A simplified mechanism for the simulation of trade in an RPG where it is not to be the focal point.

Image by Roy from Pixabay

Background

A confluence of thoughts from different sources came together the other day relating to how we assess profit from selling something. I’m not sure it was strong enough to count as a revelation, but it’s an insight at the very least, a way of looking at objects and trade goods that helps encapsulate an entire economy.

It’s completely irrelevant to the currently-in-progress chapter of the Trade In Fantasy series, but completely relevant to the broader subject, so it will eventually get given a place in the total text – I’m just not sure where it should go at this point. Because it’s a fairly fundamental conceptual tool, it will probably end up being tacked on to the end of one of the chapters already published, or inserted somewhere into the middle of it.

For today, though, it’s a standalone subject for later integration into the main text.

The fundamental concept of Trade

The whole basis of Trade as a concept is the notion that some commodity or item is worth more over there than it is here, and the difference is more than the cost of transporting the Goods over the intervening distance. A merchant therefore buys it here, moves it there, and sells it, becoming wealthier at the end of the process than they were at the start of it.

To avoid bogging down in nomenclature, let’s just call it a ‘thing’.

Processed ‘Things’

There is often an intermediate step in which a character with appropriate expertise takes the commodity, adds work to it, and transforms it from one ‘thing’ into another. It’s usually simpler to disconnect the supply chain into separate transactions, but that’s not always the case.

So,
1. Person #1 makes or extracts Thing A at Location 1.
2. Person #2 buys Thing A from Person #1.
3. Person #2 transports it to location 2.
4. Person #2 sells Thing A to Person #3.
5. Person #3 transforms Thing A into Thing B by adding Work to it.
6. Person #4 buys Thing B from from Person #3.
7. Person #4 transports Thing B to location 3.
8. Person #4 sells Thing B to Person #5.
9. Person #5 either resells Thing B to Person #6, or adds more Work to it to create Thing C.
10. If Thing C was created, the process loops back to step 6 with new People added to the supply chain.

Each of these steps is as simple as its possible to make it, but to make it even clearer, let’s look at an example.

1. Person #1 digs up some iron ore.
2. Person #2 buys the iron ore from Person #1.
3. Person #2 transports it to a smelter.
4. Person #2 sells the ore to the owner of the smelter, or pays them to add work to it.
5. Person #3 transforms the ore into iron, probably in the form of rods or ingots.
6. Person #4 buys the ingots from the smelter (or Person #2 reclaims his property, becoming Person#4 in the process).
7. Person #4 transports The iron to location 3.
8. Person #4 sells the iron to Person #5.
9. Person #5 adds more Work to it to create a steel sword.
10. Person #5 sells the sword, either direct to the public, or by completing the commission to create a sword, or to a retailer (Person #6), or to another intermediary (Person #7).
11. Person #6 (if any) sells the sword to the public, or joins it with others to fulfill a supply contract. It will almost certainly have to be moved, a service Person #7 is hired to provide.
12. Person #7 moves the sword (and other trade goods) from the place it was made to a place where there is higher demand for such.
13. Person #7 sells the sword if they own it, or delivers it. The purchaser, Person #8, either sells it to the public, uses it to fill a commission or contract, or keeps it as a personal possession.

This example breaks down a little in steps 10 and 13 because swords are typically sold by the blacksmith and not to a retailer, but it’s good enough. Many steps may be added – decorations, and scabbards and hilts – before the final product is achieved. For a presentation sword, the sort of item one Noble might gift to another, I could easily double the length of the list.

Value isn’t what you think, perhaps

At each stage of the process, the Thing being traded has three ways of being valued, and they are all valid in some respect.

There’s how much it has cost so far.
There’s how much the current owner can sell it for.
And, there’s how much the ultimate end-product can be sold for.

At each stage of the process, the current owner sells the product after increasing its value, either by adding Value of Location or by adding work. They incur costs in the process, which diminish the profits, so they want those profits to not only cover those costs, but pay therm enough to live on until the next sale.

The third value helps increase the second, helping achieve this goal.

