Performance metrics are meant to guide businesses, but in most organizations, they do the opposite. Leaders stare at colorful dashboards packed with red-yellow-green indicators, unsure of where to focus. Metrics are reviewed in isolation, performance is judged in snapshots, and improvement efforts chase symptoms rather than root causes. The result? Misalignment, wasted effort, and missed opportunities.
Good metrics provide decision-making insight that leads to the most appropriate conclusion and action or non-action. The objective is to create a measurable, auditable, sustainable, and consistent entity. Effective and reliable metrics should have/provide the following (Reference Section 3.2 Integrated Enterprise Excellence, Vol. II Business Deployment: A Leaders’ Guide for Going Beyond Lean Six Sigma and the Balanced Scorecard):
- Business alignment
- Honest assessment
- Consistency
- Have repeatability and reproducibility
- Actionability
- Time-series tracking
- Predictability
- Peer comparability
However, organizational performance metrics do not typically have all these characteristics.
Smartersolutions.com’s Integrated Enterprise Excellence (IEE) system offers a radically different approach. This page introduces Performance Metrics 2.0, a smarter, enterprise-wide performance measurement strategy that overcomes the failures of traditional metrics reporting.
An IEE 30,000-foot-level report scorecard, as illustrated in the left figure of the following graphic, addresses these elephant-in-the-room shortcomings.
IEE 30,000-foot-level report scorecard (performance metrics 2.0) characteristics:
- Performance metrics are assessed from a high-level or 30,000-foot-level viewpoint (not unlike the view of the terrain below from the window of an airplane in flight)
- When the data points are within an individuals chart’s control limits (red lines), the process is considered stable
- The performance metric from a stable process is considered predictable
- A best-estimate prediction statement is provided at the bottom of the report
- If a bottom-of-the-report futuristic statement is undesirable, there is a need for process improvement.
Conclusions from the 30,000-foot-level attribute-response performance metric shown above:
- The staging of the above 30,000-foot-level report on about 2017-07-01 indicates that there was an improvement in the process
- If the current bottom-of-the-report estimated customer dissatisfaction rate of 0.089 is unsatisfactory, there is a need for additional process improvement
Use our free 30,000-foot-level report app to create a performance metric 2.0 report for your data.
Business Performance Metrics Dashboard
Most business performance metrics dashboards are more about visual appeal than actionable insight. They give a sense of control but rarely guide meaningful action. A dashboard might show customer complaints in red and revenue in green, but what should leaders do about it? Which issue matters most? Are these signals or just noise?
IEE transforms dashboards from decoration into direction. Rather than simply displaying metrics, Performance Metrics 2.0 helps organizations:
- Evaluate trends with statistical relevance
- Eliminate arbitrary thresholds and color codes
- Prioritize efforts based on enterprise impact
Traditional dashboards encourage reactive management. In contrast, Performance Metrics 2.0 fosters proactive, system-level decision-making.
The following figure shows the transition from a traditional table-of-numbers report to a 30,000-foot-level report.
One can consider that the output of a process is “Y” and its inputs to be “Xs.” Mathematically, this relationship can be expressed as Y=f(Xs), i.e., .The output of a process Y is a function of its inputs.
In this illustration, “Down Time” is the “Y “, and “Line Number”, “Shift”, and “Start Time” are the process “Xs”. Variation from the X’s is a source of “common-cause” or “noise” variation to the Y response (a vital metric to the business),
In 30,000-foot-level reports, we only track the Y response.
Suppose the Y response prediction statement is satisfactory at the bottom of a 30,000-foot-level report. In that case, there is typically no business reason to understand any specific relationship that may exist between an X magnitude and a Y response.
However, if there is a need for improving a Y response, then an understanding of the Y response magnitude of input Xs can be beneficial to determine what to do differently. For instance, if the 1st shift’s downtime is statistically significantly less than the 2nd shift’s, an investigation is warranted to determine how to reduce the 2nd shift’s downtime to a comparable level of the 1st shift.
In this illustration, the “Y” response is continuous, and there are no specification limits. For this type of situation, the bottom of the 30,000-foot-level report provides an estimated median (or mean) and 80% frequency of occurrence rate. The 80% frequency of occurrence rate offers the reader of the report a sense of expected variation from the “Y” response over time.
