Root Cause Analysis

Value-Driven Metric Maturity

In this series on value-driven metrics we have looked at the purpose and structure of business metrics, and have identified a number of characteristics of a world-class business metric design. How do we leverage this information to set our sights on actually making this a reality? How do we get started, and make it happen?

Knowing what we need in each metric through a world-class metric definition, and how each component of the metric fits with the others and completes the whole, allows us to identify inter-dependencies and precedence relationships between the metric elements. This insight allows us to sort the requirements into a series of milestones, forming roadmap for developing a complete metric.

Once we understand the roadmap, we have an intuitive way to classify the maturity or completeness of any given metric, and by extension, the overall maturity of a business metric infrastructure.

Rating	Status	Description
1	Conceptual	identified as useful
2	Manual	calculated and reported manually
3	Automated	calculated and reported with no manual intervention
4	Systematic	consistently monitored in a business process
5	Bounded	trigger points define acceptable behavior
6	Actionable	corrective actions are defined and carried out
7	Detailed	business case details are fully documented and accessible
8	Integrated	placed in the global metric hierarchy
9	Tuned	trend/tension analysis maintains globally optimized trigger point(s)
10	Mature	intrinsic to system governance, enables root cause analysis, and full business value is established

By classifying each metric as above and taking a weighted average across all of the metrics required for a business, based on a relative prioritization of their perceived importance, one may derive an overall maturity score for a metrics system and set goals for enhancing overall metrics capability.

A well-defined metrics system is essential for the value-driven enterprise. Understanding world-class metrics methodology is the first step toward realizing it.

Value-Driven Metric Design

In our last post we considered the importance of defining corrective actions for each business metric: a business process with the specific goal of reversing sub-optimal performance trends, and triggering these corrective workflows by setting metric trigger points which identify an acceptable range of behaviors associated with the metric. These insights identify two key design components of a well-defined metric: trigger points and corrective actions. What are the other components of a world-class metric design?

To define the ideal design for a metric, we must keep its purpose in mind: to drive a business toward optimal performance. What else do we need in a metric definition to enable an enterprise to reach its full potential?

Firstly, a clear description of the metric, its purpose and scope, and its value to the business, should be documented. This should include any business scenarios where the metric is particularly relevant, how the metric is to be understood and interpreted, clear definitions of any special terms used in defining or describing the metric design or intent, why the current metric trigger points are understood to define acceptable business behavior and how these were determined, and how the metric is correlated with other metrics in the metric hierarchy.

Further, each metric requires a formula, or rule of some kind to translate the underlying system behavior the metric is designed to monitor into an objective measure of system performance that can be used to evaluate how well the business is achieving its goals. This formula is normally mathematical in nature, where the metric value and trigger points are numerical, but this need not be the case. Whatever the method for calculating the metric value, to be most effective it must be clearly documented, understood, and agreed to by all stakeholders. This includes the data sources for populating all of the variables in the formula, who is responsible for maintaining this data, and how frequently this data must be refreshed. When there are debates about the correct formula or data sources, these discussions and the resulting decisions should be captured for reference. Documenting this information removes ambiguity and uncertainty related to interpreting the metric and acting on it, which is especially essential when behaviors are evaluated and corrective actions are taken based on the metric.

The business roles and relationships tied to the metric should also be clearly documented and understood, including who is Responsible, Accountable, Consulted and Informed in the execution of corrective actions, and any business consequences for prolonged or significant non-compliance with related business processes. In addition, documenting the history of the evolution of the metric definition, past metric trends, any issues or problems and how they were addressed, why certain enhancements were made by whom and why, all serve to explain and justify current business practices and provide guidance for future deliberations in continuous improvement initiatives.

Finally, the technical details of how the metric is reported should be documented: what is needed in the metric report(s), who interprets the reports, what business decisions are made from them, and how/why these required features enable related business processes and add value to the business. Historical changes to report content and layout should be documented to capture enhancement motivations and prevent regressing back to less optimal states.

Clearly documenting all of this information for each metric, where all stakeholders can easily refer to it as needed, facilitates process adoption and compliance, and enables stakeholders to make knowledgeable, informed recommendations for continuous improvement. The completeness and accessibility of this documentation is a key enabler in driving the business to realize its full potential, and is particularly important in dynamic environments where continuous improvement initiatives require frequent modifications to hierarchical relationships, trigger points, formula(e), data sources, and / or the terminology related to each metric.

In our next post, we’ll consider a world-class metrics maturity model, to help us understand the current state of a metric system, which will help us take steps toward improving it.