So, at any given point in the process, how much is the Thing, in its current form, actually worth?

To someone who has already sold it, it’s worth exactly what was paid for it.

To someone who currently owns it, it’s COST is what they paid for it plus the Cost of whatever they are doing to it to increase its value. It’s either worth the total of those two costs, or its worth what they can sell it for at the end of that process.

If it were taken from them, the Cost Sum is how much they are actually out of pocket. But the effect on their prosperity is the higher, second, value.

Profits

A lot of people think that a business adds up its costs, including what they paid for the product that they are selling, and add a % profit margin to the total to get the price that they charge.

That’s not how it works.

For any given product, there’s a price that customers are willing to pay, and that’s what drives the retail price.

Even that’s an oversimplification in two important ways. First, there is a correlation between sale price and sale volume. Drop the price, and you sell disproportionately more of a product. If you chart the multiple of those two products against profit (assuming all costs are fixed), you find a dumbbell curve, with a peak at the point of maximum overall profit.

But all costs aren’t fixed, some of them are proportionate to shelf time, and there are other factors that impact sales volume – products stored at eye height outsell those stored somewhat higher, which in turn outsell those stored lower. The higher the sales volume, the shorter the shelf time – so lowering your price a little below that predicted peak volume can actually reduce costs and boost profits. And, if you’re already selling a large volume of a commodity, there’s a temptation to place it at eye height – but that can be a mistake; you’re already selling more relative to a market’s capacity to buy, so there might not be enough room for growth in sales for the better placement to bring maximum benefit; you may be better served putting the popular product just below eye level and using that optimum shelf space for a product with greater capacity for sales volume.

Second, because the correlation between sale price and sale volume doesn’t even mention cost directly, but cost is a critical constraint on profitability, it can be worthwhile selling one commodity at a lower price even than the ideal in terms of profitability and pricing a more premium product on the high side. That’s a modern perspective, driven by studies in the economics of supermarkets, but the principle can apply to farmers markets of a more medieval nature as well.

And you can confuse matters even further with sales and discounts. These are often kept simple for the understanding of the buying public, but “ten cents off a dozen plums if you also buy a melon” can often be a more lucrative approach.

And then you have to factor in quality, both real and perceived. Actual quality pushes up both costs and the price people are willing to pay, but not as a simple addition that would be easily mapped onto sales charts – there’s a complicate relationship between quality and desire to purchase at a given price (it’s not a simple proportionate impact, either).

Perceived quality – a component of reputation in an industrialized setting, but largely independent of it in a more medieval society, where brand identities were subordinate to personal identification – pushes both volume of sales and price tolerance upward, at minimal increase in cost.

I once read somewhere that for every dollar spent improving a product, you should spend $10 telling people about it, but I think that’s more an aphorism of perceived wisdom in the 1970s and 80s than it is a useful guideline – word of mouth is still a thing, and some companies are adept at various forms of free media. I do think the general principle would still hold true in pseudo-medieval times, but the ratio is likely to be 1:1 or less.

Even today, I think the principle is correct but the ratio is not to be relied on save at a global level of development budgets vs marketing budgets, and not at a product-by-product level – and even then, 10:1 seems extreme. Between 2:1 and 5:1 seems far more persuasive to me as a realistic set of numbers. But such marketing aphorisms often exaggerate to get the point across (like everything else in marketing).

Ultimately, there are so many interlocking variables that an informed best-guess is probably the best that you can do in terms of setting an initial price point, and actual measurements of revenue vs price carried out over a period of time used to tweak prices toward the optimum.

Modern production methods also make for more consistent price levels; there would have been a lot more variability in market prices in a pre-industrial era, and seasonal factors probably outweighed everything else, also affecting factors like perceived quality.

Don’t get that last point? When a product is in season, quality perception sits at a different bar to when things are late-season, early season, or off-season. Something that you wouldn’t give a second glance to at season peak might be seen as very high quality in the off-season – so quality expectations are a relative thing.

