Data Analytics and how to make the best decisions for your plant
by Lantek
Digital Transformation
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Data on operations, processes, logistics, personal data, financial data... Data, data and more data. Too much data. So much data, in terms of quantity and variety, that it can be overwhelming. What is the best way to collect and organize them so that they make sense? To know what to do with them, so that they boost the productivity and efficiency of the plant?
Alberto Martínez, CEO of Lantek
In addition to the other improvements proposed by Industry 4.0, Data Analytics is essential to exploiting the value of the information. Now, when I speak of value, and pardon the repetition, it is, in fact, derived from the data itself. According to a report by Forbes Insights and EY, based on the opinion of 1,500 executives from large companies worldwide, 66% of companies with a well-defined advanced analytical strategy improve their operating margins and profits by more than 15%. It is clear, then, that on the road to digitization, a significant growth opportunity is provided by the effective analysis of the information that we generate in our companies.
The challenge is, therefore, to be able to know how to structure all of this information so as to optimize processes, identify areas for operational improvement, and strengthen the relationship with customers; in short, to enhance business growth. Aided by specific software and other technological tools, data analysts extract, select, process, analyze and organize data in order to establish patterns, trends, partnerships, and follow-ups that help us to be able to make the best decisions possible at all times, using the most disruptive business model possible, in terms of production schedules, maintenance, processes, inventory management... all of this in real time, automatically, which in turn results in greater cost reduction.
Now, if that described above were not enough in itself, Data Analytics facilitates decisions made in advance. Said in plain English, it will no longer be necessary to have to send e-mails to the different departments so that they communicate some type of data to us that, if not located, would take a great deal of time to find. With digitization, we are able to be aware, for example, before the assembly has concluded, of whether the result is to be optimal, we can predict scenarios that could delay production and repair them, and even the machines themselves are capable of resolving potential problems.
Conclusion: data analysis helps to avoid missing any details involved with the production process.
How do we translate what the data tells us? As a starting point, let us use the analysis that they perform in the technological consultancy firm Principa, using the four types of Data Analytics:
What is happening? This is the most basic of interpretations. We visualize all of the data in order to carry out a descriptive analysis of the business, its products, and its customers.
Why is it happening? A second step of descriptive data analysis is to apply diagnostic tools to determine whether there are potential problems, so that they may be resolved.
What is most likely to happen? Here, the possibilities of Data Analytics in terms of prediction are significant. The probability of occurrence of some incidence, which we can in turn resolve before it occurs. This ability to predict allows for better decisions to be made.
What do I need to do? The last step is from the prescriptive model, in which an analysis is performed to determine what has happened, why it has happened, and what could happen, in order to make decisions together.
However, Data Analytics is merely one of the cornerstones of digital transformation. If we add the possibility of learning from the data (Machine Learning) and creation of an Artificial Intelligence, as well as to connect our plant with sensors (Internet of Things), or upload all our Big Data to the Cloud, then we will have indeed reached the apex of Industry 4.0.
Regardless of the degree of digitization of a plant, it is essential to be familiar with each of its processes by using data, and thus gain a competitive advantage, which increases profitability and helps us to generate disruptive business models. For those who are not able to take adopt to digital transformation on their own, this new Revolution favors collaborative environments. There is no excuse for us all not to transform and to become more competitive. Choose the leading partner in your industry.
코로나19 팬데믹을 겪으면서 객관적이고 정확한 데이터를 기반으로 한 의사결정의 중요성이 여실히 드러났습니다. 이런 데이터의 신뢰성과 품질이 필수적이며 결정 사항을 정당화하고 가치를 추가하기 위해 어떤 데이터를 사용할지 정확히 알아야 합니다. 하지만 오래된 데이터를 그냥 사용할 수는 없습니다.
공업 부문은 경제의 경쟁력과 국제화를 강화하는 능력 때문에 국가의 성장을 뒷받침하며 견인하는 원동력입니다. 공업 부문의 활동이 다른 부문의 활동에 비해 두드러지는 강력한 효과, 이 부문에서 이루어지는 작업의 질, 끊임없는 혁신, 다양한 상황에 맞춰 빠르고 유연하게 적응하는 능력 덕분에, 공업 부문은 사회의 진보와 안녕을 결정하는 중요한 요인이 됩니다.