Many manufacturers are entering Industry 4.0 with technology systems and business processes better suited for a bygone era. Now is the time for manufacturers to take a realistic look at their current operations and determine if they have the right technology in place.
Manufacturers can begin assessing their Industry 4.0 readiness by focusing on four key operational areas: workforce, business processes, assets, and customer experience. Once they begin this assessment, manufacturers may find that productivity limits have been reached and will not improve unless new technologies are implemented. They may find they aren’t currently well equipped to take full advantage of new business models. They may uncover they don’t have the necessary connectivity to share and view data globally, internally and externally. They may also find they lack the mobile and remote working capabilities required by a new generation of workers, or the ability to meet the customisation and personalisation demands from customers.
To be even more specific, manufacturers may find that the way they support their business is outdated. They may have a patchwork of systems in place that communicate with each other inefficiently, or not at all. Processes may be cobbled together, creating waste in time, resources, or materials. Or they may discover their problem-solving strategies have been limited to short-term solutions that have resulted in disconnected business systems, lack of executive buy-in, no technology roadmap, or lack of a unified data strategy.
Going through this rigorous assessment may be painful, and the results can feel overwhelming. However, this time of discomfort will prove necessary to help manufacturers chart a successful course to win within Industry 4.0.
There are the top four optimisation opportunities manufacturers should consider as they prepare for success in the Industry 4.0 era.
Manufacturing is facing a significant skills gap. Experienced professionals are retiring at a significant pace, and it has been difficult for the industry to attract and retain new talent. When many of today’s workers entered the job market, topics like data science and machine learning may have seemed like science fiction. Existing personnel may feel their skillsets are not aligned with evolving expectations, which can add tension and lead to their exit from the workforce.
For the new generation, expectations of a workplace with modern technology may cause recruits to look elsewhere when considering a future employer. Furthermore, attempts by either management or front-line workers to retain outdated organisational structures and antiquated job descriptions can create roadblocks down the line. Teams that are locked into set processes and hesitant to forge new paths can quickly derail the entire digital transformation process.
Enterprise-wide modernisation requires a workforce that is well-prepared, receptive to big ideas, and willing to execute new tactics. Likewise, having an open mind to change can yield organisational and personal opportunities. Building a company culture that values innovation and collaboration is a necessary first step in a successful digital transformation.
With expectations and priorities well-defined and feedback loops in place, managing workforce resources — from entry-level trainees to business unit managers — will be easier and more effective. Technology can help create an environment where personnel feel engaged and aligned with enterprise goals. Workforce management solutions, as well as functionality within modern ERP solutions, can help manufacturers:
- Gain access to relevant, timely data through role-based dashboards
- Identify, attract, retain, and utilise top talent
- Provide mobile access to work instructions to expand their service business
To ensure a smooth transition to new digital concepts, the workforce needs to be educated and given opportunities to participate in decision making. Helping employees understand overarching goals is the first step. The next is demonstrating its value and outlining the benefits. Lastly, arming personnel with technological tools will improve their own work experience and soon show them first-hand the advantages of accepting technology in the workplace.
Modern IT solutions, from workforce management solutions to reporting and analytics, will help an organisation plan the use of resources and control labour costs, while also enhancing the employee experience. Digitalisation can transform a manufacturer’s plant and provide a solid foundation for future growth. Above all, beginning with the creation of a culture of change will ensure that larger digital initiatives get off the ground successfully.
The root cause of almost all bad decision making and inefficiencies is bad data. Interviewing people individually to find out where the value is in a dataset provides opportunities for mistakes and is incredibly time consuming. AI can analyse a system to identify potential bottlenecks, discover places to implement or reinforce best practices, and seek out opportunities to improve and automate repetitive tasks. This powerful technology introduces transparency to business processes and reveals inefficiencies that may be preventing an organisation from achieving a higher level of performance and customer service.
In today’s environment, taking extended periods of time to gain purchasing approval or get a clear view of inventory levels can have far-reaching consequences. Manufacturers, contractors, and suppliers need to move with confidence, seizing opportunities that may have narrow windows of opportunity.
A holistic approach that provides visibility into all business processes will provide manufacturers with greater transparency and the ability to make well-informed business decisions. This can be achieved by consolidating software within one system or by implementing a two-tier ERP strategy. With a two-tier ERP strategy, the plant can focus on the operational business systems needed to run that location, while headquarters can focus on the financial management and other necessary systems needed to run the organisation overall.
Regardless of which strategy the manufacturer chooses – single system or two-tier ERP – they will benefit from a consolidated view of financial planning, demand forecasting, lifecycle pricing, assortment planning, replenishment optimisation, and more. The addition of machine learning brings precision to every point of the supply chain with AI that can sense, predict, and fulfil demand based on real-time market data.
Digital transformation of the supply chain depends on a solid foundation of visibility and trust; trust in the supply network and trust that a company will be able to deliver goods whenever and wherever there is demand. However, transformation doesn’t come easy, and any investment in the supply chain must deliver measurable results.
