Decision making is nothing new to any of us. We make thousands of decisions a day that have little to huge effects on personal, professional, and social outcomes. What time you wake in the morning is usually a decision that we have based upon the amount of time we need to safely and effectively do our morning routines and make it to work or school on time. For example, some may decide to get up an hour early to go for a run to maintain our cardiovascular health, or do we need that extra hour of sleep to help heal a nagging cold.
This example seems very mundane in the bigger picture of some of the decisions we make. Most of us would agree that such a decision should and would be an easy decision. If I am still sick and tired I will sleep in, if not I am going for my morning jog to be healthy.
Now if we break down the decision process to a very finite process of why we should run versus sleep or sleep versus run, the process becomes more complex.
We ask five whys or each case
To decide to run:
- Why? My last physical my blood pressure was elevated,
- Why? The scale shows I am slightly overweight,
- Why? I may be susceptible to diabetes, high blood pressure, and heart conditions based upon family history.
- Why? This is the only day of the week that the weather is nice to run,
- Why? It makes me feel better physically and mentally.
To Sleep in:
- Why? Gives my body the extra time to heal from the cold,
- Why? My head is clear for work.
- Why? I took cold medicine last night that requires 8 hours of sleep prior to operating machinery.
- Why? I have to drive work.
- Why? My job is flying helicopters.
- Why? People’s lives depend on the decisions I make and I must have plenty of rest and a clear mind.
In this scenario, we can all agree that the clear decision to sleep is the proper decision by taking into account all the information I offered for the reader to analyze. If the person decided to run and then go to work and an accident occurred, there would be an investigation why an accident occurred. Many contributing factors could be a result of the accident. Weather, maintenance, and so forth, but what was the real reason and the root of why the accident occurred. There could be many root causes and we can identify two in our previous scenario 1. lack of sleep and 2. side effects of the medication the pilot was taking. There is much more to the process of identifying the root cause of an issue. In the next few pages, I want to introduce to the reader a concept of how as a manager or leader we can take our decision-making process to a higher level and make informed decisions. Be able to reverse engineer why something went bad or something went good with our process.
Effectiveness in managing our business decision making will ultimately determine the success of a company. While this is an issue for companies of all sizes, its scope is broad. It’s not restricted to a certain level of the hierarchy; rather employees at all levels across all departments make decisions, depending upon the roles they play, and situations they get face-to-face with. The process of decision making through total quality management and root cause analysis (RCA) provides the tools at any level to make informed decisions. RCA was developed to identify why an event occurred. When you determine why an event or sequence occurred you can develop preventable measures. (Rooney, 2004) Many believe that RCA is reactive, but in fact, if used correctly it can be a proactive decision-making process.
The history of Root Cause Analysis (RCA) can be traced back to quality management engineering. The quality revolution, really the root cause revolution, began in Japan over a hundred years ago. A Japanese manager in the 1930s wanted to have a better understanding of the causes of quality problems, he explained: all problems arise from their root causes. Find the root causes, resolve them permanently, and your problem is solved. Sakichi Toyoda is credited with the original RCA concept. CITATION Fat18 \l 1033 (Fatima, 2018) The “Japanese Thomas Edison,” and the founder of Toyota. Toyoda called his method “The Five Whys.” If a question is asked at least WHY five times or more the root cause(s) of a problem is found. CITATION Ser09 \l 1033 (Serrat, 2009) My simple example in the introduction to this paper alludes to this process.
In post-war Japan, Japanese products were perceived as cheap and undesirable. There it may have stayed, if not for the consulting work of W. Edwards Deming. Deming had studied what Toyoda had started in the 1930s with RCA. He used Toyoda’s theories as a basis for creating his famous Fourteen Points for Management. These points were developed to bring about total quality management for the industrial manager. To his disappointment, US companies were not interested in his TQM theories. CITATION Eiznd \l 1033 (Nishibori, nd) Deming had gone to Japan to perform a census for the US Census Bureau. He saw what the Japanese were doing for quality control and realized it was non-existent. He offered his 14 points for management to the Japanese and trained their companies on his concepts. When Japan began to trounce the rest of the industrialized world in the 1970s, US managers finally saw the light and asked Deming for help. CITATION BPInd \l 1033 (BPIR, nd) In 1986, engineer Bill Smith began to develop a methodology to standardize defect measurement and improvements in manufacturing for Motorola. Six Sigma uses specific methods, including statistical information, to outline an RCA. It also puts its workers in a specific infrastructure based on their qualifications. CITATION Pie11 \l 1033 (Pierce, 2011) The high standard of risk management achieved with Six Sigma is measured by the low number of defective products produced, which is about 99.99966% or a mere 3.4 errors or defective products per million. CITATION Pie11 \l 1033 (Pierce, 2011) Due to its high success rate, the Six Sigma quality standards were soon adopted by other manufacturing industry giants, such as General Electric.
