Root Cause Analysis

The system starts with a guided process for gathering and qualifying data about an operations problem. Based upon the recently discovered causal patterns, an expert system knows what kinds of causes must combine to produce your identified problem, and asks the essential questions to accurately uncover those causes.

Integrated into the data gathering process is the on-going validation of data. Data are ordered into sets of causes that combined to produce each step in the process that led to the problem. At each step, the individual sets of identified causes are tested for accuracy and completeness. This causal logic test assures that critical elements of the problem cannot fall through the cracks, as well as assuring that irrelevant facts are not included in the analysis process.

The information gathering process itself, automatically orders the data into a unique cause and effect model that supports objective quantification. Each avenue is pursued until either a root cause is identified, or the factor is found to be not correctable internally by the organization, or information is insufficient to continue the avenue of investigation. In effect, the process separates information much the same as do our minds naturally when we are solving our daily problems, into things we can do something about, things we cannot do anything about, and things for which we have no answers.

Once a root cause has been identified, the seamless process provides a systematic method for establishing where in the organization prevention can best be accomplished. This pinpoints exactly both what can be done in the action plan to gain immediate control over the internal system that produced the problem, and what steps are necessary to sustain control in the future. Because REASON focuses upon the internal business processes as the seat of root causes and their removal, those steps necessarily involve developing or modifying business processes. The resulting data are ordered and unified into causally associated facts that translate into new knowledge about why problems are occurring in the organization. It is this knowledge that sets the REASON Lessons Learned System apart.

When the data gathering and modeling of the problem are completed, the system applies an objective quantification standard to measure exactly how much each cause contributed to the problem. The system automatically generates a logic tree model showing graphically how each cause combined and led to the occurrence of the problem, a plain-English narrative explaining step-by-step how the problem happened, and an analysis comparing all prevention options in order to identify the best and most cost-effective solutions. The process has in effect mapped the information into a causally associated sequence of causally associated sets of causes. The knowledge that is contained within the data structure goes beyond content to reveal the causal sequences, combinations and interaction of the effects of the business processes themselves, revealing a new level and dimension of understanding exactly what is happening within an organization, and providing a view of options for addressing and improving the organization’s internal systems. With the data, one can reliably predict the outcome of actions, can compare options for anticipated best control and cost-effectiveness, can assess the criticality of risk remaining within the environment and can detect similar patterns within seemingly dissimilar environments and processes.

Corrective Action Tracking

At this point you will have determined your best corrective action options. Data flows into your REASON Corrective Action Management System. Responsibilities, assignments and schedules are established. The system communicates, monitors and documents each essential step from writing and implementing the action plan to completion: email assignment, notifications, alerts, reminders and management monitoring reports and documentation. Finally, verification follow up is scheduled, completed and recorded.

Lesson Learned

The completion of the prevention action plan is recorded and the data file is automatically submitted to REASON Lessons Learned. Key personnel throughout the organization have previously submitted a data profile of all of the issues that are important to their responsibilities and processes. As the REASON root cause analysis data flow into the lessons learned system, REASON is monitoring content, watching for matches to those data profiles. When a match is found, it immediately sends an alert. In moments the targeted individual has received a heads-up alert. Information gets to the person who needs it and can act to head off a developing problem. This real-time picture of what is happening within the organization is also immediately addressable as an information resource for workers, supervisors, engineers, planners and managers. Instead of a simple indexing of words to support word searches, REASON data is an ordered structure of data that permits you to search for factors that combined into a causal system at a point in time to produce a step toward a problem. The results of these searches are richer data content and strongly targeted information. Thus the organization’s information about counter-quality becomes a dynamic, real-time resource, rather than merely a static storehouse of facts.

Risk Management

The same data file that was created when the problem was first solved, and that was used by Lessons Learned for access to past experiences, also serves as the resource for new kinds of data for risk managers. The simple and straightforward premise is that each root cause represents a lack of control or risk within the environment. Because the REASON system can measure the system that produced the problem, it is possible to calculate how much each cause contributed to the problem. In effect, it measures the amount of actual risk each cause represents in the environment. If we act upon a particular root cause, we remove a measured amount of risk. Knowing which causes remain in the environment enables us to measure and manage the known remaining risk. The hard numbers returned by the system provide unique and meaningful analyses and risk trending capabilities.

The ability to measure risk and to assign priority to corrective actions based upon that measurement provides an objective criterion for assigning responsibilities, setting completion due dates, tracking and managing corrective action plans. In the REASON Corrective Action Management System, where root causes are identified and prioritized, corrective action plans written, responsibilities assigned, activity scheduled, aged, tracked and monitored, the utility of having objective criteria for establishing priority and scheduling of work projects is a significant benefit.

Control Effectiveness

REASON root cause analysis provides new and unique data for oversight and monitoring of control effectiveness at the micro and macro level. For example, it is possible to measure the effectiveness of control not only by facility, process, and operation, but also at the organizational level to determine effectiveness of the overall control at the management, supervisor and individual level. This view is available for a single problem, a group of problems, or all recorded problems that were solved and recorded. Again, the data can help form decisions for planning and action. With REASON data one can pinpoint areas of concern, identify systemic patterns, determine best actions and monitor in real time the effects of those actions upon controls. Some would say that the exercise of such capability is a demonstration of management wisdom.

When problems and their solutions are linked to business processes, the data can provide dramatic insights to the internal health of the organization. As organizations, we set survival and success goals; we devise strategies to achieve those goals; we develop policies to accomplish those strategies; and we set in procedures to comply with those policies. By directly linking the occurrence and amelioration of operations problems with these fundamental structural steps, we create a window through which we can see how an operations problem on the shop floor directly impacts that chain of executive controls from policy to strategy to corporate goals. We see exactly how policies are affecting our strategies and whether our strategies are contributing to or detracting from our goals. The ability to associate business processes with the strategies and goals of the organization provides executive managers with both a new visibility of the efficiency and effectiveness of executive controls over critical operations, and a new means of monitoring the function of organization strategies and goals.

  New Avenues to Improvement

This expanded resource of information made possible through DSI research and product development has early provided new capabilities and insights into ways organizations can improve operations quality. If your management group is seeking new avenues to continued success and operations improvement, we encourage you to investigate the promise of REASON as a means to gain increased value from your internal information. If your organization has already made a commitment to knowledge management as a growth activity for operations improvement, we invite you to explore the dramatic benefits that REASON Root Cause Analysis holds for you.