One final point before I move on: What about our Iron example? Quality there won’t change as a function of the season, there’s no such thing as an “iron mining season”. But I would contend that seasonality is just as important in this product space as in any other – the season might impact mining costs, it might impact how hard workers can or will labor and so impact yields, it will impact transport difficulties and costs, and so on. As a result, even if no-one thinks of it in those terms, there would in fact be an “Iron Ore Season” in every practical sense.

Costs

Before you can properly evaluate what price to sell at, you need to calculate your total costs, and that can be a lot trickier than many people imagine.

There are costs per commodity, like the purchase price. There are costs per load, such as drivers and guards. There are costs per trip, like wagon maintenance. There are costs spread over many loads, like the purchase price of a new wagon (or the repayment of a loan to permit the purchase of this one). There are all sorts of license and permit fees. There are tolls. If it’s available, and your sensible, and can afford it, there’s insurance. And there are taxes and import duties and the like.

If you’re a retailer, you have often-overlooked items like shelf space and product positioning (which has been mentioned already) on top of all of the above. You may need to woo vendors and suppliers, creating entertainment expenses. There may be bribes and protection money. There are staff wages – possibly including your own. There may be advertising and marketing. You may need to hire spies to watch an opposition. There will be guards, often hired from a specialist organization.

Each of these is more complicated than it appears. So you may also need bookkeepers and accountants and a paymaster.

To see just how complicated things can get, let’s simplify things down and consider a single wagon-load.

An example wagon-load

Alphonse has been hired to transport 12 cases of vintage wine to the city 100 miles away. It will take him one day to load the wagon and one day to unload it, and he can travel about 20 miles a day, so the total length of the trip is going to be 7 days. Alphonse owns his cart outright but has maintenance costs to pay, or (more specifically) a small amount of cash that he has on hand to pay for repairs when they become necessary. His wagon is drawn by two horses who are nearing retirement age, so he’s saving for replacements. He will have to pay three tolls along the way – one to enter the city, one to cross a bridge, and one to pay a ferryman. He needs three guards, and he has to pay them well and hire the best he can find. He drives the wagon himself, but he needs a relief driver in case he falls ill. He needs a cook, who will also serve as a medic. He hopes to be able to buy a second cart sometime soon, and so is training an apprentice, but he’s not experienced or skilled enough, yet, to act as the relief driver. He has to buy and carry food and water for his people and fodder and water for the horses. Every trip, he pays a blacksmith to check the horses and replace any horseshoes showing signs of significant wear. He has to allow for a sales tax and a luxuries tax and an income tax, and he also has to pay a fee for each of his workers to safeguard them from being pressed into state service. He has to pay vet bills for the care of the horses. Twice along the route, he stays at inns, which cost money for himself and his crew; the other three nights on the road, they have to rough it. He has to provide tents, and cooking equipment.

12 cases of wine only fill his wagon 1/3 of it’s capacity. Tools and personal effects and other items for use along the way fill another third of the available space. But that still leaves a significant amount that’s not earning any money, it’s just dead weight.
The bulkier a commodity is, the more space it takes up, and the heavier it is, the more carrying capacity it consumes. Spotting a wagon that is carrying high-density items, and therefore is not packed as high, increases the risk of interest on the part of bandits. Riding unusually high (lighter) or low (heavier) can indicate the presence of gems or gold, respectively, and disposable wealth always gets the attention of the more attentive low-lifes.

The only available commodities that could fill that space are low-profit cargoes like wheat or timber. To make a decent return, multiple cargoes will be needed to fill the space. Each with a different weight, a different volume, a different cost, and a different profit level. That’s complicated enough on its own, but then you have to factor in the value of position – if there’s a commodity that can be sold at one of the intervening stops along the way (for a profit) and then replaced, that ’empty space’ becomes even more profitable. There are umpteen jillion combinations of cargo and quantity, and the conveyor has to pick the one that is most likely to be the most profitable, without wasting a lot of time in the process.

The greater the diversity of products within that space, the less he’s carrying of whatever is the most profitable at the end of the day, but the more reliable the earning of some profit.

