Article | December 21, 2021
Consumer demand has shifted dramatically in recent years, and manufacturers are trying to adapt to this shift. To maintain high product quality, minimize costs, and optimize supply chains, manufacturing analyticshas become essential for manufacturers.
Manufacturing analyticsis the process of gathering and analyzing data from various systems, equipment, and IoT devices in real-time to get essential insights.
As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity.
– Matt Mong
Manufacturing analyticscan assist in maintaining production quality, boost performance with high-profit returns, decrease costs, and optimize supply networks.
This article will outline manufacturing analyticsand present a list of possible application cases. It will also highlight the benefits of manufacturing analyticsfor any shop floor or factory.
Manufacturing analytics: An Overview
With manufacturing analytics, we can streamline and speed up the entire process. Data interchange and automation helps in speeding up the production process. Manufacturing analyticsuses predictive manufacturing, big data, Industrial IoT, network virtualization, and machine learningto produce better scalable production solutions.
Manufacturing analyticscollects and analyses data from many sources via sensors embedded in machinery to identify areas for improvement. Data is collected and presented in an easy-to-understand structure to illustrate where difficulties emerge throughout the process.
In short, manufacturing analyticscollects and analyses large volumes of data to reveal insights that might improve performance. Users can also obtain automated business reports to reply in real-time.
Why Manufacturing analytics is Vital for Leading Businesses
There are numerous benefits of manufacturing analyticsthat drive any company’s production and overall manufacturing business growth. The benefits of manufacturing analyticsfall into three distinct categories as below.
It reduces the overall cost: Analytics may save a significant amount of money if used more efficiently. Labor costs are also reduced due to automation and semi-autonomous machinery. Similarly, preventive and prescriptive maintenance programs may save money while enhancing productivity.
It boosts profits for businesses: Manufacturers can respond swiftly to changes in demand using real-time insights in production, inventory management, and demand and supply forecasting. For example, assume the data indicates that they are approaching their maximum capacity. In such instances, they can increase over time, increase capacity, modify procedures, or tweak other production areas to adapt and maintain delivery times.
Other unforeseen benefits: There are several advantages to the increased capabilities enabled by manufacturing analytics. These benefits include lower energy use, safer environmental practices, fewer compliance failures, and more customer satisfaction.
Five Real-world Applications of Manufacturing Analytics
A machine's analytics uses aggregate data from real-time detectors to anticipate when it needs to be replaced or functioning irregularly. This process helps predict machine failure or equipment defects.
Analytics can assist in determining a plant's capacity and how many products are produced by the unit in every production cycle, which is helpful in capacity planning. In addition, analytics may help determine the ideal number of units to create over time by considering capacity, sales predictions, and parallel schedules.
Predictive analytics solutions can automate maintenance requests and readings that shortens the procedure and reduce maintenance expenses.
Product development is an expensive process in manufacturing. As a result, businesses must invest in R&D to develop new product lines, improve existing models, and generate new value-added services.
Earlier, this approach was in place by repeated modeling to get the finest outcome. This approach can now be modeled to a large extent, with the help of data science and technologically superior analytics. Real-world circumstances can be replicated electronically using "digital twins" and other modeling approaches to anticipate performance and decrease R&D expenses.
Many factors that might help in the plan significant capital expenditures or brief breakdowns can be explained using historical data and a few high-impact variable strategies. For example, consider the seasonality of products like ice cream. As a result, historical market data and a few high-impact factors can help explain numerous variables and plan major capital expenditures or short-term shutdowns.
In addition to demand forecasting, predictive analytics incorporates advanced statistical techniques. With predictive analytics, a wide range of parameters, including customer buying behavior, raw material availability, and trade war implications, may be taken into consideration.
Warranty support may be a load for many manufacturers. Warranties are frequently based on a "one-size-fits-all" approach that is broader. This approach introduces uncertainty and unanticipated complications into the equation.
Products may be modified or updated to decrease failure and hence expense by using data science and obtaining information from active warranties in the field. It can also lead to better-informed iterations for new product lines to minimize field complaints.
