In problem-solving methodologies, identifying potential causes is a crucial step between process mapping and data collection and analysis. It involves the best available process knowledge, as well as creativity. Creativity and team management tools, more often employed for solution finding than for root cause finding, can generate deep understanding of the process mechanics and help the team prepare for the distilling and data-based validation of the essential few root causes of a problem.
Problem-solving teams can increase their chances of success by using a consistent methodology for identifying a problem’s origins. Such a methodology must be based on the very nature of root cause analysis. This form of analysis:
- Is a process that needs to be understood from the bigger picture.
- Is a team exercise that focuses on people and on meeting facilitation.
- Uses brainstorming to combine best expert knowledge with out-of-the-box thinking.
- Delivers measurable factors and a data-collection plan.
- Uses data to derive potential causes.
In the light of one specific example, it is possible to see how creativity and team management tools can be used to look deeper into the first four elements of root cause analysis. Using data to distill significant causes, both from a statistical and then from a practical point of view, is typically covered in Lean Six Sigma training classes. The example considered here is a delivery process where lead time had recently degraded with respect to customer expectations.
Working Through the Process
After carefully describing their problem, the team started the analysis by mapping out the delivery process. Then they brainstormed for potential causes for variation in lead time. To validate those causes, they collected and analyzed data. At first, only a small share of the total variation could be explained with these factors. The team then further elaborated the process map for the steps estimated most critical and revisited the cause-and-effect analysis to collect data for more potential factors by using the 5 Why’s analysis technique to drill down further. This process is shown in Figure 1.
Preparing the Team
To understand the observed variation in delivery time, the team mapped out the delivery process in greater detail. The team interviewed customers to determine their requirements and the rationale behind those requirements. They also analyzed how the process interfaces with suppliers; for several team members this was the first time they perceived the “big picture” of the process they were working in. Such first victories set the team on track for the next steps.
In preparation for the brainstorming meeting to identify potential causes, the team leader carefully:
- Conveyed a high sense of urgency and made participants feel “pain and pleasure” – Competitors had taken market share in line with their lead in delivery speed. A smooth flow of the process would also free up resources and reduce overtime work. Management actively supported the initiative.
- Secured creative diversity and included process and business experts and people with different personal styles.
- Made the team curious about “creativity tools” to be used – He also checked with experienced team members to find out which tools might be best suited for the specific team.
- Removed barriers to a free flow of ideas – The facilitator ensured that rules about inter-department finger pointing was clarified offline. He also verified that stakeholders were analyzed and approached accordingly.
Brainstorming Potential Causes
Like any other brainstorming activity, identifying potential influence factors is a team-thinking process. At the beginning of the meeting, management aligned the participants behind the business criticality of the process through a short intervention. The team also agreed on a schedule and ground rules. Then they went through the process map again, printed on an sheet of paper, which served throughout the meeting.
To capture the team’s experience on what might influence delivery time, the facilitator asked participants to write their thoughts on sticky notes and paste these on a flip chart. As people saw their peers’ contributions, they eventually generated new ideas. The walking and talking involved in the brainstorming set a relaxed atmosphere. Even so, after about 20 minutes, the team reached its first dead point, the time in brainstorming sessions when the team momentarily runs out of ideas. To keep the momentum alive, the facilitator decided to use a fishbone diagram. The facilitator asked participants to come to the flipchart and cluster the different potential causes into major groups.
The facilitator steered the team around a common trap that can arise when using fishbone diagrams. The team had started by writing the defect (“Delivery is slow”) at the “head” of the fish. This would have reduced the continuous variable delivery time into pass/fail information. Doing so would also have generated repercussions when capturing potential causes. A statement such as “insufficient headcount causes slow delivery” can lead a team in a different direction than a study of the influence of allocated work hours on delivery time. Thus, the team investigated the primary metric, “delivery time.”
This clarification, as well as clustering the ideas into major groups, helped generate discussions about the relations between different potential factors, which again generated new ideas. Participants also translated their original statements on “roadblocks to success” into “tunable factors,” imagined as “steering wheels to influence delivery speed” (Figure 2).
The clustering exercise generated several major groups of factors. The team sensed some of these were underrepresented because they comprised only one or two potential factors. A quick re-brainstorming made these groups more complete. Then, the facilitator used printouts of traditional Ishikawa diagrams, the basis for fishbone diagrams, which helped them realize that price aspects had been overlooked and could now be collected through another round of posted ideas.
The facilitator decided not to have the team rearrange the posted notes into any of the traditional Ishikawa diagrams. This would helped the team consider the collected potential causes from still another angle, revealing other relations between factors, and generating new ideas. However, with the team dynamics that had unfolded, the facilitator sensed such an additional exercise as a drain to people’s creativity. Note that if this rearrangement does take place, the original state should first be documented with a camera.
The facilitator used a dead point to take a short break to prepare a creativity boosting game. These games often kick people out of their thinking box by first kicking them out of their seats. Typically, human resources departments can help in selecting creativity games. Searching the Internet also delivers many leads.
A short wrap-up of the game helped understand what defined the borders of the current thinking box: policies (written and unwritten), experiential boundaries (“At the current maturity of our logistics system, improvements must be the result of major investments”), firm convictions nobody knew the foundation of (“We will only find things we have seen in the past”) and several other limitations to creative thinking. It was the first time the team had seen the boundaries of their own thinking explicitly on a white board. They decided to creatively challenge some of these boundaries to discover new factors, such as “If we had no performance reporting to management, the delivery time might depend a lot on the affinity of the personnel for a given customer.”
Delivering Measurable Factors
The brainstorming resulted in 47 potential influence factors on delivery time. Green dots, on which the source was noted, were glued on the sticky notes of the factors where data was already available. Yellow dots stood for factors where data could be made available with some effort. Factors with no measurement system in place were marked with red dots. The result turned out to be a surprise: Data was easily available for only for a few factors. The team conducted a vote, in which each participant had five votes, to decide which of the red factors’ measurement systems were high priority.
The team then drafted a data collection plan: determine factor, (potential) data source and owner. They placed sample size determination, operational definition of the measurement and capability assessments of the underlying measurement systems as action items.
After agreeing on a follow-up procedure, the facilitator closed the meeting with a wrap up and a short feedback round among the participants. The team felt that the somewhat-fuzzy objective to identify root causes to their problem had been transformed into operational tasks. The use of creativity tools and a game had also made this work more fun. The facilitator added: Facilitating root cause identification is an art that can best be learned by exercising it.