May 16, 2020

Immigration in the manufacturing industry: understanding the landscape

5 min
Immigration in the manufacturing industry: understanding the landscape
Britain is the ninth largest manufacturer in the world, employs roughly 2.5 million people and accounts for 14 percentof business investment. The sector...

Britain is the ninth largest manufacturer in the world, employs roughly 2.5 million people and accounts for 14 percent of business investment. The sector creates jobs year-on-year and is heavily reliant on migrant workers both from the EU and outside the EU due to a skills deficit within the UK.

The government is under political pressure to reduce migrant labour in the UK and this will provide serious challenges to the sector. For example, in April 2016 the government introduced a requirement for non-EU nationals to earn at least £35,000 per annum to be eligible to settle permanently in the UK. This has implications for the lower paid (but not necessarily lower skilled) workers in the sector and it might make it more difficult to recruit and retain lower paid non EU nationals on a permanent basis.

As part of the trend to reduce migration and increase minimum salaries required for non-EU migrant workers in the UK, the government has also announced that they are going to scrap the ‘Tier 2 Intra Company Transfer Short Term Staff’ visa category. This will mean that migrants must use the alternative ‘long term’ category and companies must pay a minimum salary of £41,500 per annum. This poses a challenge for international manufacturers bringing employees from an overseas office to the UK to work on short term projects or assignments.

Brexit will undoubtedly impact the sector. While the weak pound following the Brexit result has increased UK manufacturing to its highest level in two years, the longer term outlook is far from clear. The sector will arguably be hardest hit by any moves towards limiting the free movement of people in the EU. This could create issues with sourcing the required labour in the manufacturing supply chain and in some manufacturing sectors such as food production. EU migrant workers constitute 30 percent of all workers. Changes in the labour market as a result of Brexit may also lead to wages being driven up due to limits of available EU workers who might be willing to work for lower wages. 

Impact of legislative changes

As the law around immigration changes so frequently, employers need to ensure that they keep abreast of all the upcoming changes in order to be proactive rather than reacting to upcoming changes. For non-EU nationals, employers can monitor salary rates offered to prospective migrants as well as existing migrants who might be making settlement applications. This will ensure that employers are not caught out by future changes and are able to recruit and maintain a skilled workforce. 

For the large number of current EU employees in the sector, employers can assist current employees to obtain documentary evidence of their immigration status. EU nationals who have been working in the UK for five years or more should be eligible to make an application confirming their Permanent Residence in the UK. For those who have been in the UK for less than five years, they could submit EEA Registration Certificate applications, which would act as confirmation of their right to reside in the UK.

Understanding the changing immigration landscape

Employers who sponsor migrant workers must comply with sponsorship duties and are accountable to the Home Office should they breach those duties. 

This can result in companies losing all their migrant workers and (if workers are illegal) the business premises closing for up to 12 months. The knock on effect is potentially delayed product launch or development, such as new drug or car model. The company’s value and reputation might also suffer.

Here are four ways to keep on top of sponsorship duties:

1. Keep ‘genuineness’ at the top of your list

Inflating a job description so that an individual can be sponsored, or incorrectly recording their salary in immigration documentation might never be detected, but if it is, your sponsor licence could be revoked.

2. Know what to report and when

Sponsors need to keep the Home Office informed about changes to their circumstances and to their sponsored migrants’ circumstances. There are very strict deadlines and adverse consequences for failing to meet them.

3. Keep compliant records

The Home Office can visit a business premises to perform an audit without notice and will assess your compliance with sponsorship duties. Keep accessible records for all sponsored migrants containing copies of documents relevant to their visas.

4. Undertake proper right to work checks

Always (1) obtain, (2) check, and (3) copy the original document permitting the individual to work in the UK. Do this for every worker, not just migrants. Sign and date the copy.  

In addition to a possible £20,000 fine (per illegal worker), the maximum prison sentence for employing an illegal worker recently increased to five years. Liability can arise from knowing or have reasonable cause to believe that a person does not have a right to work in the UK.  The Home Office can issue an ‘illegal working closure notice’ and can close business premises for 48 hours. This can be extended to 12 months with a court order.


Home Office reforms

Manufacturing is hugely important to the UK economy in terms of exports, employment and business investment. The Home Office has made many reforms over the past few years. Recognising various job shortages in the UK (many in the manufacturing industry) has been beneficial to companies. However, other reforms make employing migrant workers more difficult and more expensive and the ‘tens of thousands’ net migration target is still in the minds of many policy makers.

It is clear there is a manufacturing skills shortage in the UK. To help the UK secure its place as a top global manufacturer, companies must be able to hire the right people for the right jobs. A collaborative approach could see companies to work with the government to identify important areas of skill and implement policies to create a skills development initiative under which migrants could perform their job role and train the local workforce.   


Neil Jennings and Sam Koppel are Associates in the immigration team at Lewis Silkin LLP


Follow @ManufacturingGL and @NellWalkerMG

Share article

May 11, 2021

5 Minutes With PwC on AI and Big Data in Manufacturing

Georgia Wilson
6 min
PwC | Smart Manufacturing | Artificial Intelligence (AI) | Big Data | Analytics | Technology | Digital Factory | Connected Factory | Digital Transfromation
Manufacturing Global speaks to Kaveh Vessali, PwC Middle East Partner (Digital, Data & AI) on the application of AI and Big Data in Manufacturing

Please could you define what artificial intelligence is, and what Big Data is?

AI is the ability of a machine to perceive its environment and perform tasks that normally require human intelligence, and it’s a whole field of different technologies, techniques and applications. 