Managing Supply Chain Risks
Data may be recorded from commodities in transit and sent straight from vendor equipment to the software platform, helping to enable end-to-end visibility in the supply chain.
Manufacturing analyticsallows organizations to manage their supply chains like a "control tower," directing resources to speed up or slow down. They may also order backup supplies and activate secondary suppliers when demand changes.
Businesses should adapt to changing times. Using analytics in manufacturinghas altered the business industry and spared it from possible hazards while boosting production lines. Industry 4.0's route has been carved. Manufacturing analyticsis the key to true Industry 4.0, and without it, the data produced by clever IoT devices is meaningless. The future is data-driven, and success will go to those who are ready to adopt it. The faster adoption, the sooner firms go ahead of the competition.
How can data analytics help manufacturers?
Data analytics tools can help manufacturers analyze machine conditions and efficiency in real-time. It enables manufacturers to do predictive maintenance, something they were previously unable to accomplish.
Why is data so crucial in manufacturing?
Data helps enhance manufacturing quality control. Manufacturers can better understand their company's performance and make changes by collecting data. Data-driven manufacturing helps management to track production and labor time, improve maintenance and quality, and reduce business and safety concerns.
What is Predictive Manufacturing?
Predictive manufacturing uses descriptive analytics and data visualization to offer a real-time perspective of asset health and dependability performance. In addition, it helps factories spot quality issues and takes remedial action quicker by eliminating the waste and the cost associated with it.
Article | December 14, 2021
Do manufacturing businesses require Business Intelligence (BI)? The answer is YES. Manufacturing is one of the most data-intensive businesses, producing massive amounts of data ranging from supply chain management to shop floor scheduling, accounting to shipping and delivery, and more.
All of this information would go to waste if not properly categorized and utilized. Scrutinizing and analyzing your data with business intelligence will help you become a more efficientand productive organization. Your organized data can show you where the gaps or inefficiencies are in your manufacturing process and help you fix it.
Many companies simply are not willing to change or think they are done once they make a change. But the truth is technology, consumer demands, the way we work, human needs and much more are constantly changing.
Michael Walton, Director, Industry Executive at Microsoft
BI has the potential to improve the operations of an organization and transform it into an organized one. According to Finances Online research, more than 46% of organizations are already employing a BI tool as a significant part of their company strategy, and according to Dresner Advisory Services research, 8 in 10 manufacturers who use BI for analytics have seen it function successfully.
How Manufacturing Operations Are Improving with Business Intelligence?
As revealed by the BI statistics above, we can see that business intelligence is critical in manufacturing. To further illustrate how business intelligence supports the manufacturing industry, let's look at some of the business intelligence benefits that are making a difference in the manufacturing industry.
Advances Operational Efficacy
While modern enterprises create massive amounts of data, not all of this data is relevant. Today's business intelligence solutions take all of the data from your organization and transform it into an easily comprehensible and actionable format. It enables you to minimize or fix errors in real-time. Additionally, it helps you to forecast raw material demand and assess procedures along the supply chain to ensure maximum efficiency.
Allows for the Analysis and Monitoring of Financial Operations
Business intelligence solutions provide insight into sales, profit, and loss, raw material utilization and can usually assist you in optimizing resources to increase your return on investment. Understanding your cost-benefit analysis, BI enables you to manage production costs, monitor processes, and improve value chain management.
Assists in the Management of Your Supply Chain
Manufacturing companies engage with various carriers, handling these multiple processes can be complicated. BI enables manufacturing companies to have more accurate control over shipments, costs, and carrier performance by providing visibility into deliveries, freight expenditures, and general supplies.
Contributes to the Reduction of Inventory Expenses and Errors
Overstocks and out-of-stocks are substantial barriers to profitability. Business intelligence can assist you in tracking records over time and location while identifying issues such as product faults, inventory turnover, and margins for particular distributors.
Determines the Efficiency of Equipment
Several factors can cause inefficient production. For example, errors with equipment due to improper installation, maintenance, or frequent downtime can reduce production. So, to keep industrial operations running well, one must monitor these factors.
