Manufacturing In A Post-Pandemic World

The COVID-19 pandemic has prompted the manufacturing units worldwide to reduce costs and increase supply chain transparency in the industry. However, the key to sustainable recovery is unlocking the benefits of the technology. It can include the advancement of the manufacturing process through data analytics and AI.

Apart from this, global manufacturing giants are intimidating other companies to collaborate on data for three main goals. These goals include an increase in productivity, enhanced customer experience, and reduced environmental impact.

The pandemic has raised the societal pressure on manufacturing companies, provided it was the hardest hit sector during the lockdown. However, with ease in the restriction norms, the industry is gaining a semblance of normalcy, and it is about time we minimize contact-sensitive practices in the various manufacturing processes.

It is now more than ever that we need data and analytics to disrupt the sector such that companies are able to unlock their goals sustainably. The article further highlights three primary ways collaboration around data and analytics can benefit manufacturing.

A Stellar Increase In Productivity
A productivity increase is imperative across the entire industry because, as distressing as it may sound, companies need to assuage for losses during the lockdown period. As a result, several manufacturing firms are already relying on data and analytics to increase asset productivity, labor efficiency, and optimizing net working capital by reducing inventory levels. With stakeholders demanding a legit answer for the setback suffered during the tightened restrictions, manufacturing firms worldwide have tried to take the challenge head-on.

For instance, workers are now getting an opportunity to operate world-class equipment to boost company performance and optimize asset productivity. Apart from this, getting a hold of the supply chain opportunities is equally imperative to ensure an increase in productivity collectively. A very current example of that would be Autosphere, which is one of the largest communities of automotive OEMs and suppliers that have come together to provide users with global visibility of assets along the supply chain.

The community utilizes a standard set of processes that enables employees across the chain to share real-time data with accuracy. The visibility prompts productivity enhancement and also allows higher resilience by identifying weak links in the supply chain curve.

Manufacturing in the post-pandemic world is primarily data-driven, with contact-sensitive activities increasingly eluding the industry.

Enhanced Customer Experience
Manufacturers can also utilize data and analytics to improve customer experience by adding features that are one-of-a-kind. Such features can also become a product’s USP, which eventually makes them stand apart from the crowd.

Nowadays, customers are getting smart. Long gone are the days when a user used to follow herd mentality to buy a product. With high-speed internet comes high-information at every user’s disposal, which prompts them to choose better and eventually buy better. As a result, improving customer experience, even though your firm might not be directly dealing with end-users, is vital for your product to keep flowing in the supply-chain market.

You can also introduce the concept of customizing the products for your users or letting them verify the provenance of the goods. One such example to substantiate the argument would be personalized cancer treatments by Johnson and Johnson. The company has established an extensive ecosystem to improve outcomes for cancer patients. Their collaborative chain includes healthcare providers, suppliers, and laboratories which seamlessly enhance end-to-end data flow across all players, which eventually helps the patient’s case.

Sustainable Production Practices
Collaboration around AI and automation benefits society as a whole, especially when it comes to sustainability. Whenever companies and governments synergize their actions, firms can achieve sustainable results for stakeholders throughout the gamut. You could see a prime example of it through the efforts made by Volvo Cars. The company coordinates with its battery suppliers to verify the ethical sourcing of cobalt for its electric car batteries. As a result, company officials developed a blockchain solution to trace cobalt throughout the entire supply chain, with officials guaranteeing behavioral conduct and social values.

Similarly, another company that has been setting an example in the manufacturing sector is Austral Fisheries. The company has developed a disruptive network tracing technology in association with WWF and BCG Digital ventures to track fishes throughout its supply chain. As a result, company employees are able to transform fish as a raw item into a branded, traceable, and premium product.

Synergizing The Three
A single manufacturer might not be able to capture the benefits alone. However, chasing the ideal has always been the notion every company strives for. To better integrate data and analytics, manufacturers must commence a paradigm shift now. There is one thing that COVID-19 taught us, and that is a transformation in the sector is necessary. If you want to achieve your objectives, the pandemic prompted that you now achieve them sustainably.

If there is anything you must learn from the present scenario, it is that there is no time left in the future. It should be now, and the changes you are thinking of implementing must happen now. Apart from this, manufacturers must work together as a community to unleash the maximum potential there is in store for the industry. Together manufacturing firms can benefit from each other’s experience. As a result, shaping advanced analytics as a sub-niche within the sector is imperative for the manufacturing industry to function seamlessly even in the future.

History repeats itself, and so will this pandemic situation if we are not sensitive towards the environment. However, what must be addressed right now is the need to transform the sector so that the losses that companies suffered during the past months do not necessarily have to repeat and the industry has a future moving forwards.

A contact-less manufacturing unit is the need of the hour, and we must realize what all has been lost due to covid. Making mistakes is natural but repeating them is foolish. As a result, what looks of the manufacturing sector post covid is all AI-powered.