December 15, 2016 / Cost Management, industry, maintaining talent, quality, ROI, strategic planning, training
Industrial manufacturers find themselves competing in an increasing uncertain global market with rising customer expectations and ever-evolving technology, according to the 19th Annual Global CEO Survey from PricewaterhouseCoopers (PwC).
The survey found that only 24% of manufacturing CEOs think global growth will improve over the next 12 months compared to 34% last year, and 23% think it will worsen compared to 18% the prior year. In addition, just 29% of industrial manufacturers are confident of revenue growth in the next 12 months, but when given a three-year span, 46% of manufacturers think they’ll see growth.
Data also suggests that CEOs believe business risk has increased. According to the survey, 55% of industrial manufacturing CEOs said opportunities have increased during the past three years; however, 61% believe the number of threats has increased.
The PwC survey, which interviewed 205 industrial, manufacturing CEOs in 53 countries, revealed that industrial manufacturing companies are working hard to deliver results year after year, but most understand that the future brings complex challenges. The survey highlights three key focus areas for today’s industrial manufacturing CEOs:
- Great expectations and influences. When asked to describe their company’s purpose, the survey found many industrial manufacturing CEOs believed it was centered on filling customer needs or developing first-class products, but others said it was creating a great place to work for employees or achieving social goals. And the influences that impact that purpose and overall strategy are many. As one would expect, customer demands drive final products, but 89% of industrial manufacturers say their customers and clients have an impact on their overall business strategy. Supply chain partners weigh-in, too, with 88% of CEOs planning to address social and environmental impacts of their supply chain. In addition, competitors and peers are also a focus, with a third of CEOs saying they too have a high impact on strategy.
- Technology and talent. Executives know Industry 4.0 has arrived and are working to invest in new innovations and train their workforce to capitalize on their investments. The survey found that 90% of industrial manufacturing CEOs plan to make changes in how they use technology to assess and deliver on wider stakeholder expectations. However, with new technology comes new skill requirements, and 76% of respondents say they are concerned about the availability of key skills to grow their business. In response, more than half of CEOs are changing their talent strategy.
- Measuring and communicating success. Data showed that 60% of survey respondents said innovation is the number one area where the business could do more to measure the impact and value for stakeholders. Not only are CEOs realizing they need to measure and track business success, but that they also need to communicate that success. The survey found that 68% of CEOs believe R&D and innovation has the potential to drive better engagement with wider stakeholders. Together with customer relationship management, data and analytics take the top three spots—validating smart manufacturing will be a driving force for industry leaders.
Like any industrial manufacturer, PwC’s survey findings can help metal-cutting organizations prepare for another challenging, but transformative, year. As reported in the case study, “Best Practices of High Production Metal-Cutting Companies,” sometimes this means investing in technology. Jett Cutting Service, for example, hit a record-setting 1.1 million cut parts last year and attributes the milestone to smart investments. “I would like to believe that our increase in sales is due to investing in the latest cutting technology, which increases our capacity and production capabilities,” Vice President Mike Baron said. “The newer technology also allows us to offer competitive pricing, which has led to many new customers.”
However, Jett Cutting also understands that it needs to be just as committed to its employees and its customers. The metal-cutting organization also has a strong training program for new employees, an ISO certification program to maintain high quality standards, and additional training for existing employees every time new equipment or software is purchased.
For many metal-cutting companies, 2016 certainly hasn’t been the best of years, but it also hasn’t been the worst. As PwC’s survey confirms, no one is confident about what next year will bring; however, industrial manufacturing leaders aren’t standing idle. Jett Cutting and many others are investing in new technology and training now to prepare for growth in the future.
How is your industrial metal-cutting company investing in the future?
October 30, 2016 / agility, benchmarking, best practices, bottlenecks, continuous improvement, Cost Management, industry, LIT, predictive management, preventative maintenance, quality, strategic planning, workf
In today’s competitive and quickly changing market, manufacturers are finding that it pays to be proactive—not reactive—in their strategic approaches. That’s why a growing number of industrial manufacturers are starting to take a serious look at advanced technologies like predictive analytics, which allows them to not only measure performance, but to also predict and prevent future challenges.
According to Deloitte’s 2016 Global Manufacturing Competitiveness Index, more than 500 senior manufacturing executives from around the world ranked predictive analytics as the number one technology vital to their companies’ future competitiveness. As reported here, another report from Aberdeen Group shows that 86 percent of top-performing manufacturers are already using predictive analytics to reduce risk and improve operations, compared to 38 percent of those companies with an average performance and 26 percent of those with less than stellar results.
The trend has found its way into industrial metal cutting as well. According to the LENOX Institute of Technology’s benchmark study of more than 100 industrial metal-cutting organizations, companies can gain additional productivity and efficiency on the shop floor by “investing in smarter, more predictive and more agile operations management approaches.”
What is Predictive Analytics?
Predictive analytics utilizes a variety of statistical and analytical techniques to develop mathematical models that “predict” future events or behaviors based on past data. As the Deloitte study explains, this allows companies to uncover hidden patterns, relationships, and greater insights by analyzing both structured and unstructured data.
In a manufacturing environment, companies can use predictive analytics to measure the health of production equipment and detect potential failures. However, the possibilities are virtually limitless. According to one analyst’s blog, manufacturers could potentially use software and predictive analytics to forecast potential staffing or supply-chain interruptions, such as a flu outbreak that could cause a temporary personnel shortage or even a blizzard that could disrupt deliveries.
Bearing manufacturing leader Timken has taken a different approach and is using predictive analytics to improve inventory optimization and supply chain performance in the automotive aftermarket sector. As reported by SearchAutoParts.com, Timken is leveraging sales history, registration data, and other information, along with complex analytics, to improve sales and reduce costs.
“Timken’s catalog team matches parts and vehicles, and combines that information with vehicle registration and replacement/failure rates, along with internal sales data,” the article explains. “Crunching that data using proprietary algorithms helps them predict how many parts will be needed in a given geography, and how those parts sales will fall within the premium aftermarket, economy aftermarket and OEMs.”
Common Use Cases
Because predictive analytics is an emerging technology, applications are typically specific to each manufacturer’s products and processes—as in the Timken example. However, an article from Toolbox.com describes four common use cases for predictive analytics that are applicable in most manufacturing environments:
- Quality Improvement. Improvements in databases and data storage and easier-to-use analytical software are the big changes for quality improvement. Standard quality improvement analysis is being pushed toward less technical analysts using new software that automates much of the analytical process. Storing more information about products and the manufacturing process also leads to analysis of more factors that influence quality.
- Demand Forecast. Predictive analytics takes historical sales data and applies forms of regression to predict future sales based upon past sales. Good predictive analytics modelers find additional factors that influenced sales in the past and apply those factors into forecasted sales models.
- Preventative Maintenance. Predictive analytics increases production equipment uptime. Knowing that a machine is likely to break down in the near future means a manufacturer can perform the needed maintenance in non-emergency conditions without shutting down production.
- Machine Utilization. Predictive analytics applications for machine scheduling combines forecast for demand with product mix to optimize machine utilization. Using new predictive analytics techniques improves accuracy.
While there is no question that predictive analytics is still new to many ball and roller bearing manufacturers, industry leaders know that proactive strategies are key in today’s uncertain market. Finding ways to anticipate future events and reduce unplanned downtime can not only help your operation gain efficiency but, more importantly, help you stay competitive.