Manufacturers can maintain their machines' health using data analytics and business intelligence. It provides real-time information about your production lines' status and streamlines production procedures.
How Business Intelligence Helped SKF (SvenskaKullagerfabriken) to Efficiently Plan Their Future Manufacturing
SKF is a key supplier of bearings, seals, mechatronics, and lubrication systems globally. The company posses its headquarter in Sweden and has distributors in over 130 countries.
Due to SKF's extensive worldwide reach and product diversity, they constantly need to forecast market size and demand for their products to modify their future manufacturing. Generally, SKF experts developed and kept their forecasts in traditional and intricate excel files. However, the efforts of maintaining and reconciling disparate studies were excessively high. As a result, SKF used require days to generate a simple demand prediction.
Later, SKF integrated its business data assets into a single system by utilizing business intelligence in production. Following that, they could swiftly begin sharing their data and insights across multiple divisions within their firm. They are now able to aggregate demand estimation fast and does not face cross-departmental issues about data integrity for the vast number of product varieties they manufacture.
This intelligent data management enabled SKF to plan their future production operations efficiently.
Business intelligence in manufacturing makes a big difference in the organization's entire operations. Given the benefits of business intelligence in manufacturing, a growing number of manufacturers are implementing it in their operations.
According to Mordor Intelligence, Business Intelligence (BI) Market was worth USD 20.516 billion in 2020 and is anticipated to reach USD 40.50 billion by 2026, growing at a 12% compound annual growth rate throughout the forecast period (2021-2026).
Hence, we may say that the business intelligence is crucial for manufacturing and is booming, thanks to its enormous potential and the numerous benefits it provides to various businesses.
Why is business intelligence so important in manufacturing?
Organization intelligence may assist businesses in making better decisions by presenting current and past data within the context of their business. Analysts can use business intelligence to give performance and competitive benchmarking data to help the firm run more smoothly and efficiently.
What value does BI add to manufacturing?
Business intelligence solutions provide insight into sales, profit, and loss, raw material utilization and can usually assist you in optimizing resources to increase your return on investment. Understanding your cost-benefit analysis enables you to manage production costs, monitor processes, and improve value chain management.
What is business intelligence's key objective?
Business intelligence is helpful to assist corporate leaders, business managers, and other operational employees in making more informed business
Article | May 20, 2021
The transformation of raw materials through mechanical, physical, or chemical processes into a new product is the definition of manufacturing in the U.S. These businesses include plants, mills, factories, and warehouses and they rely on power-driven equipment to produce their products.
Small businesses and home-based businesses are included in the scope of U.S. manufacturing - this includes sectors like tailor-made clothing, bakeries, candy stores, or toy/crafts creators. Additionally, companies that contract with the businesses in these industries are included in the sector of American manufacturing. It is worth noting: U.S. manufacturing does not include anything relating to housing or commercial construction.
Article | November 20, 2021
The manufacturing business has always prioritized providing the excellent and most user-friendly products worldwide to its target consumer groups. However, digitalization and customer interaction approaches have altered the manufacturing industry's traditional business model.
Now, manufacturers must prioritize improving the customer experience for their target consumer group and keeping up with new trends daily to flourish and remain competitive in the upgrading market. Because, in the end, the buyer is the one who drives your business and generates money. Manufacturers are committing significant efforts to improve the customer experience in the following years.
To assist manufacturers in their sincere efforts to improve the customer experience in the manufacturing industry, we have compiled some key facts that must be understood and executed by the industry's or business-specific needs.
Before going into manufacturing customer experience statistics, it's essential to understand why customer experience is so critical in the manufacturing industry.
The Importance of Customer Experience in Manufacturing
Customer service and experience are critical components of any business, which is true in the manufacturing sector. Customer experience can be described as any activity taken by a business to positively influence a customer's impression and opinion of the business, its products, or services.
“You’ve got to start with the Customer Experience and work back toward the technology, not the other way around”
– Steve Jobs.