Although first used in manufacturing industries, Six Sigma is now applied in service industries as well. CITATION BPInd \l 1033 (BPIR, nd) Decision making and Root Cause Analysis is huge in the industry I work in. As a pilot in aviation development, testing, and acquisition from the cockpit to the production floor my job entails decision making through risk mitigation. We utilize the RCA as a standard tool to identify possible risk, quality control, error reduction, and risk management to minimize accidents and meet FAA requirements. In 1975, FAA established the Aviation Safety Reporting System (ASRS) to conduct its safety management. Following its establishment, the FAA has reduced death rates from airline accidents by 80 percent. Over the next few years the FAA did much research into Aeronautical Decision Making (ADM) training. The airline industry recognized the many accidents caused by human factors, it established training programs in accordance with ADM. Crew resource management (CRM) training for flight crews is based on crews using every resource available to them for crew cooperation and improve decision-making. The final output is about making good decisions.
The proper decision-making process in aviation can be the difference between life and death. From the pilot standpoint, the decision-making process begins with the decision to fly. The risk matrix and standard operating procedures are developed to help the pilot in their decision-making process. These matrix and SOP’s are the result of accidents and occurrences that resulted in loss/damage to aircraft or loss/injury to personnel. Utilizing RCA to answer why these incidents occurred and how we can mitigate this risk. These procedures in aviation also are found in aviation maintenance and aviation production. A good example of aviation industry change is mandatory duty and rest time for pilots and maintainers.
Prior to the FAA implementing regulations on duty and rest time for pilots and maintainers many accidents were occurring in flight and due to poor maintenance on the aircraft. In June 2008, the FAA sponsored the “Fatigue Symposium: Partnerships for Solutions” to bring the aviation community together to discuss aviation fatigue management issues. The NTSB, and many specialists on sleep and human performance joined the discussion. (Johnson, 2010) The Symposium provided attendees with the most current information on fatigue physiology, management, and mitigation alternatives, including fatigue risk management systems (FRMS), perspectives from aviation industry experts and scientists on fatigue management, and information on the latest fatigue mitigation initiatives and best practices. Many of the findings presented were developed from accidents from 70 years’ worth of airline data. Root cause analysis showed there were strong contributing factors of fatigue in over 20% reported cases. (NTSB, nd) From these findings, the NTSB issued more than 200 safety recommendations in which the FAA developed a duty and rest time regulation.
Every problem has multiple underlining causes. In most situations’ problems do not just happen but can be traced to defined reasoning. If the underlining cause cannot be identified, then one is only scratching the surface of the issue and the problem will continue to exist. Identifying and eliminating the root causes of problems is quintessential to your quality processes. (Andersen and Fagerhaug 2000) Understanding why an event occurred is the key to developing effective recommendations.
The RCA is a four-step process involving the following:
- Data collection.
- Causal factor charting.
- Root cause identification.
- Recommendation generation and implementation. (Rooney, 2004)
Much time is spent gathering information, and data to ensure that the event is completely understood. Incomplete information and lack of attention to detail can lead to a misdiagnosis of the true root cause. The big picture representation that establishes a visual mapping of details is called causal factor charting. Causal factor charting starts as the investigation begins. This is a fluid document with many changes along the way. Your final draft will look nothing like the beginning chart. There are many different charts that may be used for causal factor charting, but the most prolific is a skeleton chart. Skeleton charts that maybe used are the cause-and-effect diagram (CED), the interrelationship diagram (ID), and the current reality tree (CRT) CITATION Dog05 \l 1033 (Dogget, 2005).
For the purpose of this paper I will discuss the cause-and-effect diagram (CED). Designed by professor Kaoru Ishikawa in 1943 to separate causes of a problem while organizing the causal relationships. Ishikawa developed his “fishbone diagram” as it became to be known to explain to Kawasaki Steel Works engineers how to solve quality-related problems in products caused by statistical variation. Ishikawa realized it could be used for solving other types of problems involving continuous process improvement. Ishikawa (1982)
Constructing a CED
Step 1: Begins with stating the problem or the occurrence that has caused the investigation.
