Estimating Demand

It is agreed that consumer councils are where needs are identified and consumption is defined for an upcoming year. There may be some areas where we need to look elsewhere to define what goods and services will be needed but not expressed by consumer councils.

For example, there are all kinds of unexpected maintenance needs for automobiles, homes or various other household goods that cannot be reasonably anticipated. So how could we ensure that tires, alternators, windows etc are available when the need arises?

One way would be to ensure that enough car parts etc are produced to meet unexpected needs. For that matter, how many service outlets would be needed to meet such demand? Prior year’s consumption of these types of goods/services could serve as a baseline to estimate what would be needed for an upcoming year. But, whose role would it be to make this determination? I’m not sure, but it is a function that may be necessary, unless I’ve missed something about how demand could be estimated.

Any thoughts as to whether this is a sound approach and whose role it would be to approve production levels?

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My understanding is that the service based workplaces would ask for inputs based on what they expect to use for the year ahead. Similar to how things work in market economies, they take an educated guess based on previous sales data etc, and then as the year goes on the plan will need adjusted based on how right or wrong they were initially.

On the consumer end, I imagine they would ask to consume services based on what they did last year as well. For example, they would say “I ate out almost every Friday last year so I will mark next year’s consumption with that in mind”. Again, the plan will need adjusted as the year goes on.

I’m more familiar with the goods side of this than the service side, so maybe someone else here has more insight.

I feel like this is a relevant article to your question: » 4 of 10: How will workplaces know what to produce?

You are correct. At the conceptual level there is no difference between producing a service – visits to a doctor’s office for example – and producing a good – a pair of shoes for example. We usually measure services in the number of hours of that particular service, whereas goods are produced in units like pairs of shoes. But both supply of, and demand for a service is like supply of, and demand for a good. The annual plan will settle on a supply of either a good or a service equal to the demand for that good or service. And then, during the year, producers will adjust as they find out that it turns out their is need for either more or less than what was planned.

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I think Claude raises an interesting point about capturing demand during the annual planning procedure for certain types of goods that are harder for consumers to plan for. I can think of goods that I consistently and predictably consume, like food, utilities, clothing, transport, etc. That probably accounts for most stuff in the economy, but then there is the category of stuff that is hard to predict and that we only seldomly purchase over longer time-frames, for example, like a new hammer. Won’t this category of goods likely be under demanded during the planning procedure? What if it turns out that consumer planned demand for hammers is 50% lower than it should be, when in fact we know from past actual consumption data that it should be higher? Is this a problem and how might that be dealt with in participatory planning? Could the Facilitation board adjust the algorithm to take into account for this, or does it give them too much power?


Yeah, I was thinking of this in terms of “surprise services”, like you drive over a nail and need to take your car in for a tire change sooner than expected. I feel like any type of “surprise good or service” should be accounted for when the plan adjusts. Alternatively, I suppose you could have the IFB try and brace for those things… but even if they did you’d still need to make adjustments later. I feel like the surprises should be adjusted for when/if they actually happen instead of trying to brace for them in the beginning.

I think it would be beneficial to lay out in detail how an adjustment procedure could work since it seems to be a common point people bring up. Claude and I discussed what that procedure may look like in another thread a while back actually!

Hi Michael

In your example above, I would argue that WCs, in certain circumstances, be permitted to offer or produce more goods than currently demanded. So for example, I’d have them produce 10% more tire than what is believed would be in demand. They reason being that if we cut things too close, there may not be goods in inventory when they are needed, like a new tire for example.

The capitalist economy uses a “just in time” approach to production to avoid inventories. They do because of recessions, and generally, their inventories are paid for with debt. So if they have inventories of items they can’t sell, like tires, the accrue costs until they are sold.

In a Parecon, there is no interest to pay. We don’t need to run a business on a tight string. At the end of a production year, a WC would state what it has left in its inventory, plus what it will produce in the upcoming year, so that they end up having during the year, about 10% more than is needed. In the end there is no overproduction, but there is enough to go around for everyone. No is unhappy, and we certainly wouldn’t want that, otherwise it would prompt a hue and cry for the ‘good ole days’ i.e. capitalism. No way!

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Yes I agree. The model as I understand it already takes this into account. For example, for the plan to be considered feasible all products must have an excess supply that’s within a certain percentage. If needed, you could let different industries have different percentages but that would be something solved politically I think.

I’m thinking about the impact on how initial prices are set during the annual planning. If tyres, or other goods, which are infrequently consumed and hard to plan for, are under demanded in the planning by consumers, wouldn’t this lead to inaccurate pricing of tyres and fewer tyre producers being able to submit acceptable self-activity proposals than are needed to meet actual demand during the year?

