What is Root-Cause Analysis? Working, Templates, and Examples

Root-cause analysis is the systematic process of investigating an issue using proven techniques to gather data around the problem, identifying more than one cause, prioritizing them, and coming up with a potential resolution. It is relevant to nearly every industry, from IT and software development to manufacturing and consumer goods. This article uses examples to explain the steps and tools involved in root-cause analysis.Â

What Is Root-Cause Analysis?
How Does Root-Cause Analysis Work?
Root-Cause Analysis Templates
Examples of Root-Cause Analysis

What Is Root-Cause Analysis?

Root-cause analysis is defined as the systematic process of investigating an issue using proven techniques to gather data around the problem, identifying more than one cause, prioritizing them, and coming up with potential solutions. It is relevant to nearly every industry, from IT and software development to manufacturing and consumer goods.Â

A root cause is an element that contributes to a nonconformance and needs to be permanently removed via process improvement. The core issue, or root cause, is what started the complete chain of events that led to the problem in the first place. It is also the most fundamental reason. Root cause analysis (RCA) is a broad word that refers to various methodologies, tools, and procedures used to identify the root causes of issues, usually in sectors like software development, DevOps, and infrastructure management.

It aims to locate the fundamental source of an issue by employing a specified set of processes and accompanying tools. This way, you can:

Identify the circumstances.
Analyze the cause of the event.
Identify the steps you can take to make it less likely to occur again.

System and event interdependence is a presumption of root cause analysis. A particular action sets off a chain of subsequent actions in related areas. Going back through these acts, one can find the problem’s origin and how it developed into the symptom you’re currently experiencing.

RCA is a reactive procedure that is carried out after the occurrence. However, after a root cause analysis has been carried out, it assumes the form of a proactive mechanism since it may identify issues before they arise.

There is a good possibility the failure will occur again if you address a symptom of the issue but leave the underlying reason unaddressed.

Consider the scenario where you change the damaged belt but leave the misaligned component in place, causing the belt to overheat and break. In such a situation, you may stake your salary on the belt, failing once more. To identify the issue that, when fixed, will render all other defects obsolete, RCA attempts to trace the causal chain from one problem to the next. This applies to physical systems as well as IT infrastructure.

Depending on the issue you’re seeking to resolve, numerous root cause analysis techniques are available. They are as follows:

Safety-based RCA: It is an approach that combines accident analysis with the fields of workplace safety and health. This kind of root cause analysis is used to identify the reasons behind workplace accidents, such as why a worker mistakenly dropped a component from a height or why someone cut themself.

Production-based RCA: Manufacturers use production-based RCA to guarantee quality control. You might utilize this to determine the cause of the distorted injection-molded plastic items leaving the production line.

Process-based RCA: In business and manufacturing, process-based RCA is used to identify the problem with a process or a system. One might use this in accounting to find out why suppliers aren’t being paid on time.

Failure-based RCA: It is employed in engineering and maintenance to identify the primary factor behind equipment failure.

Systems-based RCA: It began as a synthesis of a few of the methods for root cause analysis described above. This methodology combines two or more RCA techniques. It has many different uses and applications.

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How Does Root-Cause Analysis Work?

The following are the fundamental steps in the root cause analysis process:

Step 1: Identify the problem

A frequent adage in the problem-solving community is â€œA problem properly described is a problem half solved”. A precise problem characterization can aid in focusing and advancing the diagnosis. But even before the problem is defined, it is crucial to consider whether it is significant enough to work on in comparison to other issues and whether its scope is sufficiently constrained to allow for analysis with a high signal-to-noise ratio.Â Â

Due to a broad focus that encompasses several similar problems having distinct causes, a poor signal-to-noise ratio makes it challenging to distinguish between cause-and-effect linkages. Therefore, a filter that separates issues that need to be fixed from those that one can only track should be present before the corrective action. Nevertheless, not all problems found in an organization will be subject to this screening.Â

Therefore, it is vital to analyze the organization’s other issues before tackling any problem and decide which ones call for reallocating resources to address the situation at hand. This necessitates examining the problem’s relative frequency, the cost effect, associated hazards, and opportunity costs (how well does it fit with the future strategic direction, are there enough resources available â€“ like DevOps engineers â€“ to work on it, and are there any other uses for those resources?).

Step 2: Understand the procedure

Evaluating the procedures that may have failed is a crucial step many businesses skip in their problem identification. Instead, a hasty or intuitive conclusion is formed regarding where the issue was probably first encountered.Â

Due to this, many other possible explanations are never even thought about. Stepping back and considering the overall issue before focusing on potential reasons is the key to understanding the process. This is especially helpful if the problem was formerly believed to have been resolved but has now surfaced again. One must first develop a set of parameters for the diagnostic to begin comprehending the procedure.

