Data Experts Can Help Improve Manufacturing; Here’s How…

The way we manufacture anything today is drastically different than how our grandfathers did. Machines get connected to the web and are ripe for data analytics. The SMART machines are data-driven, enabling newer endless possibilities for manufacturing. In fact, realized intelligent factories depend on data science methodologies and collaborative manufacturing systems to make operations more flexible, adaptable and optimized. 

Data Science methodology is a set of techniques and processes used when solving manufacturing problems by utilizing data. This methodology has a significant impact on the practical application of data-driven products. Critical business data is analyzed with the objective of aiding enterprises better understand their business. The focus gets expanded from ‘what happened?’, ‘how often?’ and ‘where?’ to answer ‘why?’, ‘what if this trend continues?’, ‘what will happen in the future?’, and ‘what is the ideal scenario?’. Using subject-specific jargon, these questions correspond to analytical tasks widely known as statistical analysis, forecasting, predictive modeling, and optimization. [1]  

In other words, Data Analytics is about making the most of all data using a set of tools and technologies to deliver business value. The process begins with acquiring data from multiple sources (preferably clean and possibly in large amounts) in layman’s terms, the information you can leverage. Even the smallest of data can get integrated and analyzed to reveal whether or not a manufacturer is making profits, saving money, or over-spending to improve performance. Let experienced professionals or the right data analytics tools handle the data to get real value from your production processes.  

Aside from data analysts and statisticians, you can make the most out of available data by harnessing advanced AI apps, leading you to customer-centric goals and process efficiency. The AI apps work with the collected business data, bringing the numbers in the statistics to life, diagnosing, and correcting the manufacturing through informed decisions that drastically improve the production processes. 

“The goal is to turn data into information, and information into insight.” 

– Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co. 

A smart factory monitors the entire production process by linking physical and digital worlds. From building tools to individual operators in the workshop are rich data sources. It is an end-to-end connected and flexible production system, which uses a constant stream of data to provide learning from the machines. Based on the integrated data analytics, AI Apps provide real-time insights to adjust the process workflows, adapt to new needs, and optimize production. Intelligent factories thus achieve machine maintenance in advance, inventory management, and efficient production processes throughout the manufacturing network. 

Data can take many forms and fulfill many purposes in an intelligent factory environment. Data makes discrete information on manufacturing environmental conditions such as humidity, temperature, and pollutants accessible. It also helps self-optimize devices, addresses numerous manufacturing problems, improves process control, and guides while responding to new requirements. 

According to a recent study conducted by the World Economic Forum, nearly 75% of surveyed manufacturing executives consider advanced analytics to be critical for success. However, only a few companies capture the full value that data and analytics can unlock to help address the manufacturers’ most pressing challenges. [2] Establishing a strong technological backbone is a prerequisite to effectively scale data and analytics applications for manufacturing success in the post-pandemic world.  

Industry 4.0 is data-driven and when its technologies are growing exponentially, the frequency of data collection will also increase. Those organizations that are under-using data or are still not AI-ready run the risk of remaining on a lower rung of the business ladder.  

On a lighter note…. 

Although the D word is of BIG importance in the manufacturing world, we stand divided on the pronunciation. There is a valid reason behind the ‘proper’ pronunciation of the word Data. Ideally, it should be pronounced: day-taa, (not daa-taa) as data is the plural of datum (day-tum). 

References:

[1] Omar, Y. M., Minoufekr, M., & Plapper, P. (2019). Business analytics in manufacturing: Current trends, challenges and pathway to market leadership. Operations Research Perspectives, 6, 100127. https://doi.org/10.1016/j.orp.2019.100127

[2] Weber, A. (2021, August 24). The Big Data Dilemma. Www.assemblymag.com. https://www.assemblymag.com/articles/96570-the-big-data-dilemma

Breaking it down — the 4th Industrial Revolution for You.