So that adds questions of supply and demand, not just at the destination, but all along the travel route. Assuming that ‘home’ is the city where the wagon is bound, and that the carrier brought a load out with him that he sold before loading the wine, he may have had the opportunity on that trip out to get a sense of demand that he could fill upon his return; the risk is that someone else will have filled that demand in the time in between. The closer to the far end of the trip, the less likely it is for that to have happened, so any knowledge picked up will be least reliable as he approaches his final destination.

There are endless possible outcomes. The trick is always to turn a profit, even if it’s less than hoped; anything more than that is a bonus. The wine itself is paying all the expenses of the trip save for the actual purchase of goods to fill the void, so that’s a lot easier to achieve than it might have been.

A barrel of apples, a cask of apple cider, a smaller cask of apple vinegar, a couple of bags of beans, a quarter-bin of pumpkins, six crates of shingles, a barrel of nails, 50 horseshoes, a small barrel of pig’s trotters in brine with a hidden compartment in its base to conceal half-a-dozen gemstones, and six live chickens in a cage, plus any eggs they lay en route. And six woven blankets of wool and four cow-hides and a side of beef – that last won’t quite fit and overload the wagon slightly, but after a day or two, enough weight in water and food will have been consumed to solve that problem. Plus 500′ of rope to tie it all down beneath a weather-resistant tarpaulin.

If the wagon owner can just get the wine to its destination, he will turn a profit, just the win and gemstones will make it a very profitable trip, even if he sells the rest at a small loss or just breaks even.

There are always more variables to take into account. The roads will be at their worst when the wagon is most over-loaded, so there is an increased risk of a breakdown of some sort that diminishes as he travels, for example. Is that risk worthwhile, or should he forget the side of beef or the barrel of apples or maybe the bags of beans? Those all act as low-cost camouflage, hiding the real source of profits from spying bandits, so they have a value beyond the obvious.

Minutia and an alternative

As this example demonstrates, Trade as an activity is all about minutia, and – most of the time – minutia is boring. A Traveler GM I know was so put out by this that he ended the campaign when the players decided to go into being traders instead of blindly engaging in the politics that he had set up as the centerpiece of his campaign; it was that incident that led to my writing the original Trade In Traveler article, “Buy Low, Sell High“.

A Mathematical Trick

I developed all sorts of tricks to speed up mental and paper arithmetic as a child because I had trouble learning, of all things, my times tables. Some of those tricks continue to serve me, well even today, and the principles that they exploit can be even more useful.

Let’s say that I have 20 numbers ranging from 1 to 10, as might result from a series of d10 rolls that have to be totaled to give 20d10: 2, 8, 8, 1, 6, 3, 9,10, 5, 7, 6, 9, 5, 4, 10, 1, 5, 7, 1, 1.

If I add the highest possible result to the lowest, I get 11, which is not very useful. But if I exclude the highest possible result and use the one below it, I get 1+9=10. And that is VERY useful for quick counting. So I partner the results up as much as possible and see what’s left over.

2+8=10
8+1+1=10
6+4=10
3+7=10
9+1=10
10=10
5+5=10
9+1=10
10=10

That’s 9 tens for a total of 90, and I have 6, 5, 7 left over. But I’m not finished yet – I take the highest and lowest of these leftovers, and add them together: 5+7 = 12. Which makes the final addition, 12+6, even simpler – 12+6=18. Add the 90, and you get 108.

This is even easier to do if you actually have 20d10 to roll, because you can physically move the dice into their ‘partnerships’. But even without that, with a list of numbers generated 5 at a time (the number of d10s that I happen to have gotten out), it’s easy – just cross the numbers off the list as you partner them, or use backspace / delete if your list is in an electronic format.

It’s faster than simply doing it as an addition, because it’s easy to lose count of how many dice you’ve rolled.