However, if there were customer specification limits for a “Y” response, then the bottom-of-the-report statement would be an estimated non-conformance rate, if the process were stable.
This illustration of a 30,000-foot-level report is for a continuous “Y” response. The 30,000-foot-level report shown with the elephant-in-the-room is for an attribute non-conformance rate-response. One can create a 30,000-foot-level chart for virtually any type of process-output response.
Six Sigma Performance Metrics and AI
Six Sigma performance metrics are typically applied within project silos, using tools like DPMO, sigma level, or process capability indices. While valuable, these measures often fail to connect with broader business strategy.
With Performance Metrics 2.0, Six Sigma isn’t just about tools and belts. It becomes part of a holistic business improvement framework.
IEE integrates Six Sigma metrics into enterprise alignment. The IEE 9-step system provides, by way of an Enterprise Improvement Plan (EIP), a visual showing how the improvement of a 30,000-foot-level metric for an improvement project (Step 7 column) aligns with a financial business goal (Step 4 column).
An example EIP for a hospital is:
IEE enables:
- Linking project-level improvement to enterprise goals
- Identifying which processes truly need Six Sigma rigor
- Avoiding wasted efforts on “successful” projects that don’t move the business needle
IEE’s Six Sigma metrics reporting provides a solution to the many technical issues with traditional control charts (i.e., x-bar and R, P-charts, C-charts, and U-charts) and process capability indices (i.e., Cp, Cpk, Pp, and Ppk) for an organization’s Lean Six Sigma implementation. Articles describing these technical issues and their resolutions are provided in “Forrest’s Favorites.”
In a traditional Lean Six Sigma deployment, improvement projects follow a DMAIC roadmap. In the IEE system, any tool can be used to determine what to do differently to improve a process.
AI is a tool that can be very useful, especially when combined with IEE software value chain software (described below), to determine what to do differently to meet an organization’s financial goals. Techniques for accomplishing this is described in “AI Implementation 2.0: A Better Way to Achieve Holistic Business Transformation.”
Performance Management Metrics
Performance management metrics are supposed to help evaluate employee or departmental success. But too often, they promote internal competition and short-term thinking. KPIs become quotas. People game the system. And real problems get buried under political optics.
Performance Metrics 2.0—enabled by IEE—breaks this cycle by:
- Measuring process outputs rather than individual effort
- Promoting cross-functional collaboration over blame
- Evaluating results in the context of system behavior, not snapshots
This results in a cultural shift: from compliance and finger-pointing to shared ownership and continuous improvement.
Integrated Enterprise Excellence (IEE) Business Management System Software provides a behind-the-firewall implementation of an IEE Enterprise Performance Reporting System (EPRS) in an organization.
With IEE, an organizational IEE value chain (Step 2 of the IEE system) describes what an organization does and how it measures what it does. An IEE value chain is clickable and provides information to all authorized users 24/7.
Leadership System 2.0: Implementing Integrated Enterprise Excellence, Figure 6.4, illustrates the high-level Enterprise view of Harris Hospital, discussed in the book.
In this Harris Hospital IEE value chain view, the primary functions are connected by arrows, while the support functions have no arrow connections. With software, all functions are accessible 24/7 to authorized users.
The following figure shows a drill down of Figure 6.4 to Figure 6.9, Harris Hospital’s Produce and Deliver Services function.
The following figure shows a drill down of Figure 6.9 to Figure 6.10, Harris Hospital’s 30,000-foot-level metric for Length of Stay.
The above Length of Stay 30,000-foot-level report has a weekly subgrouping because the length of stay varies by day of the week a patient is released (an “X” input to the Length of Stay “Y” response).
Examples of Business Performance Metrics
Here are common examples of business performance metrics—and how Performance Metrics 2.0 reinterprets them:
Traditional Metric: Customer Complaints
- Old view: Count complaints monthly and flag red if above X.