What is 4IR? The term Industry 4.0 has been bouncing around the industrial world for quite some time now, and it’s beginning to gain traction in the business world. We have been talking about how it will change our lives tremendously. Most people think of it as the emergence of Artificial Intelligence (AI), Machine Learning (ML), Data Analytics, Augmented Reality (AR), et al. While that is true, how will it affect our lives again? It is also essential that you know what it can mean for your business exactly, for you to leverage the maturation of 4IR to your advantage.   

History tells us that every time there has been an Industrial revolution in the past, it has raised the level of income and improved the quality of living globally. Therefore, to understand 4IR, shouldn’t we start at the very beginning? Knowing what preceded it will tell us how the Fourth Industrial Revolution will impact businesses and why. 

The First Industrial Revolution in 1765: It all began with the coal-fired steam engines that powered the wheels of mechanized factory production and accelerated the economy, shifting us from an agrarian to an industrialized society.  

The Second Industrial Revolution in 1870: A century later, the world saw the invention of electricity as a source of energy besides gas and oil. The electrification of factory production enabled mass production, which further led to tremendous technological advancements and culminated in the invention of the automobile and airplanes by the 20th century. Industry 2.0 thus earned the title of the Technological Revolution.  

The Third Industrial Revolution in 1965: As the rule of three impressed, nuclear energy emerged as yet another energy source half a century later. The era marked the rise of electronics, which automated production, followed by the advent of computers and the invention of the internet. Advanced telecommunications and information technology initiated globalization and the digitization of manufacturing. Thus, it went down in history as the Digital Revolution.  

After witnessing the three steps in the evolution of technology, now we find ourselves in the middle of the fourth major industrial era — Industry 4.0.  

The Fourth Industrial Revolution in 2015: Dynamically different from the previous industrial revolutions, 4IR is progressing at an unprecedentedly fast and exponential pace. Powered by a confluence of many technologies such as the Industrial Internet of Things (IIoT), AI/ML, and big data analytics, Industry 4.0 has presented a dramatic new business model for every possible industry. Business leaders are now gearing up for this revolution to transform their organization, given the potential increase in income and benefits. Manufacturers expect it to impact every stage of the product lifecycle and optimize throughput. 

Below are 10 facts about Industry 4.0 for you: 

  1. Industrie 4.0 — the term first coined at the industrial trade fair, Hannover Messe 2011 in Germany, ignited the vision of a new Industrial Revolution and slowly captured global attention. Industrie 4.0 (I4.0) represented the strategic vision of Germany for the future in an ambitious bid to preserve global manufacturing leadership by reaffirming commitment to economic and social transformation through innovation, collective and multi-stakeholder participatory processes, and policy experimentation. The rapid diffusion of the term I4.0 across the globe has positioned Germany as a reference for strategic approaches to harnessing the Fourth Industrial Revolution. [1] 
  1. Klaus Schwab, Founder and Executive Chairman of the World Economic Forum (WEF), is credited for popularizing the phrase Fourth Industrial Revolution by publishing an article in the American magazine Foreign Affairs.  
  1. At The Great Reset, the 50th annual meeting of the WEF held in June 2020, their proposal included the Fourth Industrial Revolution as a Strategic Intelligence for rebuilding the economy sustainably after the COVID-19 pandemic. 
  1. Industry 4.0 is the era of the most ground-breaking evolution in the history of technology. It is not only fundamentally changing the way we conduct business, but it is also offering new opportunities for entrepreneurs and manufacturers, creating new niches for people to up-skill and progress professionally.  
  1. Over the next few years, you will see a phenomenal upsurge in cooperation between human and machine intelligence, blurring the difference between our real world and the metaverse — the physical and digital worlds.  
  1. IR 4.0 is driven by data, which will be the currency dominating our digital lives henceforth. British mathematician Clive Humby called data the new oil. It is indeed a fitting metaphor. Just like oil data is useless in its raw form, once refined becomes a valuable asset. With the amount of data we generate, we could be sitting on a big pile of untapped wealth. [2] 
  1. These are exciting times for the manufacturing industry. However, contrary to popular belief, IR4 is not about automation and robot-driven processes. The fact is that the core idea of Industry 4.0 is to make production processes more predictable, efficient, and beneficial to all parties involved. 
  1. A factory is deemed IR4.0 ready or digitally transformed when it operates with data transparency, intelligently connected machines enabled for interoperability, a virtual twin of the physical shop floor, and AI applications that provide end-to-end workflow efficiency and optimized production. 
  1. Industry 4.0 ushers the implementation of AI/ML technologies in workplaces, factories, and companies, allowing micro-planned production processes with real-time insights, wastage reduction, and leveraging data to improve business processes. Industry 4.0 promotes flexible production processes that utilize data for customer-oriented solutions. 
  1. Fei-Fei Li, director of Stanford University’s new Human-Centered AI initiative has rightly pointed out that Industry 4.0 has a human-centric approach even its propagation of the adoption of AI. Digitalization must not be perceived as disruptive, and AI applications are not competitors, but partners in securing our well-being. Technology has always enhanced human capabilities, not diminished or replaced it in manufacturing.[3] 

