Everyone knows the story of the Challenger Space Shuttle tragedy. On January 28 1986, the space shuttle exploded 73 seconds after lift-off. This sadly led to the deaths of seven astronauts which rippled across the world.

The Rogers Commission was set up to investigate the root cause of the explosion. The investigation findings went much deeper than initially suggested. One issue led to another. Instead of being a freak accident, it became an accident that could and should have been prevented.

This is a rare and extreme example to use for highlighting the importance of Root Cause Analysis but the principles are the same and are transferable to the pharmaceutical industry.

Finding the root cause can be an incredibly difficult and time consuming job but there are tools out there to help simplify the process, while still maximising efficiency and effectiveness. After all, we’ve all been there: Analysis failure; rack your brains remembering the procedure you did; blame human error.

However, regulatory bodies and businesses are indisputably clamping down on non-compliances. From a business perspective, the more non-compliances there are, the more analysis is needed. This in turn increases the time taken which lowers efficiencies and ultimately, profits. But most importantly, non-compliance may lead to harming patients and delaying a patient’s access to vital medicines that they may need.

Regulators are increasingly asking for evidence of Root Cause Analysis being applied. They are also requesting evidence that your teams’ are trained and confident in this procedure. Simply stating human/mechanical error, with no evidence to show further investigation, will not be accepted.

The benefit of applying Root Cause Analysis is that it should stop the repetition of mistakes. We’re all human, we all make mistakes, but, as Donald Rumsfeld said: ”try to make original mistakes, rather than needlessly repeating theirs.”

So, going back to basics, what exactly is Root Cause Analysis? Root Cause Analysis has been defined as an in-depth process or technique for identifying the most basic factor(s) underlying a variation in performance.

The Six Sigma approach to process improvement suggests that when an error occurs, it can be explained within one or more of the following “Four Ps”. These are: policies, procedures, people and plant/technology.

When determining the real root cause of any issue, a useful tool is to follow the DMAIC procedure:

  1. Define the problem.
  2. Measure by collecting and analysing all the facts and data.
  3. Analyse the data to develop theories and possible causes.
  4. Improve the issue by defining and implementing a CAPA plan.
  5. Control the process by monitoring and assessing the results for appropriateness and effectiveness.

There are hundreds of forms of analysis that can be used to identify a root cause, from brainstorming to tree diagrams, cause and effect diagrams to process mapping. For the remainder of this article, we will focus on two analysis techniques: the Five Whys and Pareto Analysis.

The Five Whys is a simple tool that challenges easy assumptions. The idea is that you start with the problem and ask why five times. After each question it should lead to deeper issues until you reach the root of a problem. It does have its disadvantages in that it relies upon asking the right “why” questions. It also lacks repeatability. When carried out by numerous people, the root cause often differs and may lead to many different root causes being identified. Going back to the Challenger Space Shuttle analogy, an example of the Five Whys could be:

Problem – Challenger Space Shuttle explosion:

  • Why? External fuel tank explosion.
  • Why? Jet blast into tank.
  • Why? Propellant leak.
  • Why? Primary O-ring blown.
  • Why? O-ring unsuitable at low temperatures.

By the end of the analysis you really dig deep into the issue and find out that the real problem was in fact not what you initially found. Had the tragedy just been blamed on the propellant leak, NASA may have never known and probably never tested any space shuttles in the right conditions, potentially leading to more lives lost on future missions.

Following the application of the Five Whys, there are often multiple findings identified. Further analysis can then be applied to help understand which findings are of the most importance. Pareto Analysis is a statistical technique used in decision-making for the selection of a limited number of tasks that produce significant overall effects.

The Pareto Principle (also known as the 80/20 rule) suggests that by doing 20% of the work you can generate 80% of the benefit of doing the entire job. For example: if all of the clothes you own need washing, a laundry service may cost you £100. However, applying the 80/20 rule suggests that people wear 20% of their clothes 80% of the time. Meaning you could save £80 and still yield 80% of the benefit.

There are many ways to apply this in a commercial setting, for example, it is suggested that 80% of sales come from 20% of staff and 80% of problems or profits come from 20% of customers.

One of the key benefits of applying Pareto Analysis is that it concentrates efforts on areas that have the biggest impact on a business. However, it doesn’t take into account the severity and relies upon the problem receiving the correct classification to begin with. Ensuring 80% of analysis is complete for all of your customers is great, but if your highest paying client did not receive their completed CofA by the deadline, it could mean you lose their custom.

Looking at the bigger picture, with any form of analysis, there are always common errors. Often you look for a single mistake/issue to pin point the blame, whereas often there are many different influencing factors which contribute to an issue. All of these are equally as important to capture. When using analysis tools, also remember the end result/s also should not be symptomatic of the problem.

If we’re being realistic, we can’t apply this to every situation, it would take too much time, energy and resource and not necessarily yield substantial benefits.

Examples of when to apply Root Cause Analysis include:

  • When there are significant or consequential events.
  • Repetitive human errors or equipment failures occurring during a specific process.
  • If performance is generally trending below a desired standard.

There are many reasons why identifying a root cause is hugely important to a business. For example, it can prevent problems from recurring and most importantly, reduce possible injury to patients.

Ultimately, applying Root Cause Analysis increases productivity and competitiveness and reduces costs. For instance, reducing the amount of Out Of Specifications (OOSs) and rework increases productivity, leading to clients receiving their results quicker, which increases a company’s competitive service offering. This in in turn, reduces all kinds of costs and saves money, from staffing costs, to ordering more standards and reagents etc. The number of billable hours and analysis undertaken increases, which enables more samples to go through the system. This results in an increase in turnover and profits. At the forefront of everything, it promotes GMP compliance both in the work place, to clients and to regulatory authorities.

Root Cause Analysis is about looking beyond the obvious. Often the root cause of a problem is not the initial reaction or response. It is not just restating the finding. In fact, the initial response is often the symptom and not the root cause of the problem. We frequently find that the root cause appears to be a much bigger issue than the issue first raised, such as, a process failure, poorly written SOPs or lack of training and so on…

Root Cause Analysis should focus on systems and processes and not on individuals.