Ways Manufacturers Can Make Better Use of Data
Big data is a buzzword you hear used by ever more companies across many different industries. For manufacturing companies, using data in smart and modern ways can improve processes and procedures, encourage growth in ways that would have been impossible in the past, reduce costs and raise profits.
Data are the facts or information about every aspect of manufacturing processes. Using IoT devices to record the manufacturing process, companies can avail themselves of all sorts of data. Unfortunately, many manufacturing companies, at best, don’t understand how to gather, analyze, and use all this data that is now available to them or, at worst, choose to entirely ignore it. If your company is not currently using data to drive production and make better decisions, you are missing out on major opportunities to improve your company. Here are 3 ways manufacturers can make better use of data to improve their processes.
Set Clear Goals
Manufacturing is all about setting goals for your machinery and manpower in order to produce the greatest quantity of good quality products as efficiently and quickly as possible. How clear are your goals? Are they passive and driven only by orders or are they based on data that allows your company to work in a way that is scalable and customizable when it needs to be? Some manufacturers struggle with these questions, especially when times get tough. The ones who set the clearest, smartest goals will be the ones that prosper.
Using data and basic analytics allows you to see the whole picture and be proactive about manufacturing goals. Using machine-level data you can learn incredibly important points such as when and how often you are producing different products, how long it takes, and how much money goes into producing each item. You can also get data on tiny seemingly insignificant information that will show you the times and conditions that generate the most profitable outcomes. When you know these data points, you can work to set goals that recreate the most profitable outcomes as much as possible to maximize your manufacturing efficiency.
Data provided by IoT devices in the manufacturing process can also help companies better understand cycle time and how it improves with more data and updated procedures. Cycle time measures the span of time from when an order is placed until it gets into a customer’s hand. With solid data to help you improve cycle time, you can start making clearer goals on customer timelines which will lead to improved customer relations and feedback.
Have Well-Defined Procedures
With clearly established data-driven goals, more data is used to help companies meet and exceed those goals. Manufacturers can do this in several different ways. As more data about their processes is gained, one of the best ways to achieve goals is to speed up production. When you do that, however, more errors can occur. Using big data companies can determine methods for going faster but with fewer errors.
To accomplish this seemingly impossible task, you must collect and analyze all the data at hand. Using error-rate data you can see who and what in the process is linked to the most errors and start creating a mix of products and workers that leads to the smallest number of errors. This will save money on unusable goods and while speeding up the process of hitting goals. It can also help to create employee incentive and training programs that will lead to a faster and less error-filled process.
Another way big data analytics generated during the manufacturing process by IoT devices can help companies adapt their processes to the modern environment, is by increasing their ability for customization. In 2020, manufacturing customization is more desirable for clients than ever before and data is the key to offering more of this. To start, knowing data about all of your manufacturing processes allows you to manufacture goods in the most efficient way possible. When you have a client looking for customization, you will quickly be able to make a data-based decision on whether or not you are able to do what is requested and how it will affect your bottom line.
Track Data Comprehensively
The manufacturing process is not merely about using data drawn from the machines, people, and products you make. Some data from all around you can be mined for better outcomes. In addition to acquiring and processing data from the tangible materials around you, you can also use environmental data to create a better manufacturing process and hit your goals. In some manufacturing industries – ones that make very precise and sensitive products – this data is a “must-have”.
Using a cloud-based monitoring system is one way to maintain widespread data visibility in complex systems. For manufacturers in such fields as the aerospace industry, where parts need to be produced and stored in precise environmental conditions, being able to collect precise environmental data about things like temperature, humidity, and pressure is vital. Dickson is an example of a company that offers data loggers and management software that can be implemented in this manner.
Using these types of data loggers allows the aerospace industry to maintain optimal conditions for making the products they produce; that helps them safely deal with volatile materials. Since they produce products using all types of electronics, metals, plastics, synthetic compounds, and other sensitive materials, precise conditions must be maintained. How they maintain these conditions varies greatly between facilities of different sizes, setups, and located in different climates, which is why comprehensive data tracking is so important for each facility that creates aerospace products.
These are just a few of the ways manufacturers can make better use of data. Big data is the new frontier of manufacturing and the companies that use it best will see quicker, larger, and longer-lasting improvements to their processes and outcomes than companies who don’t. Integrating IoT devices into the manufacturing process is the best way to start capturing and utilizing this data today.
The Ultimate Guide to the Essential Social Skills in Business
Effective communication and strong relationships are essential for success in the workplace. One factor that can greatly influence these qualities is emotional intelligence, often abbreviated as EQ. EQ refers to the ability to identify, understand, and manage one’s own emotions, as well as the emotions of others. Research has shown that individuals with high levels of EQ are better equipped to handle stress, communicate effectively, and work collaboratively with others (Chamorro-Premuzic & Sanger, 2016).
