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In Response to the Pandemic, Consider Re-assessing your Digital Portfolio

By Farid Bichareh , CTO, AASA, Inc. (Excerpted from IIC Tech Brief Digital Transformation in Manufacturing: Key Insights & Future Trends ) The global pandemic is shaping a different world. In this new world, despite the short-term decrease in demand, in the medium-to-long run, the COVID-19 digital transformation impact seems to be extremely positive.

Source: In Response to the Pandemic, Consider Re-assessing your Digital Portfolio

The need for organizations to transform and respond to an unprecedented change in customer behavior and market risks – with extensive digitization being one of the key enablers of such positive impact.

In response to the pandemic, longer term strategies and digital portfolios need to be re-assessed and re-prioritized and manufacturers need to accelerate their digital transformations to remain relevant and capture opportunities or risk their very survival. In the time of pre-COVID-19, approximately 92% of manufacturers were thinking that their business models would need to change given digitization. Studies from the same period indicate that the top 10% of manufacturer, grow revenue at two times the rate of the bottom 25%.

The difference in their respective approaches come into play among the top 10% manufacturers. Manufacturing technologies such as AI and automation, are adopted five times faster and strategies are put in place that give high confidence in the reliability of the data. One example is a global manufacturer that had implemented Digital Twin capabilities and AI tools to optimize its supply chain before the COVID-19 outbreak. They were able to access and analyze critical information quickly, enabling it to de-globalize and move supplies as close to production sites as possible, avoiding shutdown of a single production line for lack of materials or any other possible disruption.

This proves the manufacturers with the right digital foundation,adapt to crises quicker. On the other hand, the latest analysis after the 2020 pandemic shows that Internet of Things projects will shift the focus to Manufacturing and IIoT and in the comeback of industries. Thus, Connected Supply Chain, Connected Product and Connected Transportation will be leading the connectivity world.

Due to Covid-19, manufacturers think of not only resuming operations in a safe and responsive manner, but also in setting the groundwork for long-term resilience through the successful integration of IT and OT systems. Now the question is how the combination of technological capability and business impact can be successful and help the manufacturer. Many manufacturers will look for business impact in three levels:

  1. Immediate: Efficiency and cost saving
  2. Midterm: New revenue streams and customer experience
  3. Long term: Business transformation

While the technology provider’s response is in three levels:

  1. Immediate: Monitoring and reporting tools,
  2. Midterm: Control capabilities and tools
  3. Long term: Autonomy

Manufacturers will be looking for solutions that:

  • Directly solve the pain points
  • Can be implemented quickly (days and weeks, not months)
  • Have the potential for long-term, post-COVID-19 impact

IIoT and Connectivity

IIoT, as a critical part to digital and Industry 4.0 transformation, features the use of sensors to connect manufacturing equipment to IT systems, driving valuable insights about manufacturing operations and performance. With the proper sensors and analytics tools, manufacturers can capture and analyze data from every point in the manufacturing process, driving business benefits. Digital Transformation and IIoT are enabling manufactures to discover new information and make informed, predictive decisions about their operations and supply chains.

Cloud, AI

By passing manufacturing data to cloud-based analytics platforms for deep analysis and modeling of machine learning, they can benchmark operational performance to identify improvement areas and make predictions and proactive responses to future operational outcomes or industry-wide events. As a result, the adoption of cloud data which unlocks other innovative technologies and AI will be among top priorities for manufacturers.

MES, Monitoring and Dynamic Scheduling

With manufacturing applications such as MES, performance monitoring and dynamic scheduling, manufacturers can increase transparency into production and product quality, scale productivity, and adapt to shifting regulatory requirements without overtaxing existing resources. For example, many estimates show improved performance management though such tools and applications can boost labor productivity by 20% to 40%.

5G, Li-Fi

The use of wireless sensors, enabled through 5G and Li-Fi, in manufacturing environments makes it easier for manufacturers to collect and analyze real-time performance metrics about their equipment and labor. 5G and Li-Fi with low latency and greater bandwidth, accelerate the rate of data download, enabling the use of real-time data in industrial operations. Images and data can be downloaded much faster with Li-Fi and 5G integrated IIoT devices. As a result, data can be easily shared remotely. Li-Fi and 5G location system can also provide real-time track and trace capability, as well as accurate indoor autonomy such as autonomous indoor vehicles and navigation for true Smart Factory implementation.


While pre-COVID-19 manufacturers were a bit hesitant to take on large capital-intensive projects like automation, considering social distancing regulation, production line flexibility and increasing capacity right now, the payoffs of a workforce that does not take breaks, does not get sick and do not need training and insurance will be appealing to those with strong capital positions – enabling acceleration in efficiency during this time that will cut costs and boost bottom lines.

Smart Cybersecurity, AI, ML, Automated & Adaptive Network

With five times the increase of cybersecurity attacks, the manufacturing industry has become the reported the second highest rate of such attacks. In general, AI technologies can be used to help protect against increasingly sophisticated and malicious malware, ransomware, and social engineering attacks. Machine Learning (ML) can certainly provide an important component for cybersecurity in threat intelligence. Both can be applied to monitor and detect anomalies in the network and identify new threats without known signatures. Automation also allows for the monitoring of networks and automatic updating of defense framework layers, in addition to diagnostic and forensics analysis for cybersecurity.

The conclusion is that manufacturers must embrace a business environment where the focus will no longer be only on efficiencies and cost-effectiveness. Digitalization and IIoT solutions that boost responsiveness and resiliency have emerged as an even greater business consideration. Manufacturers must engage in renovation of their operations, including digital transformation and IIoT solutions. It is now more essential than ever to start this journey towards a more agile, secure, and productive manufacturing future.

The IIC Tech Brief “Digital Transformation in Manufacturing: Key Insights & Future Trends,” was designed to help manufacturing leaders keep pace with the rapid emergence of new technology. It highlights advancements driven by the IIC’s Manufacturing Industry Leadership Council (MILC), IIC working groups, and IIC members. Farid Bichareh is an MILC member.