Last week, we shared some of our most recent quality management data. Our post Cost of Quality: More than Risk and Compliance discussed the relationship between quality management objectives, financial objectives, and whether or not companies choose to measure the cost of quality. The results were intriguing, prompting us to take a deeper look into the cost of quality metric and its correlation with other variables.
Minimizing costs has been and always will be a critical component of industrial strategy. The growing global supply chain helps to improve operating margins, but in many ways, its complexities make it more difficult to compete. Additionally, regulatory burdens, among other areas, further shrink operating margins. Faced with pressure, managers are continuously looking for innovative solutions to improve financial and operational performance.
Creating a system of metrics that can be monitored, analyzed, and improved upon over time should be on the short list for any Operational Excellence model. Because there are so many metrics to choose from, it's understandable that decision-makers focus more on the final numbers than on how they were derived. In our Executive Dashboard series, we aim to break this habit, drilling down on the variables of the most important metrics to provide an additional level of granularity for top decision-makers. This week we discuss the Cost of Quality model.
To effectively provide high quality products, quality management has to become part of each employee’s everyday thought process. Market leading companies can easily attest to the operational, branding, and bottom line benefits of this approach. However, adopting an enterprise-wide how will this decision affect and improve quality mentality is far more difficult than just sending out a memo. It has to be strategically implemented into an organization’s culture over time.
In our last blog, we talked about metrics that can help corporate executives better understand the effectiveness of quality management strategy in their organization. In this blog, we will be discussing metrics that are a must for the dashboard of any plant manager. If you are involved in quality and operations decisions for manufacturing or supply-chain management, one of your most important responsibilities is to ensure that the final output of your plant is in compliance with internal and external quality standards.
If you're responsible for managing operations, the following scenario won't be new to you: You have a meeting with the executive team tomorrow and you are running around to get information on metrics for your presentation. The next day, you're expected to report on the overall performance of your plant to several department heads.
Enterprise Quality Management Software (EQMS) is a solution that touches numerous parts of the value chain—engineering, procurement, manufacturing, supply chain, sales, service and more. Because success for such an implementation depends on delivering both business value and compliance across a broad set of stakeholders, it can be a great challenge for many organizations.
This week LNS Research had the opportunity to be briefed by two solution providers that are taking a new approach to the Quality Management space. In both cases, these companies have put Risk at the center of their solutions. One described their solution as Quality Risk Management (as a subset of Operational Risk Management) and the other as Operational GRC (Governance, Risk, and Compliance).
In a recent blog post on Enterprise Quality Management Software, we examined how measuring and minimizing the Cost of Quality (CoQ) was one of the many benefits of EQMS. In that post we also took a deep dive into how to measure and gain business value from the Cost of Quality metric. However, we neglected to give a formal Cost of Quality Definition.
In our last post we examined the challenges many companies face with Statistical Process Control and SPC Software. We showed, through example, how many companies struggle to gain buy-in for SPC among operators and middle management. We also showed how many of these companies fail to support initiatives at the enterprise level with the necessary leadership, process, and technology business capabilities