All entrepreneurial ventures--from a lifestyle business serving artisanal pastries and coffee from a single store to the innovator of the latest electric vehicle--need to set up a supply chain and manage relationships with their suppliers.

The lack of a single component may mean that the eventual product or service cannot be provided to one's customer, leading to losses far greater than the cost of that component itself: Think of the cost of coffee beans and microchips in our two examples above. The cost of having too many of such components (an overage cost) is therefore minimal while the cost of having too few (an underage cost). In situations like this, it is important for the venture to order more units than it needs to sell (and more so when it faces more uncertainty).

Theory suggests that the simplest contract between the entrepreneurial venture and their supplier, a wholesale price contract, will not achieve this outcome because neither party enjoys the entire margin from the transaction. This leads to less than the maximum possible total profit across the two sides and is thus inefficient. In contrast, "efficient" contracts--such as buyback (BB) contracts or revenue sharing (RS) contracts--which can achieve the highest possible profit and arbitrarily assign those profits across the two parties have been shown to be difficult to optimize: In situations like those described above, with high underage costs, people designing buyback or revenue sharing contracts typically choose suboptimal contract parameters leading to fewer orders than needed for maximum profits.

In a series of experiments, we found that the theoretically equivalent minimum order quantity, or MOQ, contract gives the best of both worlds. It is both simple and efficient. It leads to much less cognitive burden for decision makers than the complex BB or RS contracts and achieves the optimal profits that it should, because managers are able to select the appropriate contract parameters with an MOQ contract.

In recent years we have experienced substantial disruptions to supply chains due to an earthquake, tsunami, global pandemic, and geopolitics. Each time this has happened, the immediate reaction is to advise firms to have more inventory buffer to weather the storm. The BB and RS contracts, which lead to fewer orders encourage decision makers to do the opposite, and thereby exacerbate the problem. Using simpler contracts like the MOQ contract can thus help firms better prepare for supply chain disruptions.

A quick look at Alibaba.com will reveal that most of the products sold on the Chinese e-Commerce giant's website adopt an MOQ contract. When we asked about the ubiquity of the MOQ contract and asked whether this was an Asian phenomenon, the former Chief Operating Officer of a large global chain, Dominique Lecossois acknowledged that MOQ contracts are indeed ubiquitous in his industry and that this is the case globally. This speaks volumes as retailers' entire busines relies on procuring and selling goods via contracts with their suppliers.

The use of simpler MOQ contracts is a win-win on all fronts:

• The contracts are efficient and lead to theoretically optimal profits

• Managers can easily optimize its parameters and achieve those optimal profits

• There is little need for investment in complex algorithms to optimize these contracts

• They have the potential to alleviate the impact of supply chain disruptions

• The most experienced firms and managers use it regularly

While other, more complex contracts, may have some alternative merits in terms of how risk is split across parties, the added complexity can eat into those benefits in the absence of an investment in complex systems. For entrepreneurial ventures just starting out (and even large global businesses) the MOQ contract remains a favoured option.

See below collapsible sections for a description of each contract type discussed above.

The above findings are robust across sectors but the specific circumstances of a given firm or sector will warrant specific analysis. For insights curated to your unique circumstances, to make use of predictive models, for collaboration opportunities, and speaking arrangements, please reach out through the contact form.