One of the major challenges for today’s industrial enterprises is and will be the increase in the amount and speed of change in the business and social environment. All of this is amplified by the fact that the human factor enters the decision-making processes with its experience, but on the other hand also with its slowness, fatigue, limited perception, procrastination etc. Companies try to minimize this stress, inefficiency and economic losses. Historically, there have been a number of solution methods. All of these methods have one disadvantage in common, though. They do not eliminate the instability of the weakest link = man. The stress and chaos are deepened by the fact that man is forced to reconcile two different phenomena, digital and physical technologies. This creates errors, or at least time loss. 

Digitalization of company processes is not about saving paper and ink costs, or about saving work when entering incoming invoices into the system, or about replacing some of the missing workers with a collaborative robot. It’s about the way people communicate with their environment. Digitalization is about obtaining a sufficient set of data and converting it, if possible, into relevant information in an automated way.  

Therefore, another, conceptually new vision of process management in companies has emerged, which of course does not take away the human right to decide, but tries to improve his senses and accelerate it by presenting him not only with information about reality, but mainly about the expected development and offering him causal alternatives for solutions. We call this deep digital transformation – transition from a state, where products are primarily realised by physical machines controlled by humans, to a state, where production processes are algorithmized and production takes place based on algorithmized data processing. The solution may be compared to a sport tester, which is calibrated to your optimal performance and which warns you in advance about risks you may not even be feeling yet. It forces you not to make mistakes and gives you time for a well-considered reaction. This phenomenon is called Industry 4.0. 

The result is a virtual model of the company, which we call the Digital Factory. If scheduling takes place in the physical factory and then the actual state is monitored only at selected moments, then the digital factory is actually an avatar that lives the life of its physical double. But this digital double works with a much larger set of data. It uses even data that are collected in a standard enterprise but seem irrelevant from the point of view of using the information in the ERP. “Symptom, cause, effect” links are then created over the complete data in a digital factory using artificial intelligence algorithms. These links are monitored and subsequently used for managing the company. The effect consists in the fact that based on prediction of future development, it is possible to minimise deviations of reality from the optimised plan. This will reduce unproductive time losses. The volume of produced product will increase, realised profit from sale will increase, while non-current costs will be diluted.

The charming thing is, moreover, that implementing a digital factory does not mean the necessity of providing any fundamental procedural or other changes. The digital factory is a useful parallel mirror, not a parasite hard-wired to the company’s management system. 

The transition to this new concept should be gradual and follow the backbone processes of the company. In the first stage, it should focus on the dimensions of capacity planning and provision (human and machine), monitoring the availability and movement of material and monitoring the condition of production assets (predictive maintenance). In the next stage, it is advisable to focus on master data, and finally on supporting processes of the company.

At the same time, digitalization and the use of artificial intelligence are beginning to change the situation in another area of business, consulting. A new area of expertise is emerging here, and major market players are responding. New partnerships and alliances are emerging, often involving major consulting companies working with emerging AI specialists. An example of this is Grant Thornton consulting company, which is cooperating with the relatively young company Cerebrica in the area of digitalization and the use of artificial intelligence.

Petr Horák
Manager | Advisory, Business Risk Services
T +420 604 513 426
E petr.horak@cz.gt.com