Step 3: Determine potential causes

Here is where the core of your analysis comes into play. Reconstructing a chronology of events can help you in this stage to identify the specific events that contributed to the problem and any additional problems that coexist with it. You must use this technique if you want to identify particular causative elements.

There are three ways to find potential causes: (1) regard each step in the flowchart as a potential cause; (2) use a logic tree to find potential causes at every system level; and (3) generate a list of potential causes using a cause-and-effect diagram.

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Step 4: Collect the data

The goal of data collecting is to determine whether there are any correlations between the two variables X and Y. The parameter Y, or the result of a procedure, is what the problem statement refers to as. There are often several X factors, and it is thought that X influences Y.Â

The method of gathering data intends to assist in sorting through the factors and determining which one has contributed to the problem. This frequently entails determining the entity that produced the issue before deciding the state or condition of that entity. If the problem is widespread, data can be stratified in various ways to search for patterns that may increase the likelihood that a specific element is or is not the cause.

Step 5: Perform data analysis

The research method is centered on data analysis. Data analysis aims to find causative variables and the core causes of those causal factors. The study will determine one or more root causes for each causative factor. As a result, if a causative element is not found throughout this procedure, the investigators will later overlook several fundamental causes. Data analysis’s primary goals are data organization and relevance assessment, as well as developing a model of the problem’s origin.

Step 6: Develop recommendations

The development of recommendations follows the conclusion of the data analysis and the discovery of the root causes (if carried out as part of a root cause analysis). Putting a proposal into practice should eliminate the causal element and underlying fundamental reasons for the loss occurrence. Implementing suggestions should thus prevent and obstruct the series of actions that resulted in the loss occurrence.Â

As a consequence, it ought to stop the incident’s recurrence and its underlying causes. Only recommendations that are put into practice and afterward shown to be successful may benefit an organization. Therefore, advice must be applicable, doable, and attainable.

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Root-Cause Analysis Templates

There are several possible templates to support root cause analysis (RCA). Here are only a few examples of them:

1. Ishikawa diagram

The Ishikawa diagram, commonly referred to as a fish-bone diagram or a cause-and-effect diagram, was developed by Kaoru Ishikawa to illustrate probable causes that could result in an effect (Ishikawa, 1991). When the likely cause of a failure is uncertain, it is often helpful to stimulate brainstorming.Â

The six Msâ€”man, measures, material, milieu, methods, and machinesâ€”are essential considerations in an Ishikawa diagram. These variables may and ought to be changed to match a particular procedure. For instance, one could alter the factors if the fundamental cause has been narrowed down to a specific region. The impacted process may still be influenced by other elements, such as measurement or material; as a result, these aspects may still be pertinent to the underlying cause.

2. Pareto chart

The 80/20 rule, commonly referred to as the Pareto principle, is the foundation of the Pareto chart. The 80/20 rule states that 20 percent of the issues cause 80 percent of the expenses. The Pareto chart is used to pinpoint the problems where improvement efforts will have the most significant impact.

You should note that the Pareto principle should be viewed as a suggestion rather than a law; for instance, you should handle uncommon safety problems before more prevalent ones with lesser severity. Here are the considerations to remember while using this root cause analysis tool:

Finding the 20 percent of issues that will improve by 80 percent will aid in determining the best order of priority.
Utilizing a Pareto chart requires engineering judgment and common sense.
It is possible to utilize a Pareto chart for failure kinds, failure locations, failure costs, or other categories as necessary.
Issue prioritization is the primary application of this tool.

3. 5 WHYs

The 5 Whys approach is used to explore further until the actual root cause of an event is found. When an event has more than one reason, the process might be divided, or the core cause can be sought by asking why repeatedly. The Whys can be organized into boxes similar to a flowchart or fault tree, although it’s unnecessary. When using the five whys technique, the proximate cause should be followed by the ultimate cause. Here are the considerations to remember while using this root cause analysis tool:

You can find the real root reason for an occurrence by asking why five times.
This technique must be used in conjunction with more accurate, quantitative approaches.
One may use it to identify failure as well as incidence.

4. Fault Tree Analysis (FTA)

Fault tree analysis (FTA) investigates the root causes of system failures. Risks are ranked according to importance in fault tree analysis, allowing the most significant threats to be fixed first. It takes a top-down strategy to pinpoint the component level failures (basic event) that lead to the system level failure (top event), combining them using Boolean logic.Â Â

Fault tree analysis, when used in conjunction with other Lean Six Sigma methods, aids the team in concentrating on the most crucial input variables to the most critical output variables in a particular process. FTA is a top-down method for determining the component-level failures that lead to system-level problems.

