Key performance indicators for Lean Manufacturing Excellence

by S. “Mani” Manivannan, Ford Motor Company

Automotive industries are faced with many of the same pressures as other industries, but that doesn’t mean the same old “solutions” will work every time

Are Key Performance Indicators (KPI) metrics driving or killing your business?

A manufacturing truth— “You cannot change that which you do not measure.”

What is KPI?
KPIs, or key performance indicators, help organizations achieve organizational goals through the definition and measurement of progress. The key indicators, agreed upon by an organization are variables that can be measured to reflect the success of processes or initiatives. The KPIs selected must reflect the organization’s goals, they must be key to its success, and they must be measurable. Key performance indicators usually are long-term considerations for an organization.

Metrics: When we use the term metric, we are referring to a direct numerical measure that represents a piece of business data in the relationship of one or more dimensions. An example would be: “gross sales by week.” In this case, the measure would be dollars (gross sales) and the dimension would be time (week.) For a given measure, you may also want to see the values across different hierarchies within a dimension. For instance, seeing gross sales by day, week, or month would show you the measure dollars (gross sales) by different hierarchies (day, week, and month) within the time dimension. Making the association of a measure with a specific hierarchal level within a dimension refers to the overall grain of the metric. Looking at a measure across more than one dimension such as gross sales by territory and time is called multi-dimensional analysis.

Key Performance Indicators are measurable, definable metrics typically used to signify company goals. KPIs are considered to be primary metrics. Key Performance Indicators, when exposed and properly analyzed can be used to understand and improve manufacturing performance.

Every company measures themselves to some degree. Often, measurement and analysis occur based on historical information. Although there is value in historical analysis, KPIs are biased toward real time data and are used to support decisions that enhance manufacturing performance. KPIs are tied to company goals and require careful design and implementation in order to support positive change. As with many organizational issues, acceptance of Key Performance Indicators and how they will be used to improve performance is critical.

A KPI is simply a metric that is tied to a target. Most often, a KPI represents how far a metric is above or below a pre-determined target. KPI’s usually are shown as a ratio of actual to target and are designed to instantly let a business user know if they are on or off their plan without the end user having to consciously focus on the metrics being represented. For instance, we might decide that in order to hit our quarterly sales target we need to be selling $10,000 worth of widgets per week. The metric would be widget sales per week; the target would be $10,000. If we used a percentage gauge visualization to represent this KPI and we had sold $8,000 in widgets by Wednesday, the user would instantly see that they were at 80 percent of their goal. When selecting targets for your KPI’s you need to remember that a target will have to exist for every grain you want to view within a metric.

A new handbook released by the Manufacturing Enterprise Solutions Association (MESA) shows that manufacturers that leverage technology to measure KPIs have an edge in managing their operations, yet very few manufacturers effectively manage their performance. Only 3 percent of study respondents report very effective links between operations KPIs and business metrics. This means that most companies’ management teams do not have views that accurately represent progress and plant contribution.

See the reference from ISO/TS16949 for the critical importance of KPIs:
ISO/TS16949 (2nd edition), 8.4: Analysis of Data:
The analysis of data shall provide information relating to
a) Customer satisfaction
b) Conformity to product requirements
c) Characteristics and trends of process and products including opportunities for preventive action, and
d) Suppliers

The simple fact to keep in mind is, “Any KPIs without proper analysis and action plan to improve the same are not useful.” This should drive the selection process for KPIs.

If the goals on the KPIs are not being met, have an action plan in place (documented) to meet or exceed the goals. See the ISO/TS16949 coverage on planned results not achieved and action plan.

ISO/TS16949 (2nd edition), 8.2.3: Monitoring and measurement of processes:
The organization shall apply suitable methods for monitoring and, where applicable, measurement of the quality management system process. These methods shall demonstrate the ability of the processes to achieve planned results. When planned results are not achieved, correction and corrective action shall be taken, as appropriate, to ensure conformity of the product.

You will often have more than one objective/metric for any specific process. There are externally-focused metrics (effectiveness) and internally-focused metrics (efficiency). Often I think about quality (e.g., satisfaction of the customer of the process with what they receive), cost (productivity, etc.) and delivery (e.g., cycle time).

However, one key caution here is to make sure that you don’t have too many metrics. There are organizations with literally 120-plus metrics. Needless to say, they weren’t managing them very well. They spent all their time in measurement and had none left over for management and review. The Pareto principle rules again.

The first thing is to Identify Key Processes for the Organization.
These are based on the Type of Organization. For example, in a manufacturing organization the Key Processes would be:
     1- Planning
     2- Purchase
     3- Stores
     4- Production
     5- Quality (Internal/External)
     6- Engineering
     7- Maintenance
     8- Research & Development (Innovation)
     9- Marketing, etc.

