cleared later. The reasoning was practical. Roads carry traffic. Traffic supports economic activity. Safety incidents would be higher cost.

A review was initiated.  Why should snowploughing be exempt from re-examination based on the assumption that it could not possibly contain a gendered design element?

When officials examined the data more closely, a pattern emerged. Travel habits were not gender neutral.

Men were more likely to travel directly between home and work by car, typically during concentrated commuting periods. Women, children and the elderly were more likely to make multiple shorter trips throughout the day. These journeys often involved combinations of walking, cycling and public transport, and included errands such school drop-offs and care responsibilities like groceries or pharmacy visits. Timing also differed. Car commuting concentrated movement during peak hours. Pedestrian and public transport travel occurred throughout the day. The volume of journeys taking place on pedestrian routes and public transport corridors was therefore substantial, even if it was less visible in traditional traffic measurements.

The existing blueprint prioritised clearing roads first because roads carried commuter traffic. But commuter traffic represented only one model of mobility. Drivers were prioritised intentionally, but drivers represented a smaller share of total journeys than the system assumed. When pedestrian paths remained icy longer than roads, those routes became hazardous. Hospital records already showed that pedestrians were injured far more frequently than motorists in winter conditions, and the majority of those injured pedestrians were women.

The productivity impact was also measurable. Sweden routinely tracks work absence caused by injury and care responsibilities. When someone slips on an icy pavement, the economic loss does not stop with the injured person. The injured individual may miss work. Family members may also miss work to provide care. For example, an adult child may stay home to support an elderly parent who has fallen. Because women were both more likely to use pedestrian routes and more likely to bear care responsibilities, the productivity loss disproportionately affected them. When these datasets were examined together, the flaw in the original blueprint became visible.

Karlskoga decided to pilot a different sequence. Pedestrian walkways and cycle paths were cleared first. Roads followed. The costs remained the same, but injuries declined and productivity improved. The pilot ran successfully for three winters.

When the policy was later implemented nationally, the first winter proved unusually severe. Snow accumulation was heavy. Complaints rose quickly. Media coverage framed the policy as impractical and ideological. The earlier pilot results were largely unknown to the majority of the public.

The easier response would have been to revert to the old system. Instead, the redesign held.

The original policy had not been malicious. It had been built around an incomplete model of reality.

Meadows’ central insight is that systems behave exactly as they are structured to behave. System behaviour is shaped not only by visible rules but also by mental models and feedback loops. When assumptions change or a leverage point in the structure is altered, the entire system can produce different outcomes.

Blueprint thinking asks different questions. What assumptions shaped this system? Who was the system optimised for? What data was never connected? What happens if the sequence changes?

In Karlskoga, once the blueprint was redrawn, the outcomes changed.

Leadership often focuses on improving performance within existing systems. Blueprint thinking asks whether the system itself needs redesign.

A Question For You:

Where in your organisation are persistent problems treated as performance failures rather than design failures?

A Small Step:

Choose one recurring operational issue. Map the sequence that produces it. Then ask whether a different structure or order would change the outcome.

References:

1. Meadows DH. (2008). Thinking in systems: A primer. Chelsea Green Publishing.
2. Criado-Perez C. (2019). Invisible Women: Data bias in a world designed for men. Abrams Press.