On a plane trip, I watched Jamais Cascio’s TED talk on tools for building a better world. Futurist Cascio at one point quotes Evelin Lindner:
Pessimism is a luxury of good times… in difficult times, pessimism is a self-fulfilling, self-inflicted death sentence.
So, Cascio says, he tries not to focus on the hellbound-handbasket aspects of life. And at one point he cites four attributes that augur hope and promise for the future:
- Transparency
- Collaboration
- Willingness to experiment
- Science
I found myself thinking about these attributes in terms of the spectrum that makes up most of my work life: the one running from training through learning.
There’s always been learning, of course–the internal change in the organism caused by its interaction with the outside. And I’d argue that as long as there have been organizations, there’s been training as well: activity intended to help others learn.
At times, training gets way the hell off track. It turns into rote memorization, sheep-dipping, ritualism, and above all talking at people–a misplaced faith in knowledge by osmosis.
That doesn’t negate the fact that parts of most jobs in most organizations are straightforward and procedural. Most of the decisions involved are more “how do I?” or “what’s the best way?” rather than “how can I find a way?” So, on what Rummler and Brache would call the job/performer level, and to a large extent on the process level, it makes sense to articulate, explain, and guide people as they learn.
What do Cascio’s attributes have to do with it? For today, I’ll take the first: transparency adds value. It also moves you away from the 60s-era high-school model of how people learn.
On the training end of the spectrum, transparency means you’re specific about what the training involves (hello, Bob Mager). You connect it to the real-life job or process. You make clear its value to the organization and (at least potentially) to the performer.
You’re also objective — when you’re talking about making hotel reservations or opening new bank accounts or processing advanced ship notices, you make clear how the results are measured and what the standards are. If there are three acceptable ways to install the EDI software, then you make clear what each one is and how someone might choose one over the other.
(And if it doesn’t make any difference at all, maybe you’ve got some process improvements to suggest.)
What about further on the learning end of the spectrum, when the knowledge is more tacit? Where you don’t have one right response so much as a number of possible ways?
Here I think transparency means you’re clear about known, acceptable performance. You share that to help the learn build up a mental model of what works and what doesn’t.
I once saw a case-based program for handling labor relations complaints. In the early stages, you read a case and learned “this violates the agreement because…” With the next case, you saw “this does not violate the agreement because…” The third case didn’t have a resolution; your job was to make a decision based on principles you drew from the earlier ones.
By “transparency,” I don’t necessarily mean you give away all the answers. At the same time, for something like working with a corporate computer system, you certainly could combine how-to instruction with what Ruth Colvin Clark called worked examples.
Tim and Irene Wierzbecki want to fly from Omaha to New Haven, leaving before noon on the 18th, and returning after 2 p.m. on the 24th. The complete reservation should look like this and come to this amount…
Any thoughts on how transparency might play out for learning within organizations?