The Kirkpatrick Learning model helps with evaluating the effectiveness of training. It proposes evaluating at four levels: 

There are quite a few organizational maturity levels, but I’ve generally found them either too specific to a certain domain, or too speculative to apply properly. I recently read a Miller Heiman Group publication that included the one they have developed for sales enablement processes. It seemed to strike the right mix between practicality and useful, and I’ve found it helpful in getting an orientation on a few process-related questions.

Churn is, generally, seen as a bad thing within an organization - teams wants stability and predictability. These help make the organization more legible, and they are part of generating the feelings of psychological safety and mutual trust that are needed for groups to be effective. Churn also produces work which does not feel productive: recruiting, staffing, training and so on. 

At the end of his Patterns of Conflict briefing, Boyd talks about how grand strategy is centered around maintaining and improving our adaptability to change. 

Interesting post and comment thread on Arnold Kling’s blog about construction productivity being higher in the Great Depression. 

Financial portfolio theory has the idea that owning too much of a particular stock is bad as it exposes you to greater company-specific risk, which unlike systemic risk is not generally compensated for by higher returns (assuming investors are demanding proper risk premiums etc.) This leaves room for a particular kind of human error: you have to sell things which are doing well, as they come to represent a greater proportion of your portfolio that is optimal. This is emotionally difficult. 

How do you compete with AWS? Even if you set your sights a little lower in the cloud infrastructure space, does Azure, Google Cloud Platform or Aliyun look much easier? These are big companies with a lot of money, a lot of engineers and a lot of infrastructure. They also have a suite of existing cloud services, letting them act as a “one stop shop” for customers.

There is an ad running in San Francisco that quoted the New York Times, which I think is quoting an old Department of Labor study, to say in 2020 there will be 1.4m new programming jobs in the US and only 400k new trained people to fill them.

One of the common “China is ahead of the rest of the world” stats is the percentage of mobile payments in China versus everywhere else. Like much about the PRC, assuming that signals a future direction of mobile payments in the rest-of-the-world is oversimplified. Doesn’t mean that it’s s wrong, but getting the story right is important if you want to think about the diffusion of other technologies. 

Following up on the post the other day, I have been reading some articles by economist Genda Yūji. His article from last year on the lack of wage increases despite tight labor markets is insightful. The whole thing is worth a look, but in terms of the training discussion going on in the US, I thought this historical view was interesting: