Effective virtual simulation

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We simulate various situations in our lives every day: which route to take to work, where to go on vacation, what to buy for the office, and so on. By playing out various scenarios and their outcomes, we settle on the most advantageous option for us. The same is true in business: simulation models are a research method that allows you to build process models in such a way that you can play out several ways to solve a business problem and find the best one. This allows you to choose the most suitable option, avoiding the loss of resources, the main one of which is time.

Digital twins are used in various fields and sectors of the economy: energy, retail, industry. This approach allows you to reduce costs and increase income. The effectiveness of digital twins is content writing service especially clearly seen in logistics: companies use a large amount of physical data related to navigation, road infrastructure, cargo movement, and employee performance. And based on this information, they create models for evaluation and predictive analytics.




One of the classic examples of using a simulation model is moving a terminal from one location to another. To do this, it is necessary to collect the parameters of the future warehouse in advance, calculate the expected load, check the throughput, and calculate the required number of personnel.

Or the company is thinking about opening a new warehouse, and it is simulation modeling that allows one to understand whether it is worth doing. Perhaps opening a new division will be unprofitable and it is better to transport cargo from point A to point B? In this case, it is necessary to calculate the maximum efficiency of transport use and only then make a decision, because a new warehouse can be built, but part of the premises will be idle, or the terminal may not be enough for the predicted cargo turnover. Or the company is planning expansion into a new region - here it is necessary to calculate the effects of traffic redistribution and cannibalization (reduction in sales of an old product due to the introduction of a new one).

As a rule, it is much cheaper to test a hypothesis on a digital twin than in real life.

This is a fairly complex mathematical process, but as a result, the costs associated with testing on a simulation model are an order of magnitude lower – and this provides a tangible economic effect, as well as reducing time.