5. Failure mode and effects analysis (FMEA)

FMEA is a proactive root cause analysis method that guards against a probable system or equipment failure. An FMEA diagram shows:

Failure scenarios, effects, and causes
The current safeguards against every kind of failure
Ratings for severity (S), occurrence (O), and detection (D) enable you to determine the risk priority number (RPN) and the next course of action.

FMEA combines efforts in quality control, safety engineering, and reliability engineering. It uses data analysis from the past to try to forecast flaws and failures in the future. Using FMEA requires a varied cross-functional team outside DevOps and a Scrum Master. The scope of the analysis must be well defined and communicated to your team members. Each subsystem, design, and procedure are carefully examined.Â

Each system’s use, needs, and functionalities are called into question. There is brainstorming of potential failure modes. Analyzing prior failures of processes and products that are comparable may also be done. Each of the detected failure modes is evaluated, and its Risk Priority Number (RPN) is determined by taking into account the potential repercussions and interruptions it may create.

6. Scatter diagram

The analysis of potential associations between paired data, such as the temperature used to produce steel and the steel’s resultant hardness, is done using scatter plots, also known as scatter diagrams. Analysts can show an absence of a link, a high positive correlation, a weak positive correlation, or both using a scatter plot. A correlation does not always imply a relationship between the two elements; they might be unrelated to one another and connected to a third component.

7. Hazard and operability analysis (HAZOP)

The Hazard and Operability Analysis (HAZOP) approach is a systematic system analysis and risk management tool.Â

HAZOP is a technique frequently used to detect possible risks in a system and operability issues that could result in nonconforming goods. HAZOP is based on a hypothesis that deviations from design or operating goals lead to risk occurrences. The use of â€œguide wordsâ€ collections as a systematic list of divergence views makes it easier to spot these deviations. The HAZOP technique has a unique approach that encourages team members’ creative thinking while looking at potential deviations.

8. The Challenger Interview

The Challenger Interview tool for root cause analysis emphasizes asking why repeatedly, much like the 5 Whys. It’s not about trying to figure out why anything happened, though. The question is, â€œWhy does it even matter? The Challenger Interview educates you about people’s underlying motivations and ambitions to identify the actual challenge, opportunity, or problem that must be solved.

9. Role-playing

Taking on the role of another person is the goal of role-playing. Understanding the world from another person’s point of view can provide profound insights into the underlying causes of a problem. A potential user or someone with an issue you wish to fix maybe this person. This approach is particularly well-liked in the progressive fields of technology and consumer products & goods (CPG).

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Examples of Root-Cause Analysis

Let us now explore a few examples of scenarios where root-cause analysis may be needed:

1. Analyzing the subtleties of human error

Let us say a supermarket business orders 1,000 packages of apples when they only need 100. The order was submitted erroneously, and the supplier would not accept it back. The retailer must aggressively discount and market to sell apples at a loss.Â

Initially, the problem is attributed to a human mistake. A root cause analysis technique may be able to identify the hidden human error in ordering systems. For example, there could be no validation or notice for typically big orders. Furthermore, the system’s typefaces may be unusually tiny, making it difficult for some staff to read effectively.

2. Analyzing the causes behind website downtime

Let us imagine a media company’s website is available 97% of the time compared to its competitors. Every time the website goes down, a reason is given, such as a failed change, a person making a mistake, data problems, or service failures. The organization conducts a gap analysis to identify the underlying reasons for these failures.Â

The analysis reveals that the website’s infrastructure, platform, development procedures, and code have problems resulting in an unstable environment. For instance, the company hired a company with a high turnover rate to handle its development and web application security management outsourcing.Â

Each developer only spends an average of two weeks working on the code since the company often moves its personnel around. The platform’s developers’ lack of familiarity leads to more stinky code and issues. In such scenarios, root cause analysis helps prioritize which problems to fix first and where to invest resources.

3. Analyzing the risks jeopardizing the safety of information

Imagine following an employee’s click on an email link; a government agency encounters an information security problem. Since the company had educated the employee not to click on links in external emails, the direct cause has been attributed to human error. However, the email was not blocked by spam filters, and the employee’s computer wasn’t patched with the most recent updates, which allowed an exploit of an operating system vulnerability. As a result, root cause analysis can unearth hidden security risks.

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TakeawayÂ

The root-cause analysis process is an essential part of any DevOps project. It enables team members to come together after a project and investigate any issues â€“ and achievements â€“ they have encountered. DevOps teams can apply their learnings to future endeavors by identifying critical lessons from RCA. The most significant benefit of root-cause analysis is that it can be used in technical and non-technical scenarios alike, providing enterprises with invaluable information.

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