The draft article came in a neat little package. Here was a college that had found some open-source freeware that could help its institution deal with student service issues as well as resource management. They are arguing that their going the open-source route was saving them a lot of money and time and resources. However, the argument did not include baseline definitions of the pre- and post- intervention situations. There were no real metrics to speak of, only assertions without evidentiary supports. There was nothing about prior costs and post-freeware-adoption-costs. There was nothing about the process that the institution went through to make the technology decisions. And then there was that assumption that “of course, free is cheaper than not-free”.

“Free” Does not Equal “No-Cost”

The “dazzling” aspect of “free” is seductive and somewhat misleading, as Dr. Dan Ariely has noted in his engaging “Predictably Irrational” (2008) text. Sometimes, the costs of going the free route may exact costs that may not be apparent at first glance.

Any time an organization makes large information technology (IT) decisions, it usually goes through a process of due diligence and research. They contact all the myriad potential users on a campus to get their feedback about desired functionalities; they gauge potential user sophistication with related technologies and anticipate their support needs.

They conduct a cost-benefits analysis. They scan the environment for all competing software programs. They bring in various reps from the companies and test their knowledge and customer support. They look under the hood to see what the technology infrastructure is; they calculate how likely this technology will evolve into the future; they look for weaknesses in terms of potential points of information or identity or other compromise.

For open-source software, they look at the reputation of the organization. They look at the tools’ functionalities. They look at how responsive the developer community is to the various changes. They look at how robustly the open-source community developers communicate and contribute their ideas. They look at how a product has evolved over time. They read the fine print in terms of costs. They contact current users, and they ask pointed questions. They look at how easily they can access back-end datamining to collect information. They ask for and look for disconfirming evidence.

And then they might start looking at possibly leaning one way or another.

Actual Costs

This more cautious approach comes because of the realization that the institution of higher education will sink in plenty of costs—of developer time, of user interface development time, of database administrator time…to make sure that the new systems integrate and interact healthily with existing systems, and without information or identity compromises. Staff, faculty, and administrators will sink energies, time, emotions, and resources into the socio-technological systems.

Open-source is no free ride. Actual open-source participation requires participation in the online communities. It requires learning the system in depth. It requires on-going and continuing staff training; developer and database administrator support; helpdesk supports for students (potentially), and so many other inputs that decision-makers may not see at first. The ad hoc approach to choosing software is a risky one.

The Mental Modeling of Decision Makers

Now that I’ve read dozens and dozens of draft articles by campus administrators, I am starting to realize that administrators do often only focus on the cost-benefit equations maybe quite superficially based on what people tell them. Many do not understand the technologies even if they do know how to work within bureaucracies and with people.

The IT administrators I am more familiar with and close-up are consummate professionals. They know the technologies well—both on the front end as users and on the back end in terms of structures. What they don’t know, they go out and learn. They make it their business to know their subject matters well. They’re totally conversant in tech talk, and they get their hands dirty in the fine points. They can be as enthusiastic as the next person, but they level that off with a healthy cynicism—informed by experience.

No matter how people play out a situation, there will always be unforeseen aspects. Still, I am all for the dose of caution and the deep research prior to commitments of large sums and even larger amounts of human investments into a technological system.