Generally, an organization will have certain goals, such as “Achieve turnover of 100 percent over last year,” “Reduce customer returns,” etc. Then, based on these company goals, the Individual KPIs for each process can be defined.

The key here is that individual KPIs should be aligned and linked to company goals to ensure they have real impact on the effectiveness of the overall KPIs.

For the above-mentioned nine key processes, each process can have 1 or 2 KPIs that are monitored by their respective process owners at an ongoing fixed frequency. These results are then reviewed by top management. This review serves to identify the gap by using Current State vs. Future State metrics with proper action plans to achieve the strategic objective.

Disconnects between financial and operational metrics abound. A metric may seem perfectly logical to one pocket of the organization, but when taken in context, even a person who has done a reasonable job of identifying the right metrics and aligning these throughout the organization may find they cannot shift behaviors to improve performance. To achieve this KPI metrics latency, information systems truly do need to span from sensors to the boardroom, like dashboards for example. Organizations that hope to remain in manufacturing need to invest in systems to gather and analyze data quickly and, ideally, automatically.

The study from MESA indicates that over 60 percent of respondents report that they gather less than 10 percent of the data collected for their operations metrics in a fully automated way. Manual and spreadsheet data collection methods to feed metrics are still fairly common in most plants.

They also need operational support systems that pinpoint what changes will trigger the desired future state improvements, and guide the process owners and employees to perform to best practice process standards.

Here is an example of a dashboard report:

Along with KPI automated dash board report out, an Andon system is beneficial. So what is Andon? It simply means “light” in Japanese. An Andon is any visual indicator signaling that a team member has encountered an “abnormal situation,” that can not be resolved without preventing a stoppage (as defined by takt time). Poor quality, lack of parts information or tools may cause an abnormal condition.

Key to effective andons is that they are visual and support “management by sight” before the KPI data hit.

In a study conducted by the Aberdeen Group study, participants were asked which KPI metrics were most important to achieving success. Close to 80 percent of best-in-class companies cited “On-time Delivery” among the top three metrics. Next was “Inventory turns,” with 52 percent; then “Manufacturing cycle time,” with 39 percent. On-time delivery is considered a process metric because it includes the time that takes to accept and process a customer order, manage through production, and ship to the end customer.

Reducing Non Value Added (NVA) manufacturing and supply chain costs was recognized by 66 percent of the respondents as one of the most important strategic action relative to pursing Lean. Value Stream Mapping (VSM) is the technique of choice for accomplishing this goal. VSM has evolved over time from simplistic flow charts to Current State Mapping to Future State Mapping. KPIs are the tools that identify “gaps” where improvement is needed.

When an organization achieves its order-to-delivery measures, generally this means that each participant company or division that added value met its KPI individual metrics. And although order-to-delivery may not link directly to strategic objectives, it is a strong contributor to customer satisfaction, which is measured by virtually all companies. Better performing companies also believe that their ability to successfully meet “First Time Through (FTT)” quality goals is an KPI indicator of future product quality and efficiency.

Selecting your KPIs
When you select/review KPIs for each area, make sure they are relevant to the area! (In many study cases, the goals set by management had nothing to do with the area/process involved.) Obviously, this is a recipe for failure.

Six Sigma/Define Measure Analyze Improve Control (DMAIC) problem solving methodology is highly recommended when selecting the KPIs and their action plans.

Define:
 • Define the goal as defined by your business/strategic plan.
 • For the goal/strategic plan, what are the possible indicators you could use to determine process improvement?

Measure:
 • Is there existing data (internal/external) available that measures any of the listed KPIs that will tell if you are improving the process? (Yes or No) If yes, what is the source of the data?
 • Are there any additional needs, special circumstances, hindrances or other factors that may impact obtaining or collecting the data? (Yes or No) If yes, please explain.
 • How often are you going to collect, report, and summarize data?
 • KPI must be measurable.

Analyze:
 • Collected data should be analyzed by the process owners to determine the “future state.”
 • Timeliness of data analyze is crucial to move onto next steps.
 • The simple fact to keep in mind is, “Any measurement without proper analysis and action plan to improve the same is not useful.” This should drive the selection of process for measurements.

Improve:
 • Are you able to use the KPI data collected to improve the process?
 • Select one to three KPIs, state the goal in quantifiable language (reduce, increase, implement).
 • What best practices have you identified to compare and improve your process?

Control:
 • Analyze data to determine success: Objective has been met, needs to monitored? (Yes or No)
 • Did data produce information needed? (Yes or No) Keep KPI or replace with new KPI: Keep/Modify/Replace?
 • Revise Strategy/goal?