The term — Industry stands for hard work but working hard to resist change is not industrious. Industrial manufacturers and businesses that get on board with IR4.0 today are undoubtedly the market leaders of tomorrow. May the Fourth be with you! 

AI Adoption—a SMART Business Strategy for Guaranteed Success

Digitalization has taken the manufacturing industry by storm. There is no living in denial now that AI is a transformational technology. AI has not only prevailed in the Gartner Hype Cycle, but it is also dominating this year’s technology landscape. Organizations are increasingly adopting AI applicationsolutions to create new products, improve existing products and grow their customer base. Integrating AI solutions for organization-wide applications and business workflows might seem complex, but there is no better time to get SMART than now! 

Senior Principal Analyst at Gartner, Shubhangi Vashisth has rightly pointed out, on average, it takes about eight months to get an AI-based model integrated within a business workflow and for it to deliver tangible value. Yet, Gartner predicts by 2025, 70% of organizations will have operationalized AI due to the rapid maturity of AI adoption initiatives (Goasduff, 2021). 

So, if you are wondering where and how to get started, here are our Pro Tips for turning your factory toward Smart Manufacturing:  

  1. Do not look at AI adoption as an experiment. It is a legit strategy that has proven its efficacy at reducing your business risks and improving productivity. 
  1. You need to focus on the quality of only two enablers of digital transformation—Data and AI application solutions. 
  1. Identify your business challenges first and make informed decisions about AI applications offering customized solutions for your pain points.  

The early adopters of AI, who embraced the IR 4.0 principles of making business processes more intelligent, have seen the technology deliver on its commercial promises.  

Research suggests that the BOE model provides a fitting AI adoption framework (Dasgupta & Wendler, 2019). Originally the BOE model got developed to understand the adoption of electronic data interchange (EDI) technology. It is now utilized as a general technology adoption model, too.  

The BOE model considers three factors:  

  1. Benefits-  

The perceived benefits of adopting AI applications in manufacturing organizations are  

  • Improvement of process yield by 8-10% 
  • Enhanced Product Quality by 10-12 % 
  • Reduction of working capital by 8-10% 
  • Cutting down of maintenance costs by 15- 20% 

The industry can get quicker ROI and start realizing benefits in 6 to 8 weeks of AI integration. The additional benefits of delivering such throughput with faster turnarounds and improved quality of service are improved customer satisfaction and long-term business relationships. 

  1. Organizational Readiness – 

Organizational constraints such as company culture, apprehension regarding AI adoption misconstrued as a disruptive technology, and legacy machines can pose challenges in deploying AI. However, under the skilled guidance of technology consultants and with the help of cutting-edge technology enablers, organizations can navigate the pitfalls to achieve relevant AI readiness. Systematic AI adoption increases the probability of successful transformation.  

  1. External Pressure (Competition) – 

Leveraging AI to secure significant business value can provide a competitive advantage to organizations. Industry-specific AI applications can lead to incredible improvement in manufacturing volume and process efficiency. 

