Does nothing wrong mean anything right?

A couple of interesting papers recently crossed my desktop that I'd like you to reflect upon.

The first was a 1994 paper by Dr. Juran (one of America's top quality gurus) titled "Quality Problems, Remedies and Nostrums" that focused on the Zero Defect (ZD) movement. In this paper, he states that "the results of the ZD movement are not very impressive" first, because failures greatly exceed successes and second, published results appeared more qualitative than quantitative as if their main purpose was to impress their customers.

The second document is an ISO related discussion on the difference between "corrective action" and "preventive action" to eliminate the causes of non-conformance. The paper explains that corrective action is about stability, and preventive action is about capability. For QFD practitioners, this explanation also demonstrates the difference between a problem solving approach using DMAIC, and a design approach using DMADV to understand true customer needs and assure satisfaction.

Neither paper answers this critical QFD question, however: "Does nothing wrong mean anything is right?" 

We ask this question at the start of every QFD Green Belt^® course in order to provoke students to go beyond fixing and preventing negative quality, and to search for positive quality.

In other words, customers don't buy a product or service because the product is problem-free; they buy a product because it helps them, the customer, become problem-free. This means you must understand what outcomes the customer truly wants in their life and work.

 

Unfortunately customers are not always good at explaining themselves. After all, few suppliers ever bother to ask, so customers are not practiced at describing their problems or unfulfilled opportunities.

This is why VOC tools such as the gemba visits, Customer Process model, and Customer Voice table are essential to good QFD. These tools help customers use words and actions to show us what "success" means to them and why they are failing. Through these tools, customers can explain their biggest headaches and missed opportunities. 

With this knowledge, a QFD team can then identify solutions that are capable of delighting the customer better than the competitors. This is how QFD differs from other quality initiatives.

If you find this topic helpful, you might be also interested in reading "Finding Customer Delights Using QFD" in the 2006 Symposium Transactions. Better yet, plan to join us this fall in the 24th Symposium on QFD in St. Augustine, Florida, to learn more about these modern tools.

QFD and Six Sigma DMAIC

from the QFDI newsletter, January 2012

Efforts to standardize and strengthen product and process improvements are greatly welcomed in modern organizations, and nothing does it better than the DMAIC (define-measure-analyze-improve-control) approach in six sigma. This 21st version of Shewhart’s and Deming’s PDSA (plan-do-study-act) technique is the backbone of ongoing quality improvements in today’s leading companies.

The purpose of quality improvement is to eliminate the costs and losses associated with defects and deviations from targets. The process starts with defining those targets and how to measure them, and then determining what the current level of performance is. Next is to identifying the causes of why current performance fails to meet those targets.

Causal factors can be analyzed as those related to the 4 Ms, or those attributable to workers (men), equipment (machine), processes (method), or design (materials). Advanced thinkers may also include method of measurement (ex. poor gauging or measurement techniques), money (lack of funds to make desired improvements), and management (lack of top level support to invest in and support a quality culture). Let us know if you have identified other “M”s, please.

Once causal factors have been identified, data analysis helps focus on those with the strongest contribution to improving performance. Since DMAIC attends to current products and processes, data can be collected to statistically calculate the correlation between a causal factor and the undesirable effects of the defect.

Improvements to the undesirable effect are made by improving these highly correlated causal factors, and training workers, upgrades or better maintenance of equipment, new processes, or better design are investigated and tested. In addition to efficacy of these improvements, other feasibility constraints such as cost to implement, time to implement, etc. are considered in deciding what and when to implement.

Once the improvement is in place, standardization of the improvement is needed to prevent falling back to old ways. Thus, ongoing data collection helps control any deviations to the new process.

What Role Can QFD Play in DMAIC?

QFD has typically focused on new product development; the large time-consuming “houses” of classical QFD are considered overkill for addressing concerns with local problems associated with production or service delivery failures. Rather, QFD is an approach for identifying customer needs far upstream from production, even prior to design phases in order to define quality from a customer or user perspective and assure it is designed into the new product and quality assured during its build and delivery.