There’s no denying that administrative activities are critical to any organization, but by themselves they are seldom enough to achieve high levels of performance. As we reported a few days ago, the World Health Organization has just made public the results of a study that shows that a simple set of surgical safety checklists was able to reduce deaths in the operating room by an astounding forty percent, and major complications by a third.
The point bears repeating: one of the simplest and cheapest forms of information technology, the checklist, applied to the cognitive side of surgery in addition to its administrative side, reduced deaths by forty percent.
That doesn’t mean that creating the checklists was trivial. It required surveying specialists across the globe, as well as careful analysis and refining of their responses. This was knowledge work, research in its real sense, and surely it profited from IT. But it hadn’t been done before because the healthcare system as a whole (we are talking here of systemic characteristics to which there are exceptions, of course) is rather more focused in improving their record keeping that in improving the cognitive skills of its professionals, when the latter has at least as much of an impact as the former.
Healthcare is an appalling example because of the loss of life involved, but it’s not the only one. In fact, most organizations have a blind spot when it comes to what, exactly, is the Knowledge Economy about. Gathering information, indexing it, putting it online, collaborating on it, are useful steps, but they are no substitute for the business of thinking, and most organizations today, whether they have realized or not, are in that business.
The National Research Council offers six general recommendations based on their study. Rewriting them for greater generality, we think they are valid for a wide set of organizations:
- Focus on the right metric. This is a cliché, yes. Consultants have been urging you to do that for the last few decades. But it’s useful to keep in mind that most organizations reward, consciously or not, deniability over efficacy: The problem isn’t screwing up, but screwing up without some written —digital if you are ahead of the curve— proof that it wasn’t really your fault. This skews the incentives for people away from intellectual work (finding out things) and toward administrative work (getting receipts for things).
- Improve at the small scale. Except for very specific cases, large groups don’t think, individuals do. Collaboration and debate are important, but they are things you do with thoughts, not things you do instead of thinking. Begin by supporting individual thinking, and then scale up to small groups.
- Shift from task-specific transactions to cognitive support. This is the critical point. Unless you invest as much on technology for people to think about what to put in their reports as you invest on the technology they use to write and file those reports, you will end up with many carefully indexed and formatted reports from which your organization will extract almost no value at all. They will be valuable to people’s careers, of course, because failing to file reports gets you in trouble, but filing reports with no thought behind them doesn’t.
- Encourage research on system-level organizational understanding, computable knowledge structures, and human-computer interfaces. In other words, become better at understanding in a sophisticated way how organizations work, how knowledge is extracted from data, and how people interacts with computers. Properly used, these intellectual tools are very useful to avoid some of the pitfalls that turn IT into record-keeping and nothing but record-keeping.
- Aggregate data. Records aren’t bad by themselves. They are one of the raw materials of thought. But they need to be used, and for that, they need to be available in useful ways. This is one of the few aspects in which we think organizations are moving in the right direction, with databases becoming generally more comprehensive, useful and transparent.
- Improve cross-disciplinary education and training. A famous computer scientist once said Computer science isn’t about computers, just as astronomy isn’t about telescopes. It still remains true. Organizations tend to train people to use computers, without training them in understanding the information they can access through those computers, and how they can use that information to acquire useful and novel knowledge. This wastes both technological resources and the people’s potential.