Importance of Key Performance Indicators levels:
KPIs provide a hierarchy for delivering relevant performance-related information to different levels within an organization so the right people can access the right information at the right time. Collected lower-level KPIs can be easily combined and rolled up to create higher-level KPIs that can reflect more specific strategic/business objectives. Such higher-level KPI measures therefore do not have to be directly measured. Instead, they can simply be summed from previously collected KPI measures. A performance KPI measure hierarchy also represents an excellent diagnostic performance measurement system for meaningful KPI. Higher-level KPI measures can also be easily decomposed to lower-level elements when attempting to zero in on a problem area.

KPI measure levels:
Shown below is a typical example of KPI levels for a machining operation that need to be considered to review the true value of First Time Through (FTT) efficiency from operation #10 to the final product. You need to be able calculate the Overall Equipment Efficiency (OEE), Cycle Time and Scrap in order to get a true value of final product First Time Through (FTT).

Follow the recommended steps of KPI measure level creation:
 • Define needed types of performance-related information that can help achieve desired performance levels
 • Develop a relevant and usable family of KPI measures
 • Develop specific performance measurement hierarchies

What does your management group feel is the difference between an effectiveness indicator and an efficiency indicator?

In order to successfully leverage performance improvements based on KPIs, there are three main precursors:
       • Measurability
       • Team acceptance
       • Conformance to organizational goals

Measurability
The KPI must be measurable. The methodology of the measurement must be documented and accepted before the process begins. Understanding exactly what is to be measured will help determine how it will be measured. The effects of changes can be tracked through careful analysis of the benchmark KPI data. Goals and desires are often vague — key performance indicators are always very specific.

Team acceptance
Team buy-in is often the difference between success and failure of many manufacturing projects. Buy-in is critical to KPIs. KPIs are typically the primary source of information regarding the performance of a process that is being monitored. In order to successfully use the data, everyone needs to understand why the indicator was chosen and how it represents the underlying condition. Additionally, since the data will be used as an indicator of process performance, it is necessary that the entire team use it in the same way.

Conformance
General company goals and initiatives are at the heart of KPIs. By determining a way to measure the success of a project, companies are able to monitor change. When action is required, KPIs will provide advance warning. Successful KPI implementation means limiting exposed performance data to only key indicators. Often there may be a desire to measure the entire process. While this is understandable, the difference between KPI and other metrics must be understood and enforced.

KPI provides a mechanism for companies to identify areas for improvement, create the metrics that will be used to analyze the process and the tools to support change to the future state. Lean manufacturing is a process. Companies that use KPIs in this context use them to improve every day.

How can KPIs help my organization?
Once you’ve defined the KPIs that reflect your company’s goals and have a consistent way to measure them, use them to enhance performance by charting the progress toward the target KPI. Only then will people be informed and motivated to:
       • Support company initiatives
       • Manage growth
       • Manage change

Here are a few examples of suggested KPIs with Lean and Six Sigma impact:

Process owners need a full commitment to manufacturing disciplines such as:
      1. Process control
      2. Equipment reliability
      3. Safety
      4. On-time shipping

The entire culture of “Lean Manufacturing Excellence” can be summed up in two key words: VARIATION REDUCTION – ELIMINATION OF MUDA

This is applicable to both the mechanical and human sides of the performance equation.

In its simplest terms, there is only one right way to run a machine — with discipline and knowledge. It can be statistically verified and consistently maintained.

On the human side, the more consistently technical knowledge increases, the more consistent daily feedback becomes (for example, by automated dashboard data of KPI metrics). This also leads to more consistent performance system, more consistent positive encouragement and less performance variation.

Common lean failures:
 • Lack of management support
 • Resistance to change (lack of buy-in) from supervision
   and workforce
 • Poor lay out metrics
 • Not enough training
 • Little or no impact on profitability
 • Ineffective communications
 • Not able to sustain initial efforts
 • Not expanding improvement from the initial efforts
   to other departments/processes
 • Improvements in one area seemed to have negative
   impacts in others

In general, if you have correctly located the current constraint, improving it will increase total output (from the company, department, process, product and/or machine). While improving an area that is not the current constraint may have certain benefits, it will not improve total output. If you have improved enough, the improved entity will no longer be the current constraint. We call this process “eliminating the current constraint.” This doesn’t mean it will go away completely though because when one current constraint is eliminated, it gives way to another. When you find it, your goal will be to eliminate it. This process of constraint elimination with appropriate KPI metrics will be repeated until you are satisfied with the current output level and can monitor it with applicable KPIs.

Eliminating constraints is an ongoing battle!

Subramaniam “Mani” Manivannan is a Quality Coach/Assessor – PTO Quality manufacturing process and product support engineer for Ford Motor Company in Dearborn, Michigan. He can be reached by e-mail at: smanivan@ford.com.

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