Big data is a set of tools and capabilities for working with, for processing, extremely large sets of data. 

How does AI and Big Data work together?

Big data is just one of the enablers of AI, though as we see increasing volumes of data, it’s one of the most important 

How can this be applied to a manufacturing setting?

Broadly speaking, there are many benefits of AI, and the use of data, which include reducing costs, minimising human error, and increasing productivity and efficiency. The important thing to consider is any setting - for the use of any technology - is what is the problem you are trying to solve? Be it merely automating repetitive tasks or to reinventing the nature of work in factories by having humans and machines collaborate in order to make better and faster decisions.  

Why should manufacturers use AI and Big Data when adopting smart manufacturing capabilities, what is the value for manufacturers?

One view is, again, the economic benefits of AI, which come in manufacturing as a result of: 

1. Productivity gains from automating processes and augmenting the work of existing labour forces with various applications of AI technologies. 

2. Increased consumer demand due to the increased ability to personalise and tailor manufactured products, along with higher-quality digital and AI-enhanced products and services. 

Manufacturing (and construction industries) are by nature capital intensive, and in our 2018 report, “The potential impact of AI in the Middle East,” we estimated that the adoption of AI applications could increase the sectors’ contribution to GDP gains by more than 12.4% by 2030. 

How can AI and Big Data help manufacturers to evolve in the Industry 4.0 revolution? What about those already looking at Industry 5.0?

It’s really about the investment you make now, in order to futureproof your business. 

We typically see two broad strategies or approaches to the adoption of AI. There are things that we can do immediately, without any recourse to Big Data - which is to adopt technologies we describe as Sensing, those involving computer vision, for example. There are plenty of use cases where these can be used immediately in manufacturing, such as for automatic fault detection. However, there is a longer term play which requires investing in data - getting the right collection mechanisms in place, storage, data governance, Big Data capabilities etc - in order to develop increasingly valuable machine learning driven AI use cases. This is absolutely necessary for long term adoption success. 

What is the best strategy for organisations looking to realise the value of AI and Big Data in manufacturing?  

AI and Big Data are only one part of a successful smart factory. The organisations that lead on AI adoption are those who have already made the most progress in digitising core business processes. In order get ahead in using AI solutions at scale, there are a number of technology investments and organisational decisions to be made, including: 

1. Digitising processes ultimately leads to improved ability to generate data, and in the manufacturing setting - with many 100s of sensors generating 1000s of measurements in real time, the result is Big Data. Data is key to building AI so reliable and accurate data acquisition, management and governance are key. The production line and factories play a critical and direct role in the data-acquisition process. 

2. AI strategy, both long and short term, begins with the use cases, the business applications. Manufacturers need to ask where they want to use AI and gather these use cases together and prioritising projects based on a balance of expected impact and complexity of implementation. 

Of course, in addition to technology and business processes, people are at the heart of any successful technology adoption. AI teams need to be composed not only of data scientists, also data engineers and solution architects to enable their work, data stewards to ensure accuracy, and increasingly so call “Analytics/AI translators” who are able to communicate with business leaders and technology experts. Culture is also key, and manufacturers need to enable a data and AI-driven culture, building trust in data and algorithms by educating their workforce about AI and its capabilities, how best to extract value. It’s not just the positive of course, but also the risks and limitations, as these when encountered without expectations having been set, can significantly impact willingness to invest. 

What are the challenges when it comes to adopting AI and Big Data in manufacturing?

PwC research has shown that one of the major challenges to implementing AI is uncertainty around return on investment (ROI). As I said, there is significant investment required for a long term data and AI strategy to be successful, and expectations around the time to see tangible returns must be set realistically. 

Many companies also struggle with the data side: collecting and supplying the data that an AI system needs to operate, and ensuring that it is accurate. Again, this speaks to the bigger investments required in digitisation. 

Some of the main challenges for manufacturing companies with implementing AI at a scale from our research include:  

  • 40% → Technologies not mature  
  • 40% → Workforce lacks skills to implement and manage AI  
  • 36% → Uncertain of return on investment  
  • 33% → Data is not mature yet 
  • 32% → lack of transparency and trust  
  • 24% → Work councils and labour unions  
  • 22% → Regulatory hurdles in home & important markets  

One element highlighted here, particularly around lack of trust, and labour unions, is that AI is typically misrepresented in the media as “replacing” workers, and taking jobs. Yes, there are efficiency gains to be made from automation, as there have been since the first industrial revolution. But we believe that Data and AI are at their most valuable when they are used to augment workers, enhancing their abilities and the products being manufactured. 

Another challenge we’re starting to see emerge is cyberattacks increasingly targeting interconnected equipment and machinery in smart factories. PwC recently hosted a webcast, in cooperation with the National Association of Manufacturers in the US and Microsoft to discuss this. 

What are the current trends in AI and Big Data in manufacturing?  

  • We see companies putting slightly more focus on adding AI solutions to core production processes such as the engineering, and assembly and quality testing 
  • Safety is of significant importance, with techniques adopted in protocol adherence capabilities (for example maintaining safe distance from specific machinery) being adopted in more every day scenarios for COVID-19 protocol adherence 
  • There is considerable interest in predictive maintenance for large machinery involved in manufacturing processes, and also supply-chain optimisation

What do you see happening in the AI and Big Data industry in manufacturing in the next 12-18 months? 

Honestly, I think we’ll see a continuance of where we’ve already been going for the last 12- 18 months. AI and data are already being used in manufacturing but this use doesn’t get as much attention in the media as, say, healthcare, but the success stories are there, and they will continue as operations continue their digital journeys. 

Share article