If you sell widgets you often have a choice about how to price them. You can fix their price or you can engage in differential pricing. Differential pricing, i.e. trying to charge customers more or less depending on how much value that customer thinks he will get from the product, has the benefit of increasing the number of customers you can reach. For example you can reach thrifty, poor, low usage customers. It has the deficit of raising transaction costs, for example some customers will spend additional time shopping for price. The more the buyer is aware that approximately the same goods are available at differing prices the more resource he will likely spend shopping. Note that any time the buyer spends shopping tends to imply a lack of trust. Lack of trust implies a risky market.
Standards are a way that industries can engage in collusion or cooperation (take your pick) to temper the risk in a market for it’s participants. Here is a nice example of that. The auto-insurance industry needs data to set insurance rates. Each company has claims data which gives it a rough picture of the risk of insuring a given demographic. The demographic data available to one company is limited to it’s current customers. A company that insures mostly elderly people in Florida will have good data for that demographic.
To improve the quality of the data they pool their data. The pool is managed by a non-profit organization setup by the firms in the industry. That data then becomes the standard estimate of the risk of insuring a given car for a given class of individual. Some of this data is available on the web..
All this reduces the risk for the auto-insurance industry and leaves them to compete on other attributes: customer service, marketing, in-house efficencies. It also reduces the chance that one company will give you a better price than another since it standardizes the measures used thru-out the industry for sizing up a customer prior to quoting him a price.
Notice how the data pool is very similar to a standards body.
It helps set standard prices.
The data pool both reduces transaction costs in a market, letting it run more efficiently and lowering risk. It tends to shift the pricing from differencial to fixed.
The data pool lowers the need for firms to merge. Without it the only way to get a large pool would be to merge. Stated another way the data pool provides a way for small firms to collaborate to gain knowledge that only large firms might otherwise aggregate.
I got to thinking about this because I was seeking other examples of collaborative knowledge pooling. I.e. other than open source, where the source code is the obivous reification of the pool. Other than a classic standards bodies, where you find patent pools.
Peering contracts, say between Internet ISPs, look like fourth example.