And then again, there are three approaches to AI adoption: 

  1. Top-down approach for holistic organization-wide technology adoption 
  1. The Bottom-up approach, the opposite alternative, applies technology to various components and processes in a piecemeal manner. 
  1. The Agile approach involves continuous improvement at every stage in constant collaboration with technology service providers. The crossover into AI is a smooth process of evaluation, customized micro-planning, and execution.  

The alignment of AI adoption with your business strategy will elevate your manufacturing to the Plateau of Productivity. Machine Learning (ML), one of the technologies under the umbrella of AI, is also a commendable value-addition. ML fortifies AI with its capability of continual learning through experience, which plays a vital role in the fine-tuning processes. Start with apilot project and scale it up for heightened profitability.  

Wisdom is key to human evolution, but Artificial Intelligence is key to manufacturing evolution in this Smart Machine Age! 

Empathy in Company Culture is the Sign of an Emotionally Intelligent Organization

“When dealing with people, remember you are not dealing with creatures of logic, but with creatures of emotion.” 

– Dale Carnegie. 

Business is people, and empathy is an essential business skill. Empathy in company culture is the sign of an emotionally intelligent organization. But what does all that mean? How can you build it into your business to make it more efficient and effective? Let us look at what it takes to become an emotionally intelligent organization, and why empathy in company culture is an essential aspect of modern business. 

Empathy is a foundational characteristic of emotional intelligence (EI). At its core, empathy is about making others feel heard and understood. The concept of empathy calls for feeling with as opposed to feeling for another person—sympathy. It gets a tad complicated in the context of business. Most often, empathy gets you focusing on dealing with individual customer problems and complaints as they occur. It is considered a strength of character to have the empathy to understand how others feel and then do something about it, thereby avoiding possible conflicts or misunderstandings. It does come naturally to most, but it is also a skill you can learn and develop.  

Why Have Empathy? 

Empathy can make or break business performance as it is one of the building blocks in a business relationship. Whether it is a manufacturer-customer relationship or the management-employee rapport, empathy is an essential business skill. Businesses today have begun to understand the importance of cultivating a culture of empathy and displaying a high emotional quotient (EQ).  

Under emotionally intelligent leadership, a company can grow into a well-rounded organization that is productive and competitive. Empathy in company culture ensures that employees get treated with respect and dignity. Their opinions are valuable; they enjoy the freedom of expression and ease of communication without feeling the pressure of the corporate hierarchy. Higher the level of employee empathy in the company culture, better the level of organizational EQ/EI, which is a sure sign of positive outcomes in areas such as employee satisfaction and team cohesion. Better company culture can also mean improved staff retention. Happy, comfortable, and satisfied staff are the ones who will render better customer service. Thus, empathy in company culture can help an organization succeed at all levels of the business.  

For significantly improved business relationships, they must strategize an increase in empathy in the company culture. The organization will then be able to: 

  • Enhance workforce engagement and boost motivation and productivity. 
  • Ensure more effective employee performance through better leadership and management of teams and individuals. 
  • Promote overall emotional well-being and reduce stress among employees. 
  • Improve customer service and sales approaches by helping employees understand customer needs better. 

Customer centricity is when a company focuses on the customer in all company actions, processes, and decisions. It is a strategic approach that seeks to understand customer needs, wants, and expectations to deliver a seamless customer experience that is relevant to them. Customer centricity is a philosophy that says success is a direct result of the ability of a company to understand and meet customer needs. If you wish to deliver customer satisfaction and emerge as a successful business leader, heightened empathy in company culture and customer-centricity must go hand-in-hand.  

How Do We Build Empathy? 

There are three steps to building Empathy that every employee of the organization can consider: 

Step 1: Learning to pay attention and listen. 

Before doing anything else to build empathy for business success, start by learning how to listen with complete attention. Do not get busy thinking about what your response will be while the other person is still speaking. Remain in the present and be truly interested in the point of view of others.  

Step 2: Asking questions. 

Ask questions that will give you more insight into the situation or experience of another person or even another group of people. Maintain open, two-way communication. 

Step 3: Humanize the data. 

