A determining factor in the success or failure of a project for the creation of a simulation model is certainly the degree of knowledge of both the business context and the software to be used, which clearly identify two different set of skills.

The first category of skills, related to the business dimension, often includes a mix of professional figures, partly relating to the business object of the simulation (e.g. supply chain manager, operation manager, etc.) and partly coming from specific professional fields (such as universities, research, consultancy firms, etc.).

Moving on to the second category of modeling skills we need to make some clarification: everyone has modeling skills, as our brain leads us to reason daily with patterns and models that we learn over time.
However, in order to correctly deal with simulation, the need to seek for a very analytical and objective approach arises. The objectivity requested to the modelizer is usually insufficient in those who live daily in contact with the reality or problem to be modeled. This is precisely due to the “contamination” that reality exerts on our perception: a person accustomed to work and operate according to a certain scheme and with a predetermined set of information will most likely tend to model reality according to his/her own mental scheme.

This type of cognitive bias can be particularly dangerous when modeling complex situations, where the imposition of a partially objective modeling scheme can lead to overlooking important variables or links that have a non-negligible effect on the outcomes of interest.
Therefore, when taking about creating the conceptual model, it is best to rely on external experts who, based on the experiential support of the business people, are able to analyze the situation “from the outside”, guaranteeing the correct threshold of objectivity required for the analysis of the problem .

The ability to rationalize and objectify the problem or reality is often acquired through experience in carrying out simulation projects: the need to translate processes, resources and information into virtual objects through the use of technical resources (software, programming, etc.) leads the modeling expert to develop the right mindset over time and to understand how to represent any situation (real or abstract) with the right technique and above all with the adequate effort and level of detail.

In summary we can conclude that the resources necessary for the correct implementation of a dynamic simulation project must involve a small number of modeling experts (variable based on the extension of the perimeter) and a fairly varied audience of actors belonging to the business world, in order to capture different aspects and particularities of the situation to be modeled.

The topic of technical simulation skills inevitably opens up the discussion of the tools necessary for model development.

At the state of the art, there are various software applications that allow even users who are not experts in IT and programming to develop simulation models. Obviously these applications must be managed by an expert user in order to create a model that is reliable and usable as a decision support tool.
We recommend to practice by starting to develop simple models and then increasing and transferring knowledge into the business environment.

For what concerns hardware, for a generic project of medium complexity it can be easily managed on a personal computer with standard performance, as simulation software usually requires as its main requirement the availability of correct RAM memory to be able to operate and iterate all the variable calculation steps.
This lead us to conclude that the software and hardware aspects of a simulation project are not critical, making it manageable on traditional platforms (such as personal computers).

It should also be noted that the license for the use of simulation software for professional and/or commercial purposes has a fair cost and its purchase by a company it is not always justifiable. For this reason, simulation projects, at least in the first applications, are usually outsourced to consultancy companies or professionals capable of providing what is requested with a reasonable effort.
In the most advanced and widespread applications, where the simulation model is usually used to interact directly with other company information systems, it may instead be necessary to purchase one or more licenses of the simulation software to enable company users the operability on the model(s) realized.

In summary we can conclude that for pilot projects in the field of simulation or in any case for applications with limited complexity, it is best to outsource the design and creation of the model as the implementation effort is lower than the cost of acquiring licenses and skills.

On the contrary, when opting to include one or more simulation models within the corporate digital strategy that must be used on a regular basis or which involve a high degree of integration with the technological infrastructure, it is better to acquire or build the appropriate skills in the company.
This objective, which is much more difficult than the development of a model, can be achieved with the assistance, in the initial developments, by professionals/trainers who can teach resources the rudiments of simulation modeling as well as how to design the necessary models.