Data is often said to be the new oil – a crucial resource that can transform businesses and fuel growth. And just as oil was a critical component of the Industrial Revolution, data is now powering the Fourth Industrial Revolution, also known as Industry 4.0.
For manufacturing companies, data has become more valuable than ever before. But unlike oil, which eventually runs out, data becomes more abundant as the manufacturing industry becomes increasingly digitized. Today, every machine equipped with many sensors or state-of-the-art ERP systems generates immense amounts of data that can improve production processes, enhance product quality, and optimize supply chain management.
However, with the abundance and variety of data sources comes a new challenge: how to handle it all. Manufacturing companies can quickly become overwhelmed by the sheer volume and wide range of data their operations generate. Without a robust data strategy that outlines how an organization manages, collects, stores, analyzes, and utilizes its data assets and without a solid data foundation that ensures having the right data at the right time and place, handling data becomes mission impossible.
That is where a data team comes in. By leveraging data and business intelligence tools, a data team can help manufacturing companies harness the power of their data to achieve operational excellence. In the following paragraphs, we provide a non-exhaustive description of tools and analyses that can achieve this mission.
Predictive analytics is a powerful tool that can help manufacturing companies make proactive decisions by analyzing historical data, identifying patterns and trends, and predicting future outcomes. Predictive maintenance is a prime example of this, as it uses machine learning algorithms to detect when equipment is likely to fail before it does, allowing for preventive maintenance to be performed before a breakdown occurs. Another well-known example is cost forecasting, which uses data to predict future expenses and helps manufacturing companies plan budgets accordingly.
Improving efficiency and effectiveness in manufacturing operations is of the utmost importance. Process optimization & automation is an area where data-driven approaches can provide significant benefits in this respect. By employing process mining, companies can identify inefficiencies and bottlenecks in their production processes and improve overall efficiency.
Despite having a well-designed efficient process and qualitative system, it is always possible to have problems with the product or production process. Root cause analysis is one of the most common methods to identify the underlying causes of quality issues, equipment failures, and other problems. Often, the analysis lacks sufficient historical data or data is scattered around the organization, affecting its quality. Fortunately, a root cause analysis that uses machine learning algorithms and predictive analytics, can quickly identify the underlying causes of production failures and help the company implement corrective actions.
Finally, management dashboards enable manufacturing companies to visualize data meaningfully and make informed decisions based on real-time data. Improved operations dashboards such as mission control, Overall Equipment Effectiveness (OEE), shop floor overview, supplies monitoring, and room/asset availability dashboards, provide manufacturing companies with valuable insights into their operations and help them optimize performance. Self-service BI tools, on the other hand, enable end-users to create their own reports and analyze data without relying on IT or data teams, making data more accessible and actionable for everyone in the organization.
Are you ready to take your manufacturing operations to the next level by harnessing the power of data? Be sure to reach out. We would like to share our expertise and help you become a truly intelligent data-driven organization. Contact us today to get started!