If I’m talking about d6s, the goal is still to make tens. Here’s 50d6: 1, 6, 1, 4, 3, 3, 3, 5, 5, 4, 2, 2, 5, 5, 6, 3, 1, 4, 3, 5, 2, 5, 1, 2, 4, 3, 5, 5, 4, 3, 4, 4, 5, 4, 1, 2, 6, 6, 1, 6, 3, 6, 1, 2, 5, 6, 5, 2, 3, 4.

5+5=10
6+4=10
3+3+3+1=10
4+5+1=10
2+2+6=10
5+5=10
3+4+3=10
1+2+5+2=10
1+5+4=10
3+5+2=10
4+6=10
4+6=10
4+6=10
3+1+6=10
5+5=10
4+6=10
3+2+5=10
4+3+2+1= 10

That’s 18 tens and I have a 1 left over – a total of 181.

A Cargo Standard

So, our commodities have 4 values that don’t change but that are different from one commodity to the next: Purchase Price, Quantity, Volume, and Weight. We also have Other Costs and Profit. Most of those numbers are relative to something – kg per bag or kg per 10 items or whatever. How can we repackage those numbers to eliminate some of these in favor of a more user-friendly description that has less minutia?

Volume

Let’s start with volume. Our cart has a fixed amount of it. If you divide that capacity by the commodity that takes up the greatest amount of volume per item, you get a relative minimum quantity that it can carry, and if you divide by the smallest volume per item, you get a maximum quantity. Neither of those are particularly helpful, but if you take the average, you can get a ‘typical quantity per load’. Is that of any more use? Not really.

What we can do is define a standard volume size, and package commodities by volume to fill that exact volume. To do that, we need to start with the volume occupied by the commodity with the highest volume per unit, and round that to a convenient number.

Or we can start by defining the volume capacity of a ‘typical cart’ and divide that by a convenient number to get a standard volume. Our actual cart will have a capacity of so many of those standard volumes. It’s a simple spreadsheet calculation to transform all of those volume-per-unit numbers into a value of standard volumes per unit – or take the reciprocal to get number of units in a standard volume, with a certain amount of space left over to fill that standard unit. And then we can partner that with another commodity whose volume per unit exactly fills the available space.

Weight

The typical wagon will also have a maximum load that it can carry before you start adding to the likelihood of a breakdown. If we divide that by the same number of standard volume as will fit, we get a maximum weight per unit. If we then use our spreadsheet, we could translate the weight of each of our partnerships into a certain number of those maximum weights per unit.

But here’s where my mathematical trick first shows up. We don’t care about the actual weight of any standard volume, so long as the average overall is within the capacity of our actual cart. So we can partner the weights per unit so that we achieve this overall average – a heavy standard unit partnered with 1, 2, or 3 lighter ones. There will be some that are a little over, and some that are a little under, but we’re packaging groups of standard units that will fit in the physical volume so that the weight overall is right.

This process can even be refined – if you’re 0.2 over on one pairing / partnership, you can take that off the next one that you’re putting together so that it ends up being 0.2 under. But that’s probably more detail than you need to go into.

A better approach is to ensure that each package of standard-units is as close to the desired value as possible without going over it.

So far, then, we’ve created standard shipping units that contain combinations that ‘fit’ the available space and weight capacity with specific quantities of a group of commodities.

Price and Profit

Price per item is known, so each of these combinations will have a total price. Profit per item is trickier because of all the different costs that have to be taken into account, some of which only affect specific commodities. Perhaps, then, it’s a good thing that the actual selling price is what a customer is willing to pay, which has nothing to do with either the purchase price of the shipper / wholesaler and the costs incurred. Instead of profit, we should be looking at revenue – the income that can be generated from selling the commodity.

Choosing the commodity package that yields the highest total revenue creates the maximum scope for profit after those expenses are taken out. We could even label it “Idealized Profit”.

That’s what the successful trader wants to maximize. In an ideal world, he would pack his entire wagon’s capacity with whatever yielded the highest idealized profit and be on his way. Unfortunately, it’s not quite that easy.

Compromises With Reality

Said trader has to accommodate two more limitations: Finances and Availability. The second is the more readily dealt with, so let’s do it first.

