Technological advances and the improvement of industry 4.0 – the 4th industrial revolution – have transformed data management and analysis. Being updated, reliable and with good industrial management means having accurate data.
The 4.0 industry is the concept that comes with a great technological innovation in industries. The factories are now automated, integrated and controlled even through sensors or other devices. All this is already a reality thanks to the Internet of Things (IoT), among other technologies and systems.
The connection to the world wide web makes it possible, firstly, to remotely control the objects and, secondly, for the objects themselves to be used as service providers. These new capabilities of common objects open the way to numerous possibilities in both academic and industrial fields.
But only having this data is not enough anymore.
Now we have a huge amount of data. So what?
Big data is a recent term and therefore not found in most statistical dictionaries. They are multivariate and large data, usually created in real-time and show exponential growth (in time scale), named mega data.
The more data is generated, the greater the effort to extract information, and data centres have had to learn to cope with the exponential growth of generated data and have had to develop tools that go beyond relational databases and parallel database systems. Thus, the speed to get the information is part of the success that big data can provide in your company.
Take a look at more fundamental details about the big data definition:
- Volume: related to a large amount of data generated;
- Variety: the data sources are very varied, which increases the complexity of the analysis;
- Speed: Due to the large volume and variety of data, all processing must be agile to generate the necessary information;
- Veracity: The veracity is directly linked to how much information is true.
- Value: This concept is related to the value obtained from this data, that is, to the “useful information”.
Benefits of data for industrial management
Having understood the importance of data in general in the context of the new 4.0 industry, it is necessary to think further. What are, after all, the benefits of data for industrial management? How can this become a differential within an industry, regardless of its size?
To be aligned with the digital transformation, you need to look at data. Innovations like Big Data don’t appear to be just another technological term. They arise to help industrial management to be more effective, profitable and autonomous.
According to research by Pricewaterhouse Coopers (PwC), the use of accurate data in industrial management is already approved by the industries themselves. It was verified that 86% of the interviewed companies believe that they will have lower costs and more income in five years. This happens precisely because of the use of precise data in industrial management.
It is essential that the areas are integrated with each other and with the operational processes. Thus, it will be possible to monitor and optimize all production steps, ensuring greater competitiveness and efficiency in the industry.
Thus, when a good management system is incorporated into the other initiatives of Industry 4.0, it is possible to achieve greater competitiveness, including for small and medium companies.
Other main benefits:
- It reduces the probability of errors;
- It offers a subsidy for the future planning of the company;
- Production control;
- Management of stages;
- Autonomy to the machines in the power of decision;
- Traffic management;
- Production optimization;
- Assists in customer relationship management;
- Decreases costs;
- Increases productivity;
- Quick and accurate answers;
- Cross data between branches and machines;
- Simulation of the production and sales process.
How to manage data in the industrial sector?
First of all: what is data management? Data management is a discipline that aims to manage and care for business data, treating it as a valuable resource, so that information can be transformed into business value and underpin strategic decisions. And for that, data management uses processes, professionals, methodologies and tools.
Efficient data management crosses operational and financial information concurrently and finds gaps to reduce costs. A large part of companies’ waste goes through minor procedures that can be eliminated, saving time and money.
The technological tools are fundamental to integrate the company around a common goal: to have effective data management.
And this could lead to important steps over the process:
- Exchanging manual document and report preparation for an automatic generation – which makes everything much more agile, reliable and complete.
- Have more secure access to strategic data, since this type of software has authentication control.
- Information only reaches those involved with the process, avoiding leakage of strategic knowledge.
- In general terms, the commitment to information management is no longer restricted to the IT sector.
Now, this responsibility is distributed to the other business departments of the industries:
- the information must be controlled throughout its useful life cycle, especially when it is integrated into processes and no longer only during the development of methods and systems;
- data is estimated as an asset of incalculable value, but they are not the only relevant assets. Besides them, employees and finances are also indispensable for the companies’ effectiveness;
- information management needs to follow the same pace of evolution of the business segment and technology.
And how to manage data at a high level over the industry?
- Determine those responsible for the information
The first step is to determine who will be responsible for the project as a whole and for its various aspects. From there, this person can create a council that will formulate policy and report on progress.
- Identify the current situation
Before moving forward with changes, it is crucial to identify exactly what the current situation is. Our practices already being used? What are the existing devices? Are there control standards and quality indicators? By making this assessment, the company will be able to observe several points of improvement.
- Create a strategy
After the initial study, the board should lead a strategy for information management in the coming years. At this stage, it is very important that departments act in an integrated manner, choose a suitable infrastructure, as well as smart tools and rules. The decisions made will affect the business for the long term, so they should be the result of much study and reflection.
- Use the data in the best possible way
It is essential that the organization develops a culture of always using its information in the best way. Therefore, it is important to train each department to know the security standards, storage and records of data. This will reduce errors and increase reliability.
- Keep track of the results
Monitoring the results is the most important part of the whole project because it is from this monitoring that the company can make constant improvements. Currently, the information changes very fast and, therefore, data management must always be improved. See how each change has impacted the productivity and competitiveness of the business.
Finally, remember that good data management also needs a balance between strategy and practice. In other words, it means having good leadership decisions and, at the same time, implementing efficient tools. Good information management is one that provides risk reduction, cost reduction and, mainly, competitive intelligence.
Data management can become a competitive advantage
An important article from Harvard Business Review just went deep on how/when data could be a competitive advantage for a company. They have found 7 points to be aware of:
- How much value is added by customer data relative to the stand-alone value of the offering?
- How quickly does the marginal value of data-enabled learning drop off?
- How fast does the relevance of the user data depreciate?
- Is the data proprietary—meaning it can’t be purchased from other sources, easily copied, or reverse-engineered?
- How hard is it to imitate product improvements that are based on customer data?
- Does the data from one user help improve the product for the same user or for others?
- How fast can the insights from user data be incorporated into products?
When we take a look at this piece of content, then we can take good advantage of data management. It’s really important to have this clear: data management really needs to make things better within your company environment. If not, you are not doing it right (I mean it).