One of the activities that every European project have to carry out is the development of an plan to exploit project results. This activity involves identifying project outcomes with the potential to generate revenue after the project finishes. This is usually followed by a business plan created with the most accurate information available. Like any business plan, problems arise at the moment of execution mainly because we do not have a guide that can tell us how our products could impact the market nor how the market dynamism could impact our new business venture.

In DIGICOR we are trying to minimise those future problems by simulating our business models under dynamic market conditions. Thus different DIGICOR memberships with different payment amounts, frequencies, and different access types are simulated.

In order to do this, a simulator was created using NetLogo where manufacturers and suppliers can join the DIGICOR platform with a certain probability. Once registered in the platform and after choosing membership type and paying, they can post and bid for calls for tenders. Supplier selection occurs and contracts are established in the simulated world. Those companies unlucky enough to miss opportunities or unable to received high quality bids, will eventually leave the platform and stop paying because they will not see any benefit in paying without getting any contract. Whether we want it or not, this is a common behaviour in any user, in any company, and in any market.

This dynamism allows us to be more realistic about what we could expect with current business models. It also helps us to determine the minimum number of users we need to meet the operation cost of the DIGICOR platform. Moreover, when the simulation uses the market size (number of manufacturers and suppliers) of our use cases, we can see whether there could be revenue indeed or whether the operation cost has to be minimised according to the target market size.

Further work along this line includes adding more specific DIGICOR outcomes/tools into the simulation so that business interactions based on those tools affect the acquisition of contracts and the decision to remain in DIGICOR as a member and keep on paying. Consequently, we will get data on how each tool performed economically in each use case, leading us to conclude that each tool is more tuned for this or that market.

One drawback of our simulations is that "all [simulation] models are wrong, but some are useful" (G. Box, 1978). This is a common principle in statistics that stipulates that no matter the level of detail we add in our simulation models we will still not be capturing the whole reality of the phenomenon we aim to recreate. But we only need a sufficiently simple simulation model to provide a hint that we are moving in the right direction.