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Yeah, it’s possible that could happen. But my understanding is that this is the type of thing that is handled when the plan adjusts. It’s likely that even products that are not “surprise products” will be mispriced at first if people change their mind. For example, everyone proposes to eat broccoli based products but then decides to buy carrots or something. It would be harder for the carrot producers to get approved during the annual plan, but easier as time moves on. Prices may have to adjust alongside the plan to reflect reality, or maybe prices could stay the same and you could deal with it in other ways.

After spending time with the simulations, I tend to think of the initial plan as being a perfect representation of the economy at that specific point in time. As time moves on it’s possible the entire plan could become extremely inaccurate. It’s also possible most of the plan would be fine. You can’t predict these things, which is why I think having a solid idea of how the plan will adjust is important.

Agreed. Making adjustments during the year will be important and is an area of work that could do with more attention. I see these price adjustments during the year as being minor changes though, requiring negotiation between delegates in industry and consumer federations, which I think is something that we all here would like to aim to keep to a minimum. We want the annual planning procedure to generate, as much as is possible, an efficient, fair and sustainable plan to start the year off. Not perfect, but good and it could turn out in the real-world that demand for durable goods is way off which would then require, not minor, but big adjustments.

In your example, demand for things like broccoli or carrots I don’t worry will be hard to capture in the planning. I consume those things regularly. I can see how much I consumed last year and propose the same again or adjust a little.

If we take say swimming goggles, demand for these are less likely to be accurately captured in the planning than carrots. My question here is: if this turns out to be the case, are there any ways we can think of to optimise this in the planning? Here are some ideas:

a) Each product that is entered into the product catalogue, along with its name, description, also has included its average lifespan. Say we know that a pair of swimming goggles lasts on average 5 years. Five years after purchasing their last pair of goggles in the planning procedure, a consumer can be given a prompt: “Hey, Mary. Your swimming goggles are now five years old. Might you need a new pair this year?”. The more data we have about Mary (how often she swims), the more accurately prompts can be given. As you have in your game Michael, the software could aim to gather data about a person’s lifestyle and personality. This could also be a slippery slope.

b) Or, the algorithm is just designed so that demand for durable goods, which we know from past data is under demanded, adjusts demand for those goods up by whatever percentage that is. This obviously takes away direct influence from the consumer to the designers of the software algorithm, which is something we want to avoid.

Thoughts? Any other ideas? Or am I overstating the problem?

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I think it’s a good idea to plan for some excess supply. However, I feel this is captured by the percentage that all products must be in for the plan to be considered feasible. If we feel certain industries should be allowed a higher percentage to help balance the surprise demand, I think that would be fine. For example, by default all proposed products must have an excess supply of 5% or less for the plan to be approved, but other industries could be allowed 10%.

However, all of this is extremely variable. I agree that products like broccoli and carrots will be easy to capture assuming nothing out of the ordinary is happening. However, it’s still possible that it will be wrong and need some big adjustments.

I think it would be wise to brace for the entire plan to need major adjustments. That’s always going to be in the realm of possibility because anything can happen in the real world. I feel like any further attempts to optimize such as adding “fake demand” are going to boil down to guessing and hoping for the best. Either way, adjustments will be needed.

Maybe this is the software designer in me, but I think it’s best to keep things as pure as possible. Respond to the actual data when it really happens instead of trying to brace for things you can’t predict. Again, I think it’s wise to err on the side of excess supply, but the procedure already does this by allowing products to be overproduced within a certain percentage.

After thinking about what everyone has said, let me try to reframe what I said above in a way that’s more relevant.

Let’s take the tire producers. At the beginning of the annual procedure they will look at last year’s demand and propose something that’s close to that. Consumers, who are not taking into account the nails they are going to run over, propose to consume an amount that’s lower than what tire producers are proposing to make. The plan allows a certain level of overproduction (let’s say 5%). If the excess tires are within that percentage, the plan will be approved. If not, tire producers will need to decrease their proposed production. Let’s say the excess tires are higher than 5% so they must decrease their production proposals.

Let’s say that the tire producers experience this over and over, and constantly have to make big adjustments due to the consumers under demanding. The tire producers could request that they are allowed a higher percentage of excess supply during the initial plan. They could cite the data as proof that people constantly under demand. Alternatively, you could have people at the IFB monitor this and come up with the percentages automatically.

However this is dealt with, once the tire producers are allowed the higher percentage they are requesting (say 10%), they will have enough excess supply from the start to meet the surprise demand that keeps popping up.

Does that make sense?

This is a very interesting and thought-provoking discussion.

The problem I understand it is this: what if individual consumers erroneously demand too little of a good or service in their annual consumption proposal, such that these individual errors sum to a serious deficiency in the aggregate?

Following Jason, what if consumers - in the aggregate - demand only 50% of the electric drills they need? (I changed it from hammers to drills).

