Manufacturing has been the steady backbone of global economies for centuries. Yet manufacturing is also defined by constant change, as it uses raw materials to create objects that are more valuable than the sum of their parts. The resources that manufacturers use change as well, and these days the world’s most valuable asset isn’t something you can even physically manipulate.
In almost every way imaginable, data and analytics have altered manufacturing. By transforming the procurement of raw materials, optimizing workflows, and shipping products, data has rewritten the rules of the manufacturing process and operations, as well as how manufacturers conduct business.
Modern manufacturing contains numerous connected machines and systems that continuously generate thousands of data points. Without knowledge of how these systems work, without any IT experience, you can still delve into complex data sets and draw valuable, actionable business insights.
Imagine the ability to create products that customers want before they know they want them. Imagine working with machines that alert you when repairs are needed months before they break down. These might sound like futuristic fantasies, but they are already active in factories nationwide—helping businesses drive results.
The key is to build data and analytics within a modern enterprise resource planning (ERP), a system capable of mining and processing information for all aspects of your business. In the past, manufacturers may have been prone to siloed systems that produced vanity metrics. Now 38% of manufacturers say that analytics platforms and ERP systems are the software projects that provide the quickest impact in uncertain times.
Modern ERP: The Foundation of Business Analytics
Modern ERP software enables businesses to generate and utilize data from all aspects of their operations, from financial statements to supply chain and machine management. This data-driven approach can significantly enhance operational efficiency and profitability—one reason why 67% of manufacturing leaders are embracing a data-first strategy in their businesses.
With modern ERP, manufacturers can go beyond the traditional data analysis predicated on a closed-loop framework. Instead, you can use five types of analytics to create a complete cycle of understanding, predicting, and improving outcomes:
- Descriptive: Helps you understand why things happened.
- Diagnostic: Reveals critical errors to fix.
- Predictive: Shows what may happen based on historical data.
- Prescriptive: Describes actions to take.
- Prognostic: Estimates timelines and progression of future system events.
These levels of analytical capabilities show the growing importance of data in the manufacturing industry. It’s not just about collecting data, but about using it to make informed decisions that can improve business operations and drive growth.
How Modern Data Platforms Turn Information Into Insights
A solid data infrastructure is the cornerstone of a robust analytics program. The ability to seamlessly integrate various data sources and provide user-friendly tools for data storage, processing, and manipulation empowers average business users to extract valuable insights through an intuitive low-code/no-code user experience. When paired with modern ERP systems, this robust infrastructure simplifies complex data tasks, promoting a culture of data-driven decision-making and business expansion.
Investing in machine connectivity through advanced software like an advanced manufacturing execution system (MES) enables a closed-loop analytics framework to view your business. This software acts as a bridge between machinery and data analysis, facilitating real-time data collection and thereby enhancing operational efficiency and decision-making. Such an investment cultivates a culture centered around data, driving businesses toward innovation and growth.
Adding to the benefits of a modern data platform is the power of predictive analytics and financial reporting. This tool takes data processing a step further by forecasting future business trends based on current data, allowing businesses to anticipate changes and strategize accordingly. Furthermore, it offers comprehensive financial reporting, providing a clear view of a company’s financial health. This empowers businesses to make informed financial decisions, manage risks, and ultimately drive profitability. The integration of predictive analytics and financial reporting into a modern data platform underscores the transformative potential of data in today’s business landscape.
Leveraging a modern infrastructure is about more than just having the latest technology. It’s about developing a system that can handle the vast amounts of data generated in a manufacturing environment, and turning that data into actionable insights. This can help businesses identify inefficiencies, predict future trends, and make strategic decisions leading to increased productivity and profitability.
Why Democratizing Data Helps Build a Strong Workforce
Once the exclusive domain of IT professionals, a truly modern ERP system empowers everyone to transform vast data volumes into actionable insights. In a time when 60% of frontline manufacturers say they would take a pay cut to leave their current company for a more technology-driven factory, democratizing data is critical for both improving business outcomes and building a strong workforce.
This approach empowers operational support roles to drive and own analytics for continuous improvement. These roles already have analytics skill sets, are most accustomed to providing decision support to operations, and fit easily within their existing business processes.
Direct control and ownership of analytics by operations is highly correlated to follower status. While operations needs to set the vision, strategy, and priorities, they can then relinquish ownership and control of analytics to others. This approach helps ensure that the right people are focusing on the right tasks with the right insights, leading to more efficient and effective operations.
Democratizing data doesn’t just make data available to everyone. It helps build that culture where data is valued and used effectively. It helps train employees to understand and use data and provide them with the necessary tools and support. This can lead to a more informed and engaged workforce that can drive organizational innovation and improvement.
