Operational Excellence is a process that aligns people, processes, and capabilities to achieve steady growth and improvement. In short, implementing an Operational Excellence program streamlines organizations to maximize efficiency, allowing them to cut costs, improve product quality, and ensure consistency and cohesion in the manufacturing process.
Efficiency is one of the most significant aspects of Operational Excellence with core tenets being a reduction of errors and seamless processes. The ability to deliver value to the customer in a timely and organized manner is integral to operations.
Gaining insights from data is a major challenge companies struggle with in the face of digital transformation. When organizations are able to utilize their data to successfully gain insights required to identify, prioritize, and concentrate resources on the most important production constraints, they unlock the ability to seamlessly provide valuable service to the customer.
Making a conscientious effort to achieve Operational Excellence is a strong growth strategy for manufacturers. Implementing best practices, such as investing in efficient operations and digital transformation, sets a high standard for team members and customers alike.
Industry 4.0 is the application of IoT, automation and robotics, predictive maintenance, simulation, and additive manufacturing to transform the way manufacturing companies operate. The fourth industrial revolution is driven by a need for Operational Excellence – to boost efficiency, better handle uncertainty, improve quality, reduce downtime, and transform existing business models.
Most companies struggle to utilize their data in ways that allow them to successfully unlock the insights required to identify, prioritize, and focus resources on acute production constraints. However, with a standardized performance management approach leveraging the Industrial Internet of Things (IIoT), manufacturers can automatically collect and analyze the takt and cycle times to identify evolving bottlenecks across their work centers, lines, and factories.
While companies often collect lots of data, they lack the insight to know what it means – which problem to solve first, and subsequently, how to provide the most impactful solution. If there is an incomplete understanding of the scenarios related to the identified loss area, the chosen improvement might not deliver the desired results. When management and manufacturing teams don’t work in lockstep, a lack of visibility and cooperation can lead to equipment issues falling through the cracks – ultimately increasing downtime. Frontline workers and management must align to proactively analyze the data and boost productivity.
It is very difficult to uncover operational tendencies, as well as create corrective actions, without comprehensive, accurate insights. Outdated manufacturing systems lack coordination between management and manufacturing teams, opening the door for various disconnects and too many moving parts. These analog processes are largely incapable of handling more intricate issues like downtime, meaning systematic upgrades are needed to face the increased number of variables affecting production performance today.
Lastly, it is difficult to follow the status of those corrective actions and measure their corresponding impact, whether it be functional or financial.
The most advanced way to achieve Operational Excellence is to approach it alongside digital performance management (DPM), which is a systematic, closed-loop problem-solving approach empowered by four digital capabilities: prioritization, analysis, improvement, and validation. This allows manufacturers to identify, prioritize, analyze, and validate the absolute top opportunities for financial improvement more easily. By collecting data and delivering it to powerful and secure on-premise OR cloud-based platforms, a DPM solution is able to increase production efficiency by at least 5-20%.
Learn how a Digital Performance Management (DPM) approach to Operational Excellence can normalize production data, identify bottlenecks, and more.