Research has consistently shown that emotional intelligence (EQ) is an important predictor of job performance and success in the workplace. EQ is comprised of a set of skills that allow individuals to recognize, understand, and regulate their own emotions, as well as the emotions of others. In addition, individuals with high EQ are better able to communicate effectively, build relationships, and navigate complex social situations. As a result, they are often viewed as effective leaders and collaborators, and are more likely to achieve their personal and professional goals.
In fact, a number of studies have demonstrated the significant impact that EQ has on job performance and success. For example, one study of 85 upper-level managers found that those with higher EQ scores were rated as more effective leaders by their subordinates (Law, Wong, & Song, 2004). Another study of 151 employees found that those with higher EQ were more likely to be promoted within their organization over a five-year period (Carmeli, Brueller, & Dutton, 2009). These findings highlight the importance of EQ in the workplace and suggest that developing these skills can lead to significant benefits for both individuals and organizations.
According to a study conducted by TalentSmart, a leading provider of EQ assessments, EQ is responsible for 58% of success in all job types (Bradberry & Greaves, 2009). In contrast, IQ only accounts for about 4% of success in the workplace. This suggests that EQ is a crucial skill set for individuals in any professional field. Fortunately, EQ is a skill that can be developed and honed over time with practice and awareness.
There are several key components of EQ that are particularly important for success in the workplace. These include:
Self-Regulation: This refers to your capacity to recognize and control your emotions. Sometimes treating them when they arise may be necessary. Understanding how to manage your anger is essential. However, it can also cover how to control the feelings you’ll experience.
Self-Awareness: This implies recognizing and understanding your own feelings. Do noisy places make you nervous? Do other people talking over you make you angry? Knowing these truths about yourself shows that you are working on your self-awareness. Being conscious of yourself is necessary for this phase, which can be more complex than it sounds.
Socialization: This category focuses on your capacity to manage social interactions and direct relationships. It doesn’t entail dominating others but knowing how to work with others to achieve your goals. This could entail presenting your ideas to coworkers, leading a team, or resolving a personal disagreement.
Motivation: Strong motivators include external forces like money, status, or suffering. Internal motivation, however, plays a significant role in Goleman’s concept. By doing so, you demonstrate your ability to control your cause and initiate or continue initiatives of your own volition rather than in response to external demands.
Empathy: It’s equally critical to be sensitive to others’ feelings. This may entail learning to identify different emotional states in individuals — for example, can you tell the difference between someone at ease and someone anxious? — but it also requires comprehension of how other people may react to their current situation. Empathy is one of the essential traits in business and business leadership.
A thought leader in this space, Michael Ventura has built a career advising organizations on the importance of emotional intelligence in the workplace. In his book, Applied Empathy, Ventura highlights the value of empathy in business and provides strategies for developing and applying this skill set. With two decades of experience as a leader, facilitator, and educator, Ventura’s work has made impact in with prestigious institutions such as Princeton University and the United Nations as well as corporate clients such as Google and Nike.
Through his work, Ventura advises leaders to focus on the development of EQ in order to help individuals improve their communication, collaboration, and leadership skills, ultimately leading to greater success in the workplace. Experts like Ventura continue to support the growing body of research on the value of EQ in business, and the evidence that organizations who invest in the EQ of their teams help to create a more empathetic and successful professional environment.
And it’s worth noting that EQ isn’t just important for individual success in the workplace, but also for overall organizational success. A study by the Center for Creative Leadership found that EQ was a better predictor of success than IQ or technical skills in the workplace, and that teams with higher levels of EQ tend to be more effective and productive (Boyatzis, Goleman, & Rhee, 1999). By cultivating a culture of empathy and emotional intelligence, organizations can improve their overall performance and create a more positive work environment for their employees.
In conclusion, emotional intelligence is a crucial component of success in the workplace, and individuals and organizations alike should prioritize the development of these skills. The ones that do not only develop a leading edge in their category, but also become a meaningful place to work for their teams. And in today’s rapidly changing talent landscape, the retention of highly capable, emotionally intelligent leaders is one of the greatest keys to unlocking success.
Boyatzis, R. E., Goleman, D., & Rhee, K. S. (1999). Clustering competence in emotional intelligence: Insights from the emotional competence inventory (ECI). In R. Bar-On & J. D. A. Parker (Eds.), Handbook of emotional intelligence (pp. 343-362). Jossey-Bass.
Bradberry, T., & Greaves, J. (2009). Emotional intelligence 2.0. TalentSmart.
Chamorro-Premuzic, T., & Sanger, M. N. (2016). Does employee happiness matter? Journal of Organizational Effectiveness: People and Performance, 3(2), 168-191.
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