A commerce network connects businesses to their entire supply chain – from suppliers and manufacturers, to brokers, 3PLs, and banks – paving the way for enhanced supply chain visibility, collaboration, and predictive intelligence.
By taking a staged approach to digital transformation and building greater connectivity across the supply chain, businesses can pave the way toward a fully connected future, while still being able to tackle the biggest challenges they face right now.
Technology is changing at a rapid rate, making it difficult for manufacturers to stay on top of the latest innovations. With today’s high expectations for stretching resources and keeping current systems operating at their peak, manufacturers need every time-saving tool they can get. The potential gains in efficiency and productivity from various technologies can help manufacturing operations run smoothly. Affordable sensors can monitor equipment for early warning signs of downtime. Leveraging the IoT to connect data from these sensors to enterprise asset management systems enables early detection of performance issues, allowing for timely intervention before there are major repercussions.
These sensors produce massive amounts of data, reaching an immense level of volume and complexity. The data, with the context of time and place, must be sorted for it to have meaning. Without analytics, it is useless. Predictive analytics use embedded functionality such as artificial intelligence and machine learning to recognise patterns and apply data science algorithms to project future incidents. In the maturity model for asset maintenance, a prescriptive approach is considered optimal.
This will be even more important in the post-digital era. In this approach, advanced enterprise asset management solutions suggest preventive tactics, prescribe how to act, and predict the outcome. Prescriptive maintenance uses predictive science and algorithms to provide a glimpse into the future and anticipate how the asset’s performance can be optimised. For example, plant maintenance teams, asset managers, utilities, and facility managers are keenly aware of the substantial costs associated with energy and the critical role it plays in the smooth operation of industrial plants and commercial facilities. In fact, as energy costs continue to escalate, energy consumption is increasingly becoming a key focus of the cost-conscious asset maintenance teams. The data collected can point to opportunities for savings as well as indicators of asset health. Technology can help monitor energy usage, giving managers a valuable tool in managing this major expense.
Historically, manufacturing has been notorious for a “take-it-or-leave-it” business model. For decades, the formula for profitability in discrete manufacturing was in creating made-to-stock inventories of products with as little variation as possible. Process manufacturers could depend on recipes and ingredients that remained unchanged for decades, from juices and soft drinks to beer and cheese. Distributors and retailers had the responsibility to engage with customers, listen to their feedback, and work with manufacturers to initiate any changes or innovations for product improvements.
Direct feedback rarely reached the designers, engineers, and product development teams who sat at the drawing board envisioning new releases. The Industry 4.0 era has rewritten the rules for customer engagement. Customers expect rich, compelling experiences and highly tailored transactions. Leading manufacturers are implementing technology that delivers a seamless experience for their customers.
AI can introduce transparency to business processes and reveal inefficiencies that prevent an organisation from achieving a higher level of performance.
Automated quoting and customer self-service network to track materials globally
It’s imperative for manufacturers to bring customers into the design process, even though customers may not have the technical language to easily share their ideas and concepts with professional product designers. Manufacturers can help bridge this communication gap with a solution that gives customers design parameters that are practical and based on best practices. This kind of environment gives customers the freedom to customise and submit their product ideas and gives product designers an efficient starting point to build out the technical specifications required for production.
Configure-price-quote (CPQ) technology is helpful at this stage. It can help foster the custom order process with advanced visual product catalogues and search capabilities similar to tools such as Google, and guide customers through the process of isolating the precise product, options, and configurations to fit their unique needs. Through pre-built account rules and compatibility constraints, CPQ tools can limit customers to creating only orders for end products that are viable from the manufacturer’s standpoint, while still empowering the customer with choice and flexibility.
An integrated approach between the CPQ and ERP systems ensures coordination between all disciplines and specialisations within the enterprise. Breaking down organisational silos as the quoting process crosses department boundaries allows for a more timely and automated production of a quote, ultimately delivering a more seamless experience for the customer.
Data insights generated from the IoT enable manufacturers to turn a traditional product offering into a service. This new customer-centric feature becomes a differentiator, adding value, building relationships, preventing commoditisation, and adding profits.
Leading manufacturers are adopting a subscription-based business model, which creates a recurring revenue relationship by charging customers a regular, generally time-based fee. Although this business model is relatively complex, manufacturers can manage it by taking advantage of modern technology.
This approach allows manufacturers and distributors to increase their focus on customer experience while positively impacting their bottom line.
Chart a course for Industry 4.0 success
Industry 4.0 is forcing manufacturers to take a comprehensive look at how their operations are equipped to address today’s top challenges, including the talent shortage, inefficient business processes, supply chain complexity, asset management, and meeting customer demands.
Industry 4.0 can be overwhelming, but with a strategic roadmap in place and a keen focus on the four key areas – workforce, process, assets, and customer experience – manufacturers will gain momentum and be well positioned for success within this new era.
Nick Castellina, Infor