Availability

There might only be two units of the most profitable combination while the merchant has room for 8. So he picks those two and then looks at the next most potentially profitable units. If there are six of them available, that fills his wagon and he’s on his way. If there aren’t, he adds what is available and then moves to the third most potentially profitable, and so on.

That’s just common sense, right?

I’ll get back to that in a moment. First, we have the other compromise with reality to deal with.

Finances

Merchants frequently don’t have as much money to spend buying commodities to trade as they might like. Perhaps the most potentially profitable single commodity is Emeralds plus something cheap to fill out the unit – potatoes, maybe. But these cost 10,000 GP a unit, and the trader might only have 14,000 to spend.

So, even though there might be two or three such units available, the trader can only afford one – and maybe not even that.

To find out, he has to play a little game with himself. Deduct the price of however many top-profit units he can afford from his ready cash and divide what’s left by the number of spaces still to fill. The result is the maximum amount he can spend per unit on the remainder.

If the list of available consignments has been sorted in sequence of idealize profit from high to low, the job is simple – work your way down the list until you find the highest potential profit package that he can afford. Fill the remaining space with them – if there are enough available. If not, buy them all and repeat the assessment.

If you reach the bottom of the list without being able to fill your wagon, you then have a choice: run light, or assume that you can’t buy as many of the most expensive units as you thought you could. Reduce that quantity of units by one, and recalculate.

Eventually, you will end up with a full wagon-load that is as much profit as you can afford. The next time you come back, hopefully you will have a bit more cash to spend.

If that’s all there was to being a successful trader, there would be a lot more of them to go around.

Idealized Profits, revisited

What?s missing from the picture is allowance for the impact of supply-and-demand, and market knowledge. Both of these impact the idealized profits of the different types of unit on offer.

Demand for certain commodities rises and falls with the time of year and with the market environment. If there hasn’t been a supply of something that’s in demand – no matter what the level of demand is – that demand will rise, carrying the price people are willing to pay with it. If the market is oversupplied, demand will fall, and will again take sales price with it. You might know what the prices and supply were like a couple of days, or a couple of weeks, ago, but you have no idea what they are now, or what they will be when you finally bring your goods to market.

Some of the change depends on factors outside your control – what other traders have delivered a commodity in the meantime, for example, or a temporary hazard that means fewer such loads are reaching their destinations. Inclement weather and a hazardous river crossing can cause loads to build up, undelivered, while demand skyrockets, until conditions improve. And suddenly, there will be a glut on the market as everyone tries to capitalize on that pent-up demand. If you’re one of the early traders, you can do unusually well; if you’re late to the market, you can lose your shirt.

The one thing that’s for certain is that any ‘idealized profit’ list will bear only a passing resemblance to the actual prices at sale. Some commodities will be higher, and some lower.

In practical terms for the GM, they can either drive themselves nuts tracking every influence on actual sales prices – back to minutia again – or they can simply roll a bell-curved die roll and get a relative price adjustment which they then explain in narrative terms.

But just because a factor is outside your control, that doesn’t mean that its completely unpredictable. Market knowledge is a powerful tool that only the most intelligent can access. If there are a bunch of new homes being built, building supplies will increase in demand and therefore in price. If there’s a major sporting event coming up, the resulting groundswell of visitors will push up the demand for food of all sorts, and alcohol in particular. If the other team are from an area with a specialized cuisine, the ingredients for such cuisine will rise disproportionately relative even to the inflation of food demand in general.

If a particular bridge is rickety and old and in urgent need of repairs, it might be worthwhile going around it, even if it slows you down; while that might produce a short-term reduction in profits, sooner or later that bridge will fail, and you will reach your destination to find demand skyrocketing.

The more the canny trader knows about the world around them, the more they can use that knowledge to anticipate movement in demand and in price, and can then buy accordingly.

The GM Shortcut

All that fussing around with so much of this and so much of that comprising a unit can still be a lot of work, time that could more profitably be spent on something else. It’s still minutia, just a more generalized form of it. Is there a way around that?