Customer experience benefits your business in a variety of ways, including the following,
It increases customer retention
It increases the customer lifetime value
It creates brand loyalty
It influences brand reputability
It can deliver businesses with a competitive edge.
Manufacturing Customer Experience Statistics
Make your manufacturing business more customer-centric and reap the benefits that many customer-centric companies, such as Apple, Nissan, and Chick-fil-A, are experiencing.
To better understand what the customer and industry have explored regarding the customer experience in 2022, below are some statistics from well-known businesses.
Businesses that prioritize customer experience see an 80% increase in revenue.
A positive customer experience increases customer interest in the product and acts as a form of word-of-mouth marketing. This way, the business benefits from increased sales and organic promotion by genuine consumers, critical for any manufacturing organization.
# Stat 2
73% of customers say that customer experience influences their purchasing decision.
Customers are not solely concerned with the product's quality or pricing. Instead, they are interested in the complete experience they get while purchasing a product. Therefore, if customers have a negative experience during the purchasing trip, it is pretty likely that they will leave the purchase process in the middle and hunt for other viable solutions on the market. Whereas, if the purchasing journey and post-purchase service are satisfactory, they will gladly purchase the goods and suggest new clients to your business.
# Stat 3
By 2023, AI and machine learning will manage around 40% of all consumer contacts.
(Source: Super Office)
Manufacturing production and revenue are increasing as a result of technological advances and applications. However, the customer experience is not far behind in implementing cutting-edge technology like AI, VR, and AR. For instance, chat bots are the best example of how artificial intelligence, natural language processing, and machine learning are being used to increase consumer engagement.
Virtual interaction is becoming more prevalent in the manufacturing industry daily, and both manufacturers and customers like this digital interaction.
“Our interactions with our customers have become much more virtual, which frankly seems to work well for the customer and us.”
-Scott Heide, Chief Executive Officer at Engineering Intent Corporation
Technology application in manufacturing will be maximized, and businesses intend to automate the customer experience by 2023.
# Stat 4
According to 70% of customers, an ideal customer experience should be quick, convenient, and cooperative, as well as friendly.
Customer service is a skill, and it's always a good idea to put yourself in your clients' shoes. According to an Adobe study, 70% of customers want a quick and convenient service that saves them time. In addition, they anticipate full collaboration throughout the purchasing process, including post-purchase servicing.
# Stat 5
72% of customers with a good consumer experience will tell six or more people about it.
(Source: Nice Reply)
In the first statistic, we discussed word-of-mouth marketing. You will always receive referrals for the excellent products or services you provide to your target consumer group. Customers that have a positive experience will always bring you two additional potential customers, and this number will grow exponentially with each pleasant experience delivered by your organization.
How did MacDonald's plan to increase revenue simply by improving the customer experience?
When McDonald's revenues started to decline, they focused on the customer experience rather than marketing strategies.
They began by listening to their clients and giving them a more streamlined experience. Customers told McDonald's to simplify the menu, increase order accuracy, and use higher-quality ingredients.
McDonald's also improved store interiors and introduced digital self-order kiosks and table service, reducing customer wait times. BTIG predicted a 4.1% increase in revenues as these modifications were made. As a result, McDonald's may outperform competitors by improving total customer service.
Customer experience is crucial in manufacturing, and manufacturers must leverage digital customer experience trends to improve their reputation. These a fore mentioned customer experience statistics can assist you in shaping a compelling client experience for 2022 and propelling your organization to new heights of success.
Why should a manufacturing company invest in customer experience?
Client experience improves customer retention, builds brand reputation, and gives companies a competitive edge. So manufacturers must invest in the consumer experience.
What is the difference between customer service and customer experience?
Customer service is one aspect of the customer journey, whereas consumer experience is the sum of all customer encounters with the brand.
What does a customer experience include?
Customer experience is the overall perception of your business or brand. It is the consequence of a customer's engagement with your website, customer service, and the product they purchase. So, it is the aggregate of all elements from browsing to buying to the product experience.
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