SWOT Analysis on Relevance of Industry 4.0 in economic downtrend

Manufacturing being one of the major industries, Economy of many countries rely on their manufacturing industry. It defines competitive edge they have from other countries in terms (employment creation, skilled labor, technology and infrastructure).

SWOT Analysis on Relevance of Industry 4.0 in economic downtrend

Is spending for Digital Transformation & Industry 4.0 required when the markets are not doing well?

Manufacturing being one of the major industries, Economy of many countries rely on their manufacturing industry. It defines competitive edge they have from other countries in terms (employment creation, skilled labor, technology and infrastructure).

The new revolution that has begun globally is Industry 4.0 where the largest industry – Manufacturing, is being Transformed using Technology to improve Production, Quality and Equipment Reliability.

There is question which is constantly being heard on how Industry 4.0 is relevant today and how important is it when the many analysts have been talking about the occurrence of a global economic down trend.

Here we are showing a SWOT Analysis on how Industry 4.0


• IoT enabled devices are a subsection of digital transformation adoption, bringing these products on to an organization’s existing network is not as simple and any network issue can disrupt the whole system
• IT is very expensive investment for the company and sometimes a company many are not able to forecast the ROI right and end up getting bankrupt due to loans made for the implementation of Industry 4.0 in their manufacturing plant.
• The IIoT can be a powerful tool to help manufacturers address their most pressing issues and take their operations to new heights but Small and midsized manufacturers face many challenges today as competitive pressures mount and cannot benefit as much as large manufacturers.
• One of major the problem is loss of employment due to automation implemented in their industry. This will majorly affect the low skilled workers due to the advancement in technology
• The disadvantage that both AI and IoT share is yielding unemployment. These technologies take away mundane jobs, which is nothing less than trouble for less educated or low-income level people
• IoT enabled sensors collect the raw industrial data from various parts/sector of the enterprise. This data is very complicated as it can be structured or unstructured big data with varying dates. Thus, a complex relation lies between the data of different sectors. In order to use the data for the organizational benefits, operational teams cannot correlate the data.
• IoT solutions deployment is that they are going to be valuable in the long term, but it takes time to get there. Organizations roll-out IoT in pockets of their businesses and expect immediate value but this is normally not the case.


• Hacking is the biggest vulnerability to an IoT platform. It still lacks the preventive measure for strong cyber-attack. It’s a massive loss for the organization if the data is stolen as they will lose their competitive edge.

• It’s not easy to classify IoT data breach consequences for companies at large because the ramifications vary depending on the type of device infiltrated.
• A lot of manufactures are still in the world of traditional methods and believe in human efforts rather than adopting to the automation technology.
• Integrating of data and receiving all the data in a central command center is easy part, but when it comes analyze the data and make sense out of it a lot of companies struggle there. It is very easy to go wrong in setting the trends and report for actionable insights.
• As an effort to implant recent technology onto former, it encounters a wide range of dissimilar standards and design principles in each entity from transmission protocol to other actors in the IIoT eco-system


• Virtual prototyping has tremendous potential in creating a new product or service digitally, simulating its operation and surroundings even before it exists, not only saves costs, but removes a massive barrier to innovation and it can be highly precise
• New trends of data can help manufacturers to quickly capture, cleanse, and analyze machine data and reveal insights that can help them improve performance.
• Considers analysis of the collected data for the earlier detection of the occurrence of possible machine failures and supports technicians during the maintenance interventions by providing a guided intelligent decision support.
• To use a higher level of profitability and labor productivity in manufacturing industries according in order to form the new leading markets for goods and services. The creation of the markets for new goods and services (robotics, electric cars, drones and others) and significant transformation of the industrial sector of the economy, just as it is currently happening in the digital media and trade sectors through introduction of the Internet technologies;
• There is a new technology entering the market every day, it’s safe that we can expect a better automation and data integration technology can come into play in the manufacturing industry sector and change the dynamics of how things are functioning now.
Digital transformation will only continue to grow and expand in the coming years. Industries must get prepared for the future work which contribute to the upskilling of the modern workforce.
• With the new interpretation of data and customization of data into analysis opens a new door of possibilities. This gives the organization a possibility to enter a new market.


• With all the real time data from equipment, the predictability of unscheduled maintenance and reduction of downtime improve the productivity of the equipment’s
• Predictive maintenance helps reduce any damages or unscheduled maintenance which will decrease expenses and real time monitoring will help increase quality control and better waste management, as this will reduce the cost of purchasing extra raw material.
• Industries are losing lots of money on returned and damaged products. Industry 4.0 can reduce or eliminate those costs. Real-time monitoring and quality control allow data to be collected from every point of production. This helps determine and control the conditions that affect the quality of products while production is in process
• Implementation production of individual and customized goods at reasonable prices will contribute to the growth of customer satisfaction.
• Increased product adaptation and product variety will contribute to development of new business models which will use cutting edge data technologies to offer new services.

Industries today are constantly investing in ways of improving their production counts, better quality to meet the growing demands of customers while being competitive. Maintaining an expensive supply chain with low margins is not promising for industries.

To make sure the gradually depleting bottom lines are stabilized and turn the industry profitable, every industry will soon be adapting technology (may be gradually though) so they can reduce their wastage, improve equipment availability and control their production stats.

When Markets Slow Down, we need to strategize, plan, invest and implement better means to stay ahead of our competitors not just to make profits but also to be able to stay in business.