May 16, 2020

From the factory floor to the boardroom: leadership tips for women in manufacturing

Women in Manufacturing
Alliance Rubber Company
5 min
From the factory floor to the boardroom: leadership tips for women in manufacturing
As a girl, I remember my father staying up late sketching out new ideas and spending long hours working in the factory he had built from the ground up...

As a girl, I remember my father staying up late sketching out new ideas and spending long hours working in the factory he had built from the ground up. As a teenager, my first job was in the factory, sorting rubber bands. Manufacturing is in my blood, and I have my brother Richard to thank for teaching me a strong work ethic and for changing our culture to one of empowerment for our associates. As I worked my way up through sales and marketing to company president, I have seen and been a part of the natural progression of women in the manufacturing industry.

Women in manufacturing understand the importance of collaboration, hard work and investment in people. My advice for women in leadership roles is to capitalize on these attributes.

Choose a field you truly love

Above all, you must enjoy what you do to be any good at it. I was always interested in the family business. Throughout my life, I saw the ways local manufacturing benefited both the people who worked there and the community where the company was based. American manufacturing became my personal passion. This passion fuels business decisions, employee relations and my love of the job. My advice to any women in the industry is to enter a field you can enjoy and be passionate about.

Get as much valuable education as you can

Education does not, and should not, stop after you walk across the graduation stage. Learning is an ongoing process, especially in this age of technology. Actively take time to research what’s going on in your field. Are there new methods in development? What technology advancements are being made in machinery? Which companies are performing in the top of their class? As the industry grows, so should your knowledge.

Similarly, look for opportunities to learn. Look for classes, workshops, summits and conferences that could benefit you, your employees and your business. Whether it be on leadership, technical skill development or any interesting topic, always invest in valuable opportunities to learn. At Alliance we provide an EAP - Employees Tuition Assistance Program - to help with their further education. This not only widens the knowledge base of our employees, it also gets employees excited and even more invested in their work.

Surround yourself with people who know what they are doing

Work with people who push you. Their expertise and knowledge in their specific field should encourage, motivate and educate you, which strengthens you as a leader. Over 95 percent of our managers began on the factory floor. These individuals have worked their way up through the ranks and, as a result, know how intricately all jobs work together. They know what they’re doing and how it trickles down to every employee below them. Though I also began on the floor, there are many aspects of this company I am still learning. By surrounding myself with people who are experts in their field, I am constantly advised and inspired.

Focus on teamwork and collaboration

As a woman in a predominantly male-led field, there can be pressure to feel the need to overly assert myself as the primary leader and decision maker. I believe it is in everyone’s best interest to focus on and utilize the impact teamwork and collaboration have. As I stated earlier, surrounding yourself with key people is crucial. Use them. Bring in everyone’s specific skillsets and unique perspectives to create what it best for everyone. Not everything is meant to be the responsibility of one person. Good teamwork and collaboration are what sets great companies apart from good ones.

Prioritize helping others

My mom always said, “help somebody if you can.” If you prioritize creating a positive and helpful work environment, that will reflect in your business. By establishing a precedent that employees are free to question, learn and assist their fellow peers or supervisors, they will feel much more comfortable and competent in their roles. A teaching atmosphere also allows an ease in the process of shifting roles within the company as associates rise through the ranks.

Reward your associates

As part of the positive, empowering environment you want to create, establish ways to reward your associates. Whether it be through providing educational opportunities, bonuses, a clear pathway to advancement and success or uplifting words from a supervisor, know that your people will be appreciative their hard work is recognized. We survey our associates what their favorite Alliance attribute is and the vast majority say "the people they work with." A positive culture is so vital to teamwork, and we benefit from the fact that we have less than a 5% annual turnover rate. When your workforce feels like family, your people will enjoy coming to work. Diversity is a strength for us and at Alliance we build leaders.

Be open to new technology and innovation — stay competitive

We are always looking for innovative, yet resourceful, ways to progress our methods and our products. Change can be scary. As a part of continuing your education, you should be aware of new technology entering your field. And while some new additions can be faulty, it’s your job to do the thorough research to determine whether these new advancements could be beneficial. Stay ahead of the curve in your industry. Don’t be afraid to fail! Not every new idea will be a success, but failing is an important part of learning and growing as a company.

Being a woman in an industry driven by men can be challenging. The great work ethic of our people, technology and innovation help us to overcome the challenge we have of having factory wages which are 13 times what our competition enjoy. I have tried to encourage women - in manufacturing and across all industries - to take on leadership roles and never settle. It takes patience, collaboration and lots of hard work.

Bonnie Spencer Swayze, President and CEO of Alliance Rubber Company, has led the company since 2008 and oversees the production of more than 2,200 skus of mailing, shipping, office and packaging products sold through dealers in 55 countries. Pioneering the women’s entrance into the boardroom, Swayze was the first female board member of the Wholesale Stationers Association and has served on the Women’s Business Enterprise National Council board and other HUB organizations.

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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. 

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