Step 2: In the example below, you can see you want to write the issue on the right side and draw an arrow from the left to the right-side
Step 3: Draw lines of the left to right arrow and these become the main factors or the major branches. These branches will become the primary causal factors of the issue and resemble the rib bones of a fish,
Step 4: For each of these major branches, you will draw out detailed causal factors that is causing each major branch to exist. These small lines are taking shape as the real issues of your problem.
Step 5: Take time completing your skeleton diagrams to develop and classify root cause categories, one may assume you have enough knowledge to be able to isolate and identify probable root causes, but the identified causes may not be specific or reasonable enough to continue to step 4 of the process of recommendation generation and implementation. More time can be taken here to truly identify the root cause. By taking the fish diagram and asking the five whys from each branch and the identity of the root cause becomes aware through further mapping of the causal effects.
Step four is to generate multiple solutions and recommendations.to prevent the reoccurrence of causal factors. Many hours and details can be put into identifying the causal factors. Presenting these recommendations can be a through root cause summary table. These tables can capture all the information and recommendations in one document. You will develop a summary table that has three columns. These columns will present a consolidated data preview of the entire RCA process. The first column identifies each causal factor and background information for individuals to understand the need to address this casual factor. The second column presents the causal factors mapping through the root cause analysis process. The third column is utilized for recommendations for the best course of action and the way forward in regards to the causal factor (Dogget, 2005) The maps will help categorize each root cause and allow management to see multiple courses of actions to eliminate the problem in the future.
In today’s industry, achieving significant decision-making improvements in all activities from operations, human resource management, and logistics management with a major focus on safety and quality control. Through disciplined improvement techniques such as lean six sigma and training of leadership in quality management, businesses can reach cost savings and expense reductions. By embracing an organizational culture of continuous process improvement, business is developing not only financial capital that will be able to re-invest back into future technologies but also human capital. The new personnel that develops a zero-deficiency mindset, that answers the hard questions of why something happened now. These are the future leaders of your company and will continue the process improvement throughout their careers. This paper has given a brief description of the decision-making process and utilizing root cause analysis. The history and application are far more in-depth than what this paper has touched on. I continue to improve my own decision-making skills through my own readings, personal experiences, and formal training. This makes me a better leader, pilot, and overall manager.
BIBLIOGRAPHY BPIR. (nd). Retrieved from Business Performance Improvement Resource: https://www.bpir.com/total-quality-management-history-of-tqm-and-business-excellence-bpir.com.html
Dogget, M. (2005). Root Cause Analysis: A Framework for Tool Selection. Humboldt State University: ASQ.
FAA. (nd). Aeronautical Decision Making . Retrieved from FAA.gov: https://www.faa.gov/regulations_policies/handbooks_manuals/aviation/phak/media/04_phak_ch2.pdf
Fatima, A. (2018, ND). A Brief History of Root Cause Analysis. Retrieved from Bright Hub PM: https://www.brighthubpm.com/risk-management/123244-how-has-the-root-cause-analysis-evolved-since-inception/
Ishikawa, K. (1982). Guide to Quality Control. Tokyo: Asian Productivity Organization.
Johnson, J. (2010, October). Short History of Flight-Time/Duty Time. Retrieved from ALPA: http://www3.alpa.org/portals/alpa/fastread/2011/docs/HistoryofFTDT_ALPOct2010.pdf
Nishibori, E. (nd). Deming Influence on Post-war Japanese Quality Development. Retrieved from QFD Institute.
NTSB. (nd). Reduce Fatigue Related Accidents. Retrieved from National Transportation Safety Board.: https://www.ntsb.gov/safety/mwl/pages/mwl1-2016.aspx
Pierce, F. (2011, September 27). Motorola’s Six Sigma Journey: In pursuit of perfection. Retrieved from Supply Chain Digital: https://www.supplychaindigital.com/procurement/motorolas-six-sigma-journey-pursuit-perfection
Rooney, J. H. (2004, Jul 1). Root Cause Analysis for Beginners. Retrieved from ASQ: http://asq.org/quality-progress/2004/07/quality-tools/root-cause-analysis-for-beginners.html
Serrat, O. (2009). The 5 Why’s Technique. Cornel University Key Workplace Documents, 1-3. Retrieved from http://digitalcommons.ilr.cornell.edu/intl?utm_source=digitalcommons.ilr.cornell.edu%2Fintl%2F198&utm_medium=PDF&utm_campaign=PDFCoverPages
Cite this essay
Effective Decision Making. (2020, Sep 11). Retrieved from https://studymoose.com/effective-decision-making-essay