Value-Driven Metrics: Corrective Action

In our last post we considered how well-designed metrics enable root cause analysis. Positioning metrics within a global hierarchy of interrelated metrics equips a manager to quickly traverse the hierarchy, drilling down into sub-metrics which are reporting sub-optimal behavior until root causes are identified. But discovering the root cause is just a diagnosis; the real goal is to restore optimal behavior within the system. This capability is provided by identifying corrective actions for each metric.

A metric provides measurable value when it both reports sub-optimal performance, and also triggers responsible business roles to carry out corrective actions: business processes specifically designed to reverse undesirable trends and restore optimum business behavior. When timely and appropriate corrective actions are taken in the context of problematic system dynamics, business goals are achieved more consistently and optimally.

For example, when a Customer Service metric begins trending downward, triggering a root cause analysis workflow might indicate that Forecast Accuracy has also been deteriorating, requiring an update to inventory segmentation and buffering policies, and an update or enhancement to demand forecasting workflows and enabling technologies. If Forecast Accuracy has been stable but inventory targets are still being violated, it might be due to increasing supply variability caused by lack of plan conformance, requiring an enhancement to supply planning capabilities, plan conformance metrics, and a review of execution-level business processes.

As in the above example, corrective actions are often not the same as routine business process execution, since in a well-defined system business processes are inherently designed to produce optimal business behavior when followed correctly. When sub-optimal behavior occurs under such conditions, this is often symptomatic of a systemic, underlying problem with the business processes themselves and/or their corresponding process metrics. This may be due to incomplete or inappropriate design, or to unexpected system dynamics which require an adjustment or enhancement to one or more business processes or metrics. This principle often positions corrective actions within relevant system governance business processes, where problematic situations are often unique and require innovative approaches to resolve.

Identifying effective corrective actions for a given metric requires a thorough analysis of the business behavior being measured, understanding which actions most directly contribute to and influence this behavior, what steps must be taken to most efficiently correct sub-optimal trends and restore and maintain optimal behavior in likely business scenarios, and which business roles are responsible to carry out these actions.

For higher-level KPIs (those with supporting sub-metrics) corrective action often focuses on root cause analysis: exploring the metric hierarchy to understand why a given behavior is occurring and who is responsible to correct it. For base-level metrics (those without sub-metrics), corrective action is often related to parametric changes in planning and/or execution systems, business process or workflow enhancements, training and/or change management. Corrective actions and their corresponding RACI matrices must be well-documented, easily accessible to relevant roles, and continually enhanced as the business environment continues to evolve.

Now that we have considered how metrics should enable root cause analysis and drive corrective actions, next we will look at remaining aspects of a world-class business metric architecture.

Value-Driven Metrics: RCA

In our last post we discussed how world-class business metrics must be designed to optimize a global business system rather than focused on local optima; seldom is the optimal target for a metric a behavioral extreme. Ideal design requires metrics to be defined in a hierarchical relationship with other metrics such that their interdependencies are recognized and respected, and trigger points are set to achieve maximum business value.

Putting each metric into such an hierarchy requires understanding its relationship to the ultimate goals of the business, and ultimately provides justification for each metric in a global context. Metrics which appear to be isolated from real value creation are likely obsolete or irrelevant; these should be carefully reviewed and discontinued unless they can be fully justified as essential for understanding how the overall system generates value.

As parent-child metric relationships are identified and ironed out in the context of a global metrics hierarchy, metric trigger points should be set to drive corrective action which consistently tends toward optimal business value.

Once this hierarchical relationship structure begins to take shape, which certainly takes time and is seldom perfect, strategic metrics can begin to be used to perform root cause analysis: when a key business metric is reporting suboptimal behavior which requires corrective action, and the immediate steps of the business process are not designed to correct this behavior, then if its child metrics are well-defined, one or more of them should also be triggering corrective action, enabling a manager to drill down and traverse the metric hierarchy looking for root cause behavior in one or more supporting business processes, reflected in their respective process metrics.

For example, when a Customer Service metric begins trending downward, it might be noted that Forecast Accuracy has also been deteriorating, or that inventory targets are being violated frequently.

Alternatively, when a parent metric is triggering corrective action which is not directly and sufficiently addressed by its immediate business process steps, and neither are any of its child metrics calling for corrective action, this may be an indication that the metric hierarchy is incomplete, misunderstood, and/or that related metric trigger points are inappropriate. This condition may be used to tune metric trigger points, and/or to enhance/add business processes and process metrics in order to fully understand and efficiently manage the total system.

If in the above example, Forecast Accuracy has been stable but inventory targets are still being violated and no other cause is obvious, further exploration of recent supply plan and production history might reveal that machine breakdowns have been more frequent and longer than expected due to last minute execution-level overrides of planned maintenance, indicating a need to add plan conformance metrics and business process to the metric hierarchy.

In our next post, we will look more carefully at the concept of corrective action, and how defining this carefully is essential is to any business metric.