Making musical sense by email, part 7
I think there are a few key points to note about the process. Before I start, I should note, in case you missed it, that we've been applying a methodology called system dynamics to the problem Greg Sandow posed. I've only mentioned "system dynamics" twice so far in this series and never in my emails to Greg.
- System dynamics can help us think more clearly. Part of that comes from the act of making our mental models more explicit and more precise, even when we're still viewing the world from 10,000 meters up. Part comes from the lessons we learn by considering the effect of feedback on the behavior of the system that's creating our problem. In this case, we used simulation to explore the effect of feedback.
In other words, system dynamics can make us (seem) smarter.
- Because system dynamics leads us to make our mental models very clear and explicit (even at the 10,000 meter level), we also clarify what it is we don't understand. That can help identify and resolve differences in understanding more quickly.
Because system dynamics has the potential to make us look more unambiguously dumb, it can seem risky; fortunately, the benefit of thinking more clearly usually offsets the risk of clarifying our ignorance in front of others, and the two (clearer thinking and revealing our ignorance) together can help us learn and move forward more quickly.
- System dynamics models and system dynamics "interventions" don't need to be big, overarching affairs that take the lead in organizational work; they can be inserted casually and naturally into the conversation as partners in an effort. As you saw, I never once told Greg that I wanted to do or was doing a system dynamics model nor why system dynamics was special. I think I was able to introduce enough information so he could follow what I was saying without inserting too much jargon. I think he was able to assess the utility of the model by what we did discuss.
I think this is healthy. While big programs and up-front acceptance may be important in some cases, I think we respect our clients and our managers if we don't ask them to buy into a process before they see the results. Focus on the problem, not the tool.
There's a benefit for those of us using system dynamics, too. System dynamics isn't the best tool for every problem. If we've sold a client or manager on system dynamics as the way to proceed and it then becomes evident there's a better way for this particular problem, we risk seeming to have failed. We can either change courses and make that risk real, or we can push ahead, staying with a less-than-optimum approach. By inserting system dynamics
dynmaicsmore naturally, we can change courses as circumstances warrant, without having to eat too many of our words along the way.
Of course, that requires that we have skills in (or connections to people with skills in) a variety of approaches.
- It's possible to use system dynamics even by email. Text-mode email is quick (relatively), easy, and encourages interaction. Text-mode graphs make it easy to incorporate graphical data into the conversation, and text-mode drawings make it easy to show simple model diagrams. Text-mode models make it easy to convey the full detail of the model we're using to the degree and in the manner it's useful. I like that.
Of course, some graphs and some graphics are too complex to show in text; for that we use other means. And some people, such as Greg, will prefer higher-quality graphs, while others will be quite happy with the text-mode graphs.
- You don't have to simulate everything. Sure, our insights about nonlinear feedback systems aren't always very good, but there are times when we learn enough from a simple simulation so that we can carry useful lessons over into the more complex situation we really face. There are times we can draw on past experiences with simulations to understand the problem we're currently facing. There are times when we can glean enough insight out of the model we've created to do a useful, informed static analysis.
In this case, I simulated a simple "aging chain" that simplified Greg's problem rather than building a more complex model that replicated the exact dynamics seen in US orchestra attendance. That model seemed to give insights useful enough to guide our discussion profitably.
- You don't have to use system dynamics for every problem. System dynamics works superbly in addressing problems involving feedback, but it's not the only systemic approach we have. Pick the methodology that best suits your problem. Better yet, consider viewing your problem with multiple methodologies to see if that triangulation leads you to consistent solutions; if you get differing recommendations from multiple methodologies, perhaps you have more work to do.
There are a few lessons to be drawn from the musical content of this series, too:
- In general, you won't change the average age of concert-hall audiences over the long haul by reducing the number of newcomers. While you may certainly affect that average age over the short term, the system will recover to its old equilibrium eventually.
- If you cut the inflow of newcomers to zero, you will make the average age change to a new value.
- Based on some results I shared with Greg but didn't show here, the average age recovers more slowly with more drastic drop-offs in newcomers. For sufficiently drastic drop-offs, it may take years or decades to distinguish between a drop to zero and just a drop to a drastically lower number.
Because Greg is working on a book on this subject, I encourage you to check out his blog to explore more lessons about the musical content of this series and to enter into a dialog with him. Check out his interests, too; I think you'll find he enjoys a broad spectrum of musical styles.
If you're more focused on orchestra management, see Drew McManus' Adaptistration.
You can also see another model I'm working on that addresses classical music in my upcoming TAFTO contribution; I'll announce that here when it's published.
I'd be remiss if I didn't thank Greg for the dialog we've had and for his willingness to share it here. Thank you, Greg. All of his words are published in this series with his permission.
Stay tuned for the final postings in this series next week, including a full listing of both models, a table of contents with links to each article in the series, and the possibility of a surprise guest essayist!