A theme widely spread and spoken that assumes different pillars and has generated great transformations in industries. But, have you, manager, used the whole potential that this concept brings to your operation?
In this article we present a clarifying interview with Matheus Anversa – CEO at Dojo Technology, where we explore the theme a little more, his perceptions on the usability of Industry 4.0 concept, from his broad experience with the Brazilian industrial market.
Current scenario
It can be observed, in a broader way, that the common pursuit across industries and the optimization of resources, processes, and people, to keep better performance in the different areas of the company, is intended to reduce costs and wastes, or to expand the market share, for example.
Doing more with less is what operations have sought, historically, and leads industries to a relentless pursuit for resources and technologies that will favor such condition.
The concept of industry 4.0 was mentioned for the first time in 2011, in Germany, at the Hannover fair, and was about a project that contained a set of strategies prepared by the German government focused on technological solutions. The Fourth Industrial Revolution, called Industry 4.0, started to be a widely explored theme in this universe, due to the breadth of solutions that favor better performance and solve some of the great pains experienced by industries.
“I like to look at the Industry 4.0 from a more integrative perspective, involving systems, IoT, and data, because, with that, companies become more analytical and have more operational efficiency. For this to be possible, the technological apparatus, which, in industry 3.0 was limited to physical systems, now involves virtual systems, support of computational clouds, with levels of integration, making possible the long awaited Artificial Intelligence across all sectors.
Artificial Intelligence in the industry favors the analysis and learning of complex scenarios, producing better results, and helping reduce risks of future decisions, due to the lessons learnt over time. In other words, factories become more intelligent, connected, with robots supporting the automated process, with capacity to generate learning. This is the industry’s wish and future, but there is still a long way to go in terms of analytical maturity in companies”, says Matheus Anversa – CEO at Dojo Technology.
In fact, the Industry 4.o can be considered as a set of integrative and enabling technologies that allow machines and humans to work and communicate in a collaborative way, favored by the society access to the digital world, transforming companies into Agile Industries.
This concept brings nine pillars, and each of them their technologies, which, together, complement each other to generate more efficient results.
The 9 pillars of the Industry 4.0
- Big Data Analytics
- Robots
- Simulation
- Integration of systems
- Internet of Things (IoT)
- Cybersecurity
- Cloud Computing
- Additive manufacturing (3D printing)
- Augmented reality
With regard to Big Data Analytics Pillar, data are increasing generated, in an unprecedented scale, whether by systems, sensors, social media, mobile devices, wearable tech, among others. The Big Data Analytics favors the capacity of analyzing them to improve decision making process, and is essential today.
Generating data alone does not make an operation more intelligent and efficient, but the professionalized centralization of these data, creation of robust panels demonstrating the information contained in these data, the possibility of learning and analysis of future trends in operations, generate confidence in managers in decision making, and monitoring of their operations.
Though it contains nine pillars, what can be observed in industries’ operations is that not all of them are the focus, as emphasized by Matheus Anversa.
“Considering my experience, the industry has invested a lot in robotization, for being a technological resource already present in industry 3.0. I dare say that it is one of the main pillars with more investments. Integration of systems and IoT are also in the agenda of investments of companies, some of them with high level of maturity.
The other pillars are starting to gain maturity, like Big Data Analytics, Cloud Computing, Cybersecurity, and some companies have already started investing in the past years. They emerge at moment of understanding what makes sense to the businesses, because not all pillars must be addressed with the same intensity and investments.
Some of them are essential to ensure business sustainability, like systems integration and Big Data Analytics, since decisions must be made in faster and more assertive way.”
Managers seek effective solutions
Regardless of the moment of industry or the technology chosen for the moment, it’s common opinion that the path to solve pains of processes, predictability, and results, is long, because these difficulties are present in the routine of managers, and need higher investments to reach higher levels.
Though investing more widely in software for alignment of processes, it is still very common the use of spreadsheets to complement data collection and provide some type of analysis. As addressed in the article “I hired software! Is that enough to manage information?” (“Contratei um software! Isso é o suficiente para gerenciar informações?”).
Technologies emerge to solve daily problems of companies. Where well applied they supply operational needs and open room for managers to focus their energy on strategic themes. This synergy makes business more intelligent and profitable.
Anversa also mentions the constant need of reinventing themselves: “A new era, caused by constant evolution of technology, added to economic acceleration and new market dynamics, made century-old companies reinvent themselves to survive, since technology companies arise developing products and services to the market and expanding in an exponential manner.”
With this new market dynamics, some problems that did not exist emerged and industries started to seek resources that provide support.
See below some points observed in Matheus Anversa interview:
- Integration: companies need to integrate the whole production and logistic chain to understand bottlenecks and improve delivery time for customers. The industry 4.0 enables the integration of systems, generating increase in productivity and customers’ service level.