The answer is yes, and it gives rise to a fundamental principle of making trade work in an RPG – any RPG, regardless of genre.

The GM sets the prices and the quantities and every other significant value in the process.

Some GMs use random die rolls to do so, thinking that takes the effort out of the problem. And they’re right, it does – but it makes more work and more minutia than you save, in the long run, and the removal of GM bias doesn’t make the system any more or less fair, just more chaotic.

Two die rolls are all that are needed. Two.

The first one sets the current market conditions if these are not already known / inferrable.

<0, 0 = catastrophically unfavorable, +2 to the second roll
1 = strongly unfavorable, +1 to second roll
2 = somewhat unfavorable, +1 to second roll
3 = slightly unfavorable / neutral
4 = slightly favorable
5 = somewhat favorable, -1 to second roll
6 = strongly favorable, -1 to second roll
7+ = incredibly favorable, -2 to second roll

The second one sets the trend, the direction things are going. The GM can add or subtract 0, 1, or 2 from this die roll to correspond to known external factors, plus there are the modifiers from the first roll.

-2, -1 = becoming strongly more unfavorable, -2 to the next ‘first roll’
0, 1 = becoming somewhat less favorable, -1 to the next ‘first roll’
2 = becoming somewhat less favorable, -1 to the next ‘first roll’, re-roll 5+ results on the next ‘first roll’
3 = becoming slightly less favorable, -1 to the next ‘first roll’, re-roll 6+ results on the next ‘first roll’
4 = market steady, no real change
5 = becoming slightly more favorable, +1 to the next ‘first roll’, re-roll 0- results on the next ‘first roll’
6 = becoming somewhat more favorable, +1 to the next ‘first roll’, re-roll 1- results on the next ‘first roll’
7, 8 = becoming much more favorable, +2 to the next ‘first roll’

These then become the foundation for narrative (which has to explain both the movement from the last ‘first roll’ and the current market trend).

The GM then interprets that narrative to set a general trend in commodities and pick out two or three exceptions going up and two or three going down. He then deliberately constructs unit packages with an eye to the implications of supply and demand from the narrative, and from that, can set availability levels.

Working backwards from the general picture of trade to the specifics of what’s available and what it’s likely to sell for saves an awful lot of work.

But it’s possible to simplify the GM’s job a little bit more, by considering group effects.

Group Effects

The principle of group effects is a simple one: events affect related commodities in a common way. As a general rule, you can treat all grains as a single entity, all vegetables, common meats, alcohols (except beer / ale, which often stands apart, and which may go down in demand when other alcohols like wine go up), and so on. If there’s a military conflict on the horizon, weapons, horseshoes, saddles, and armor will all increase in demand, and so will (higher-quality) cloth that can be died into standards and flags. And basic produce, like beans, hay, and oats. If there’s an increase in building, stone, timber, nails, panes of glass, and tools are all affected. And so on.

If only part of a unit is affected in this way, the proportion by cost price that is affected goes up, the rest doesn’t.

Fitting All This Into Trade In Fantasy

The main series deals with minutia of effects. It’s designed to fully simulate immersion by PCs into the world of commerce, where business activities are to be used as a springboard to adventures.

Sometimes, that’s overkill, because that’s not what the PCs have in mind at all – but the GM still needs to simulate the complex field of commerce within the game world. The PCs are hired on as guards for a wagon train of goods, for example – what are they actually protecting? And why does the wagon master need so many guards? Is the owner just paranoid, or is there something he’s not telling the PCs?

Or perhaps the PCs are employed to scout markets in remote places, searching for unusual commodities that might be valuable, and places where something or other seems to be in high demand. That could be a gateway to all sorts of adventures because it’s simply a justification for them going places they’ve never been before. You need some method of simulating trade to give the mission verisimilitude, but it should be as unobtrusive as possible.

That’s where the simplified system contained in this post comes in. You can make it as generalized as you want to – having standardized volume and weight, why not cost as well? It can be done in the same way, so long as you handle expenses separately.

There are some circumstances where this article is all you’ll need.