- IEE view: Track the number of monthly complaints over time (e.g., many years): Assess process stability using an individuals chart; stage any observed process changes; resolve any identified “special-cause” response events (e.g., a new product design problem caused a significant increase in complaints); provide a prediction statement for a stable response; undertake a process improvement effort if the Y-predicted response is undesirable (e.g., a process improvement investigation found that customers frequently complained because their products’ setup instructions were confusing).
Traditional Metric: On-Time Delivery
- Old view: Track percent on time and hold teams accountable.
- IEE view: One could track the percentage of monthly orders over time (e.g., many years) and do similar activities as described in the Customer Complaints illustration. However, more helpful information about a process is available if an organization can obtain “how late an order was” and “how early an order was” (e.g., the number of hours late being a positive number and the number of hours early a negative number). The reason for this is that the lateness of a delivery can have a dramatic impact on customer satisfaction (e.g., 1 hour late versus 300 hours late would count the same as a missed order delivery time, but customer opinion could probably differ dramatically). For this tracking-of-time-against-a-due-date situation, a weekly subgrouping would probably be appropriate since the day of the week that an order was to be received (an X) could impact the Y response.
Traditional Metric: Product Non-conformance Rate
- Old view: Report monthly non-conformance rate numbers in Tables so Executives can direct corrective action.
- IEE view: Track a non-conformance rate (e.g., over many years) using an individuals chart (i.e., not a P-chart). Select an appropriate subgrouping frequency so that a significant number of failures occur in the periods, e.g., weekly or monthly. From a 30,000-foot-level perspective, one can include in this metric report failures from several sources, e.g., product or defect types. One can create a Pareto chart to summarize the types of defects from a 30,000-foot-level chart over a stable time period. This Pareto chart can provide insight into process improvement opportunities. In IEE, a 20,000-foot-level chart serves as a reference for tracking a large Pareto chart item separately, using techniques similar to those employed in creating a 30,000-foot-level report. Also, one should consider similar activities to those described in the Customer Complaints illustration.
NOTE:
- A significant difference between the previously described “old view” and “IEE view” is that the “old view” attempts to manage the process via a “Y” response, which can lead to very unhealthy, if not destructive, behaviors (e.g., playing games with the numbers).
- The previous “IEE view” dialog may give the impression that there will be much ongoing work. This observation is not valid since there would only be an initial straightforward setup where metrics are typically updated daily and observed, staged, and acted upon by various departments, when appropriate.
- These examples illustrate that context and system behavior matter more than isolated numbers.
Why Traditional Metrics Fail
Before exploring the benefits of IEE, it’s critical to acknowledge the pain of current systems:
- False alarms: Noise in data leads to overreaction.
- Missed warnings: True issues are masked by color-coded calm.
- Silo decisions: Metrics drive local optimization, not enterprise success.
- Firefighting: Leaders chase symptoms without root cause clarity.
- Gaming: KPIs incentivize behaviors that undermine long-term value.
If your dashboard encourages defensiveness instead of insight, your organization is flying blind.
The IEE Advantage in Performance Metrics 2.0
IEE brings clarity, alignment, and insight to performance metrics. Unlike traditional scorecards, IEE provides:
- Enterprise Alignment: Every 30,000-foot-level metric is reporting in an IEE value chain and can be updated regularly via IEE software
- Statistical Rigor: 30,000-foot-level charts reveal true trends and can provide predictive statements
- Prioritized Focus: Root causes are targeted for process improvement efforts when a predicive statement is undesirable
- Integrated Improvement: Metrics drive actionable change (or non actions) across the enterprise
By implementing IEE, organizations gain a single source of truth that unifies planning, measurement, and execution.
A Better Way to Lead with Metrics
Leaders today are overloaded with data but under-informed. Performance Metrics 2.0 offers a way out:
- Fewer, more meaningful metrics
- Trends that matter, not snapshots
- Decisions based on evidence, not instinct
Imagine a world where your organization doesn’t just track performance—it understands it, improves it, and aligns it with strategic goals.
That’s the world Smarter Solutions helps you build.
What’s Next?
If your organization is:
- Tired of reacting to dashboard noise
- Frustrated by inconsistent improvement efforts
- Ready to make data a driver of strategy
…then it’s time to explore Performance Metrics 2.0 with Smarter Solutions.