- Product life cycle: different from previous decades, when products had more extensive durability, like for example, washing machines that lasted for decades, products started to have shorter life cycle due to technological advances of new products. It also enabled prediction of problems in production line to follow products’ life cycle. The industry 4.0 addresses this problem with predictive maintenance, and improvement in products’ quality, avoiding defects to be passed on to customers, in addition to better provision of stock and impacts on the chain.
- Interaction with customers: customers from a conventional industry have their last contact with the company at the moment of the product delivery, and many opportunities with these customers are lost. With the Industry 4.0, initiatives like service automation using chatbots make possible the personalization of the customer experience in different channels and creation of personalized service strategies. Moreover, understanding behavior patterns over time makes the capacity to anticipate the customer’s needs a reality, enabling the offer of the right message or product, to the right person, at the right time.
- Future predictability and better analysis of scenarios: since the market speed changed, being reactive ended up by becoming a big problem, since post-decision actions have their execution time. Companies that used data analysis to justify their actions no longer have time for that, because wrong decisions’ impacts are immediate. With the industry 4.0, the power of data makes companies increase their analytical capacity and use their operation as a joystick, because they can simulate scenarios, increase future predictability, in addition to understand decisions’ trade-offs. Anticipating the future becomes a reality that generates operational efficiency and more profitability to the business.
The solutions indicated as priority at this moment in industries, are solutions that provide deep and realistic data analysis to managers. With correct information, from their own areas, they can observe trends, predict future scenarios, and so make more assertive decisions.
The solutions offered by Dojo Technology are exactly what industries seek today. These solutions initially innovated in aspects like robotics, cloud, or systems’ integration, for example. With so many data collected, efficient ways of looking at them are necessary, and so, solutions like well structured dashboards, with data centralization make the difference. Data only become efficient when transformed into analyzable information.
What can be observed is an increasingly number of managers seeking these advances in their areas, and working to raise awareness of the need to use data in favor of results. Some companies have already started this process and count on solutions implemented, and, while observing the benefits, they seek dissemination and expansion of the data culture.
Matheus Anversa also observes that in operations where Dojo has led the data theme it’s possible to notice how leaders can quickly perceive the value of deliveries of solutions, and thus expand the project to other areas. In the interview, he highlights the model he has focused on, and the satisfactory results obtained in industries where Dojo works:
“Dojo is positioned more as a business company than technology itself, because it counts on CRISP-DM methodology maturity, which enables co-creation of solutions for data analysis directly linked to clients’ business goals. I like to look at Dojo work as a form of moving the pointers of the clients’ results. That’s what grounds the commercial strategy, and how the development team works, and the process is end-to-end advisory.
In this regard, our corporate attitude is direct and realistic, and does not use the current Artificial Intelligence market Hype, because, to reach this type of work, there is a journey of increase in the analytical capacity. That is, for some clients, a simple Dashboard with analytical view instead of report view has already produced great results.
Our methodology has generated important results to our clients, as can be shown in some cases:
- Simulation of capacity in S&OE process: this project brought improvement of 40% in operational efficiency with increase in capacity of analysis at level of granularity that crosses SKU with bottlenecks and raw material stock, in automated way and with intelligent routines.
- Price distortion solution: an algorithm was developed using neural networks to understand all variables (for example: technical capacity of compressor, client, size, sales volume, etc.) that may impact on the price, and with that a suggested price was created so that marketing and sales areas can adopt commercial strategies to increase the company’s billing. The project generated 5.2% increase in billing.”
Demystifying managers’ needs
The market maturity with regard to use of data to improve performance in industries is still low, because it is a “new” subject in this context.
Industry leaders have many questions like “how to start?”, or “how can these data solutions help?” In this respect, a work of market education and more simplified initiatives became predictive so that they can learn with the journey, incorporate in their cultures these initiatives, and for operation to acquire maturity to advance with this technology and finally obtain better results.
Matheus tells us what he is experiencing in the market:
“Initially we believed that the market needed to govern more data for this asset to increase its value over time, and that analyzing data was already a quite common practice in the market. Today I understand that the market knows about the need to increasingly use data in the decision-making process, but doesn’t know exactly what to do or how to start. That’s why working on data programs and strategies is not about technology, but rather about people, education, and co-creation. Thus, I believe that managers need to seek partners that use simple language but help them in business questions that need to be answered and the possibilities that Analytics can bring as support to the decision-making process. Once the analytics world is connected to the company’s processes, the game becomes about what lever to move to improve results and how data will show the way for managers to make decisions in a more assertive manner” says Matheus Anversa.
At Dojo Technology we seek the best solution to each manager of each area, in each company. We understand that despite the similarities across operations, needs are very particular and so, ready solutions or dashboards built without specific focus on daily bottlenecks not always bring the expected results.
With the in-depth identification model in the greatest problems experienced by the manager in his/her area, it’s possible to customize solutions, so that in an agile and practical way, initially, the manager can visualize the current scenario and make decisions that will reduce risks and improve performance.