Using Data to Bridge Communication Gaps
In a typical manufacturing operation, numerous employees work on different projects in various departments and locations—dozens if you’re a small business, hundreds if not thousands for larger enterprises. Synchronizing such a diverse workforce can be challenging. However, intelligent data-driven business analytics can bridge these communication gaps by giving all personnel access to the same insights and ensuring that everyone is working towards the same goal.
For instance, sales teams can have access to social network chatter analytics and regional consumer data that can help them identify pools of new potential clients. Statistical analysis can then be used for customer segmentation to enhance the effectiveness of new marketing efforts. Sales managers will also have access to data measuring performance across different teams, regions, and customer pools that they can use to identify in which areas their marketing dollars are best spent.
Production teams can then use this data generated by sales to know exactly how much inventory they need to produce. Supply managers can leverage this knowledge to inform their relationships with suppliers and vendors, knowing how much supply to order and when it is most needed.
Turning Your Supply Chain Into a Value Chain
In manufacturing operations, productivity and profitability are only as good as a supply chain. With supply chain management (SCM) solutions, you can gain new perspectives on your supply chain’s inner workings. You’ll know when, how much, and from whom to order the materials that keep your factory producing. It can also help you get a clearer picture of your inventory and better understand how long that inventory might last when assessed through the lens of sales data and environmental factors.
Using analytics, a manufacturing operation can generate reports on all the suppliers it currently uses, along with all the other potential supplier relationships within a certain desired proximity. This allows the manufacturer to choose based on pricing, inventory, and potential environmental constraints. It can also allow for better negotiation leverage and consolidation of the supply chain across multiple vendors.
Reimagining Research & Development
Research and development (R&D) are crucial to any manufacturing operation. R&D is a time-consuming and costly process with a wide margin of error. However, with access to a rich data fabric of insights, R&D can be more efficient, accurate, and cost-effective.
Analytics allow for expanding R&D scope, enabling collaboration with suppliers and customers. Many ERP systems can create a co-creation platform where customers and suppliers can influence the design of new products with crowd-sourced input, eliminating guesswork and ensuring better design-to-value margins.
Traditional point-of-sale data is also complemented with information from new sources, such as social media interaction and market trends. With this deep and predictive analysis, you can identify precisely where the market is headed and know exactly how you need to pivot to keep up. Customer involvement in the product design process doesn’t just improve innovation—it makes it faster.
In a competitive industry, time to market can often be the biggest difference-maker in profitability. More accurate market trend insights and customer involvement can significantly shorten the time to market by eliminating the need for lengthy prototyping and research phases. Quicker development times means hitting the market before the competition starts on production. This allows you to increase market share, establish industry standards, and create more customer loyalty.
Beyond creating new products, many manufacturing operations have even been able to significantly optimize their business strategy based on identifying once-invisible trends. For instance, by mining and processing critical market data, a company might discover that one of its products has generated a secondary market for spare parts for which its customers are turning to other vendors. With this knowledge, they can expand their sales operation to include those valuable spare parts and provide servicing and repairs for the product in question. A deeper understanding of market trends and enhanced customer communication make small shifts in strategy possible that could lead to significant changes in profit margin.
Upping Your Smart Factory’s IQ
In the past 10-15 years, no technological development has impacted manufacturing more than the Industrial Internet of Things (IIoT). While IIoT’s primary function has always been allowing the user to communicate with their machines, business analytics allows the machines to communicate with you. A data-driven ERP can allow your smart factory to generate valuable data from your operation and identify your biggest opportunities for optimization.
While in the past, addressing equipment failures has been a measure of how fast you can react, with data, it becomes a measure of how far ahead you can predict. While interacting with each machine’s sensor, your ERP can tell you exactly which equipment operates at diminished efficiency and which requires repairs far ahead of their ultimate breakdown. This allows you to help ensure that the system will never let you down when it’s most needed, allowing you to better plan maintenance for times when operation needs might be slower.
3 Tips For Joining the Data Revolution
Modern, innovative ERP can help ensure that manufacturers have access to leading-edge technology to drive their business. Here are a few tips for turning your production business into an automated machine and joining the data revolution.
1. Start small, expand big
With such wide-sweeping functionality and implications, no software company would ever ask you to overhaul your entire operation at once. When embracing business analytics, it can be helpful to start with a few functions that can be easily implemented, such as financials and sales tracking.
2. Customization is key
Every manufacturing operation is unique, so a suite of relevant tools could never come in a one-size-fits-all package. Your system should be customized to meet your factory’s needs, with different tiers of functionality that can be scaled up or down at any time.
3. Treat data like just another tool in your box
While new technology can always be daunting, business analytics is not designed to fundamentally change how you run your business. With relevant data and insights at your fingertips, you can apply your years of experience and intuition with expanded vision and control.
