Parent categories: Economics.

Goals Pursuit Measurement

YAML Category

Each goal that we set, is essentially economic, because in order to achieve it, we need the time of people and machines to achieve it. The ideas created and plans ("companies/projects") executed towards the achievement of goals may be said to be a type of KPIs for goal pursuit.

In fact, the specific assets (such as products that appear on markets) are a derivative result of these ideas and plans. The economic input to execute these ideas and plans are human and machine execution time. The economic output is the other types of assets -- derivatives of that time. All types of assets are traded on various places (from social media -- human assets, to e-shops -- commodities, to stock markets -- projects, and all other kinds.) They are de-facto traded in all kind of currencies, which are not themselves valuable, but rather, just help determine the price, as a result of supply-and-demand driven exchange.

So, a problem is this -- suppose we have a trade (some market), and assets already have acquired some equilibrium prices. What does that say about the goals of the market participants? Since our Goals can be expressed in terms of ranges for amounts or qualities of assets that we pursuit to have, the markets can tell us about the estimates of goals of all of their participants.

However, suppose we have data about trade of participants of all markets. This trade occurs in various currencies. How do we define a measure, that normalizes the value to some physical unit (i.e., non-monetary unit -- machine/human time and energy) to measure what's physically needed to produce those asset flows that the world needs, and have relative value of different types of times (e.g., true statistical value of different times of different types of machines and different types of humans)?

And, more interestingly, since human combination with a machine may be producing another machine of greater value, it would be interesting to see, what combination chains tend to multiply the physical spending on time (for example, the spending of machine time to do X vs Y product, or human time spent to do X vs Y). Ability to measure and recommend at this level could potentially greatly increase our ability to solve problems and pursue goals.


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