I’d frame the problem in terms of certainty/information: the individual consumer doesn’t know how many electric drills they need this year (for example, they don’t know theirs is going to break in 3 months). However, society does know how many electric drills are needed. It will be the number purchased last year +/- some small percentage (say 5%).

I’d also say that we need to view this problem on three levels: (1) the individual consumer, (2) the individual enterprise, (3) society as a whole.

The question becomes: when this problem arises. what is the practical result?

Scenario 1 - no intervention: Consumption proposals are approved, demanding 10,000 electric drills whereas 20,000 will be needed. This results in a shortage of electric drills produced in January. The shops respond by raising prices. The electric drill producers receive this information and ramp up production, hence requesting additional inputs from other worker councils, the results of which are unclear to me.

The following occurs to me. Firstly, these spurts in production are precisely what planning seeks to avoid. Secondly, such a spurt might be acceptable for one good, but if this occurs for sufficiently many goods it could distort the economy at a systemic level. We cannot just think about whether consumers who want drills will get them. For example, producing electric drills requires steel, wiring, and plastic. If the approved plan under-demands electric drills, it will also under-demand steel, wiring, and plastic. If other goods are under-demanded which also require steel, wiring, and plastic, then the indicative prices will be too low for those inputs and all worker councils and consumer councils will be implementing an annual plan which under-values them. Not efficient.

Here is a good time to think about consumer councils rather than individual consumers. While an individual consumer might not know that will need a new electric drill in 3 months, a consumer council / federation will know approximately how many electrical drills it will need this year. The question is how to bring this knowledge to bear on the planning process.

Scenario 2 - CC intervention: We can begin to think about that by thinking about how exactly this problem could be spotted. For example, let’s say a forecasting support unit in the National Consumer Federation peruses the data for the proposed annual plan. They see that aggregate demand for electric drills is down 50% on the quantity purchased last year. The first matter is the threshold: what % decrease is considered problematic? That will depend. Now there is an evaluation: (1) is this a real decrease in demand due to a change in preferences? (2) is this a measurement artifact distorting the plan? The answer to that question will come from historical data and practical sense. It is perhaps plausible that demand for coconut water, a fad item, has decreased by 50%. It is not plausible that demand for electric drills has done so, barring some exceptional circumstance.

One solution could be to authorise consumer federations to modify consumption proposals in specific ways to facilitate a smooth and efficient planning process. So, in this example, the NCF decides to change the total electric drills demanded in the total consumption proposal from 10,000 drills to, say, 20,000 (what it was last year). To take a conservative approach, this could be mandated only for certain types of goods. Experts in consumption patterns will relatively easily be able to demarcate what is likely to change rapidly and what is not, and this knowledge can inform what NCF policy is agreed.

The thresholds for different goods/services will have to be guessed at first and then refined over subsequent years. For example, if the NCF sees demand for car tyres is down 20% from last year and so changes the consumption proposal to demand the same quantity as last year. At year’s end, there is a 15% surplus of car tyres. Well, lesson learned for the NCF and in particular its support units. Institutions have to gain practical experience like that. As for that example, car tyres aren’t perishable so no big deal. They can be sold next year.

As far as I’m concerned, that solves the problem. Thoughts?

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I’d frame the issue as this: our goal is to make the planning as participatory and bottom-up as possible; however, it’s possible that there could be some inefficiency if some categories of goods are significantly under-demanded by consumers in the planning, particularly durable goods. IF through experimentation and implementation in the real-world that this proves to be the case, the question then becomes what should a Participatory Economy do about it in a way that maximises its values.

If I may, I will attempt to summarise all the ideas proposed so far in order of level of intervention from pure participatory planning, and add some further comments:

A) No Intervention

Ferdia lists a number of undesirable effects and inefficiency that would result from doing nothing about historically known under-demanded goods in the annual planning procedure. (When you say “shops respond by raising prices”, the consumer and worker federations who meet to adjust the prices, as individual sellers don’t set prices in a PE, in case someone reading misinterprets that, but I assume that this is what you meant).

B) Prompting Consumers

I suggested that individual consumers could be prompted with suggestions to include items in their consumption plans based on knowing the life span of goods and gathering data on their personal preferences, similar to how online shopping platforms recommend items to you based on past consumption behaviour. This might be a good idea to do anyway, but may not be sufficient alone to address the potential problem.

C) Adjusting the Algorithm to take into account anticipated under demand

Two ways have been suggested to do this:

Michael suggests increasing the acceptable threshold of excess supply for goods that we know will be under demanded from past data. More workplaces producing electric drills would have their proposals accepted in this case. Would the price adjustment algorithm also need modifying for those goods? I don’t know. It would be interesting to test out.

I suggested that the facilitation board could increase demand for these certain types of known-to-be-under-demand goods by a certain percentage based on historical data.

In either of these cases though, and even if socially agreed upon, this does gives the facilitation board workers much more discretion in shaping the plan.

