Culture of Openness

A Culture of Openness is one of the three essential components of an Open Source City, specified in the Introduction.

Moving to a culture of openness is a scary proposition for municipal staffers. It means pushing the city’s internal operations into open data management and workflow management systems that are better tailored to sharing and collaboration than the current hodgepodge of closed, proprietary, black-box systems.

It also means exposing the city to much closer oversight, including potentially identifying wasteful processes that currently pass unchallenged because either a) no one has time to notice them or b) the people who know about them don’t have the power or inclination to fix them.

Staff members may feel that either their job security or professional reputations may be at risk in such an environment. As a result, the change to a culture of openness should follow at least four main guidelines:

1. Make Staff Jobs Easier

An open data system should make it easier for staffers to get necessary information in an accessible format and perform work that adds real value.

2. No Job Loss Through Redundancy

No one’s job should be threatened with redundancy. Instead, it should allow staffers to do the kind of analysis that machines can’t replicate, redeploying city resources where they can work most effectively at solving problems.

3. Iterative Development

The transformation to an open data model should be iterative and incremental, not sweeping. As John Gall famously stated, “A complex system that works is invariably found to have evolved from a simple system that worked. The inverse proposition also appears to be true: A complex system designed from scratch never works and cannot be made to work.”

4. Celebrate Errors

The prevailing corporate (and public) culture would have to change from one that punishes errors (and hence drives them underground) to one that celebrates openness and sees problems not as faults to be punished but as important and valuable opportunities to improve the end product.

Under today’s system, no one wants to look bad so people spend too much time data hoarding and CYA and not enough time finding and fixing problems. As a result, yet more time is wasted trying to obtain and manipulate information to produce reports that are, in turn, also hard to find and manipulate.