In this post we will present a few simple ideas around how grain might flow in SC orgs (scorgs). SC is many things: reputation system, compensation system, project management. This post will focus on SC as a compensation system.
Solvent Scorgs
We begin with an assumption and an observation. The assumption is that contributors prefer to receive a stable monthly payout rather than a volatile one. The observation is that for any org to be solvent (i.e. not go bankrupt), it must earn more than it spends over time. Let us then present two quantities: average monthly inflows (I_m), and average monthly outflows (O_m). I_m is the amount of grain that gets boosted into an org each month. O_m is the amount of grain that gets paid out to contributors each month. Clearly we must have O_m <= I_m or the org will eventually go bust. It is worth noting the difference in character between I_m and O_m. In particular, I_m is liable to be intrinsically volatile, at least until an org becomes very large. This is to say that the amount of grain that gets boosted into an org will vary significantly from month to month, depending on the particular needs and economic conditions of the scorg’s clients. This month clients may boost in 100k G, the next month 50k G, then 150k G. On the other hand, O_m needs to be kept stable, otherwise contributors will have unpredictable salaries, and scorgs will be less appealing than traditional orgs, at least on that dimension.
Let’s assume that monthly inflows of grain (I_m) have averaged 100k over the last six months for a given scorg. If the standard deviation (i.e. typical fluctuation) in I_m is 10k grain, then we can imagine setting O_m to 80k G for a comfortable margin of safety. This is to say that we set our monthly payouts to two standard deviations less than our monthly inflows, to ensure that we are consistently earning more than we spend. Sure, some months I_m may fluctuate down to 70k G or lower, but since on average O_m < I_m, we can make up the difference on these down months by pulling from the savings pool, and still payout to contributors the expected 80k G.
At this point some readers may have noted that if O_m < I_m, then on average there will be some leftover grain each month. We call this leftover grain the monthly savings (S_m). As suggested in the previous paragraph, this monthly savings might be added to a pool which buffers us during down months. We call this savings pool the scorg’s reservoir (R_s). Clearly, since the monthly savings is positive on average, the amount of grain in the reservoir will grow by S_m each month. This fact is worth dwelling on because it is not obvious how the excess grain in R_s will be allocated. We obviously don’t want the reservoir to grow infinitely large, since that’s just a waste. Instead, we want grain to make it back to the contributors somehow. We will now present what is perhaps the simplest mechanism for returning reservoir grain to the scorg’s contributors.
Grainy Season
Following the example above, we can see that on average the reservoir grows by 20k grain each month. Thus, after six months, R_s = 120k G. What to do with this excess grain? It’s just sitting there, not earning anyone interest, and it’s much more than we need to buffer I_m and ensure consistent O_m. We thus propose setting a maximum threshold for the reservoir (R_m). For example, we might set R_m = 120k G. What happens when the reservoir fills to the max threshold? You guessed it: it grains. This is to say that when R_s >= R_m, we “flush the reservoir”, and temporarily increase the monthly payout with the flushed grain. We don’t want to flush all the grain in the reservoir, since then we wouldn’t have any buffer for next month, perhaps just half of it. This would mean that during the grainy season, the excess 60k G would get added to the typical 80k G for a total monthly payout of 140k G (O_m_grainy = O_m_avg + Rm/2). Also note that given this setup, a grainy season would occur every 3 months, for a total of four grainy seasons a year (seasonal period = R_m / 2 / S_m).
Note that the “grainy season” mechanism described above is one of many possible variations. For example, the grainy season could be spread out over multiple payment periods. It is also possible to have an algorithm control O_m continuously to keep it at a target level. While these other mechanisms have definite merits, we will argue below that in order to best serve the population of contributors as a whole, the grain cycle must be simple enough for the median contributor to understand it and to participate meaningfully in the governance of the scorg. We also note that the tipping-point style flush mechanism described above is reminiscent of the action-potential mechanism in neurons, condensation-precipitation mechanism present in earth’s water cycle, as well as competitive-inhibition/cooperative-excitation voting mechanisms in the animal brain’s striatum.
Simplicity as a requirement for decentralized governance
In the discussions above we proposed various parameters including the monthly payout (O_m), the reservoir max threshold (R_m), and the flush amount (R_m/2). For our example, we set these parameters to values that might make sense, but how will these parameters be set in a real-live scorg? The contributors will decide. That is, we propose that these parameters be set via a simple and understandable governance voting process in which the vast majority of contributors can reasonably participate. For this to be possible, the mechanism must be kept simple enough for the majority to understand. Why? Because wealth follows power. If the wealth is to be widely and fairly circulated amongst the majority of contributors (a prerequisite, we believe, to unlocking the crowd intelligence of a scorg), then the power to steer the scorg must be widely circulated as well.
Formulas could possibly be extracted to an appendix, or even better, introduced in conjunction with a diagram. That takes more time though, and I didn’t want to invest it without validating the underlying concepts first.