Data-driven empathy is about working with personalized insights and aligning your business with customer-specific requirements. Data can give you a real-time view of the customer’s evolving needs. Business problem solutions can thus be tailored to the T, establishing the company as a customer-centric organization.  

Step 4: Create awareness about empathy as a Key Success Factor (KSF). 

Propagate empathy in the company culture as a winning strategy for all. Employees who look at empathy in a different light will focus on getting to know customers better, treat them with more respect and undiluted attention, have complete transparency in their communication with customers, and provide them with appropriate solutions. That, in turn, will create a company that customers trust and think of going back to or conducting business with again.  

Essentially, that is the way to ensure golden ROI from happy customers and long-standing business relationships. And we can thus conclude that empathy is a sustainability tool too. Is it surprising that even the European Council has recognized Empathy as one of the core competencies for the future? 

How Artificial Intelligence Is the Change Agent for Manufacturing Success

Data does not lie, and artificial intelligence creates transparency!

Change begins with an idea, and a change agent can make or break an idea or turn it towards becoming the next innovation.

That has always been true, but now more than ever before. The innovations that are changing the world are happening at lightning speed. Companies can launch an idea, iterate on it with customers, and scale it globally in the blink of an eye. We are talking about artificial intelligence, robotics, virtual reality, advanced materials, 3D printing, and more.

The Fourth Industrial Revolution is reshaping the world. New capabilities are getting rolled out daily. But are we thinking ahead of the curve or are we resisting the drivers of change? At the core of Industry 4.0 are transformational technologies such as Machine learning (ML) and artificial intelligence (AI), backed by Big Data — change agents that gave a solid foundation to the biggest revolution in innovation. Are you wondering why and how your business will get impacted? If you think this is another fad that people will eventually forget, here is our $0.02.

Let’s face it! Manufacturing success can be rare to come by. Even for the biggest and best manufacturers, it is a constant struggle to compete in a global economy. There are two perpetual goals of any manufacturing business — two qualitative and quantitative goals — increased output and improved efficiency, which fetch the ultimate goal of Golden ROI.

For starters, there is a lot that AI can do for optimized manufacturing. The best way to understand that is by breaking down each word:

• Output: AI can pinpoint where your company is experiencing loss in productivity and recommend ways to correct your processes. It could begin with detecting bottlenecks that cause WIP and also do as much as providing real-time guided production models that enable end-to-end synchronized production planning.

• Efficiency: Close at the heel of increased output comes efficiency through AI. The more efficient the workflow and production processes, the better revenue generated for the company. And that can also translate into increased investments in applications that can bring further growth. By utilizing this fantastic catalyst or change agent of business success called AI, companies can ensure optimized manufacturing.

And what is fueling those recommendations and insights from your AI applications? That which tells you where and how your processes are flawed? Big Data is the massive collection of information that gets analyzed by AI applications. It is from Big Data that companies can extract meaningful business insights. And that can help them optimize manufacturing, improve customer experience and satisfaction, and thus eventually gain an edge over market competition.

The demand for data-driven decision-making is growing as businesses enter the 4th industrial revolution (IR4.0). For some time, manufacturers have been looking for new ways to boost production while saving costs. Many turned to the internet of things (IoT), but data analytics with AI applications came as game-changers.

The power duo creates clarity out of complexity. Human perceptions and biases from experiences can obstruct the optimization of manufacturing. Whereas data does not lie, and data analytics give unbiased observations. It helps distill facts and creates transparency in operations. Artificial intelligence applications can provide integrated analytics and actionable insights in real-time. Manufacturers can achieve optimized quality production through timely informed decisions.

The report published by PwC based on their study conducted regarding Exploiting the AI Revolution says that AI could contribute up to $15.7 trillion to the global economy by 2030. Of this, $6.6 trillion is likely to come from increased productivity. Research has also suggested that 45% of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. That is because AI will drive greater product variety, with increased personalization, while also reducing production costs considerably (PricewaterhouseCoopers, 2016).

So, understand, invest and embrace. Don’t just resist and reject. Informed and progressive decisions today will lead you to success in the future. And see if you can borrow some artificial intelligence to do that!