The Key to Using Manufacturing Data for Better Decision-Making

Explore data-driven operational excellence  

The effective use of data in manufacturing sparks critical conversations from the frontline to the boardroom on how to achieve and sustain operational excellence (OE). The concept has gained significant traction since the 1989 Exxon Valdez oil spill, which prompted the development of OE management systems. Decades since, analysts and consulting firms continue to emphasize its importance, underscoring the need for effective data management strategies.

However, creating a workplace culture of sustained OE remains a key, and underappreciated challenge. In our new on-demand webinar, Maintaining Operational Excellence in Manufacturing, we discuss how to address this challenge to utilize data effectively to improve efficiency, productivity and overall business outcomes. 
 

Why Data-Driven Operational Excellence is Important 

Data-driven OE proves essential for manufacturers that aim to enhance safety, talent and quality while reducing costs. In fact, companies like management consulting firm, Bain & Company, highlight the significant impact of lean manufacturing methods, which can reduce key operational costs by 50%. Research shows that the adoption of data-driven lean methodologies can achieve up to 100% improvement, typically resulting in a 30% cost reduction.

Such cost reductions for high-volume, low-margin producers can increase production volumes, enable additional investments and diversify product lines. Similarly, companies with high-value, low-volume products can use cost savings to optimize operations and expand their portfolios. These measurable outcomes underscore the importance of data-driven strategies to achieve and sustain OE. 
 

The Challenges Manufacturers Face  

First, what does OE mean? OE requires organizations to honestly self-assess to maximize their return on investment. Companies identify the best version of their operations from perspectives like technology, efficiency and productivity. OE encompasses rules that govern the optimal use of data, assets and human capital to achieve the highest possible metrics. Each organization's OE outcomes will differ based on its specific nature and business context. 
 

The Culture Challenge 

Change in an organization's operating culture poses a significant hurdle to meeting OE goals. Many manufacturers resist discussions that link business outcomes to culture change because of its inherent difficulty. However, effective data management and decision-making processes depend heavily on cultural shifts.  
 

The Quality of Data Issue 

Data quality also plays a crucial role in OE goals. Companies often discover that their historical data, though digitized, may lack accuracy and reliability. For example, handwritten operator logs converted into digital formats may lack consistency.  
 

Why Aren't More Companies Successful at Addressing Challenges? 

Many companies struggle to address operational challenges effectively because they oversimplify the journey toward OE. Organizations often treat the problem as merely an issue of data access. Leaders believe gathering extensive data and making it available to stakeholders will improve decision making. However, this approach overlooks critical nuances. 

How Manufacturers Can Get on the Right Path 

Join us to learn how to use existing data to make informed decisions and foster a culture that supports continuous improvement. Watch our on-demand webinar "A Data-Driven Approach to Maintaining Operational Excellence in Manufacturing" to unlock the potential of data-driven OE and drive better business outcomes.