D) Adjustment by the Consumer Federations

Ferdia suggests that the consumer councils are the ones that could be responsible for spotting issues and updating the consumption proposals to take into account possible under demanding on behalf of their consumer members. This gives the consumer federations more discretion in influencing the plan, but I think there is a good argument that if this needs to be done, it should be the consumer representatives rather the facilitation board workers who can do it, and why I like this option out of those presented so far.

Although, being able to add additional electric drills to their plans could take consumptions councils’ consumption plans over their member’s planned income limits, which may need solving.

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This is a great discussion thread, a lot of thoughtful commentary.

Regarding meeting demand for the unforeseen and how we respond, think of the COVID pandemic and its impact on the supply chain. I’m all for efficiency, but at what price? Almost, any, but not all, product for which where there isn’t enough supply could create inefficiency.

I’ll give you an example. It may be a bit extreme, but worth considering. A contractor built an addition on my home. The price of wood was through the roof. It had a huge impact on the overall cost of the project. The build was not a luxury, its use is intended for my mother in law who has Alzheimer’s. Allowing prices to rise to meet demand resulted in the devaluation of our currency and hence lowered its purchasing power. I can understand how this can happen in a market economy, but If this were to happen under a Parecon, I would not be impressed with this Economy. I’d have higher expectations. Which is why i argued earlier that a little bit of over production is not such a bad thing when it comes to non-perishable goods.

Another example is where the contractor who built this addition had an issue with his truck’s transmission. The part he needed was back ordered. It was unknown when the part was going to be available. He needs his truck so that he can do his work. These are extreme COVID supply chain circumstances, but one that would have to be avoided in order for construction projects to move forward as planned.

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In such circumstances, I would produce fewer hammers the following year. Taking inventory of goods would be an important activity to undertake each year and should be part of the planning process when calculating and approving production levels. But, large swings of availability of products should be avoided as much as possible. In this example, it could be disruptive for the WCs that would now produce fewer hammers. It may create an excess labour supply and workers would have to locate work opportunities elsewhere. A stable and constant supply of goods is the best case scenario for all concerned with as little fluctuation as possible so as not to disrupt people’s lives.

Yes, this is a great discussion and it’s great to see multiple people chiming in! I will just add this:

The goal of the procedure is to ensure that the entities decide for themselves what they want to do and then make adjustments based on the data that’s sent back to them. I would strongly argue against any kind of plan manipulation unless it’s the individuals themselves making adjustments based on the data available to them. At the end of the day, the entities are the ones making the economy run, so it’s the entities that need to address this scenario. I agree that society as a whole has the relevant info in this case, not the individual. However, the entity that’s responsible for providing this society wide info to the individuals is the IFB.

Jason mentioned that a different pricing algorithm may be needed in this scenario. This is true, and I believe there’s already been discussion among the simulation team regarding how the IFB will adjust different products in different ways, just like how different surplus percentages will be provided to different products. Everything we’ve been talking about would be taken into account when the IFB decides how to go about doing this.

I also believe the prices alone do not provide enough information to producers during the procedure. I think they provide sufficient information to consumers, but I think the IFB should announce additional pieces of info to help producers calculate the specific amounts they need to use in their updated proposals. I was able to speed up the planning procedure quite a bit in my game by doing this, and I also think this is a great way for the IFB to keep producers informed of any “surprise demand” that’s anticipated. The IFB can’t force producers to take their advice, but I imagine it will be very useful in cases like this.

Great discussion. This is how I see it:

Some support unit on the consumer side or a subunit of IFB focused on statistics will prepare first draft consumption proposals based on actual historic consumption patterns (not just covering the last year but all time) for every household/individual. This is a starting point and the individual/household then make any adjustments s/he wants.

In this context only expected changes to a consumer’s consumption patterns need to be considered. It could be based on expected changes in income, changes in habits (someone deciding to become a vegan etc,) a newly found desire to do something different not done before like downhill skiing, starting a family, moving to a house that needs work etc. When trying to estimate such changes in their consumption patterns, consumers would have access to a large number of statistical consumer profiles to consult to help him/her to estimate changes in consumption.

Some consumption will be statistically derived from other consumption and cannot be changed, such as service, repairs etc if you propose to consume a car or a bike.

In short, statistics in the form of historic consumption patterns and consumer profiles will be the basis for a consumer’s proposal but it will be the consumer that makes final adjustments and pushes the button and submits his/her proposal.

This, together with the suggested supply excess percenatages, will work good enough, I think. Note that there is a built in tendancy for demand to be over stated since a percentage of all submitted proposals will not be implemented since people will die unexpectically in different accidents, illnesses, etc, etc.

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Yes, that’s how I see it too. I envision the IFB being a supercomputer, so I think there’s a lot of ways for the IFB to smooth out the process by providing statistics or automating certain aspects of the procedure.