Managers and teams operate under assumptions, receiving feedback from the markets, and constantly trying to adapt their offerings to remain in business.

Monitoring operational performance and benchmarking should be a constant, automated task. Performance monitoring is more than just a few numbers: they are the foundation for further accessing your business intelligence.

But getting valuable insights is not self-evident.

Operational Performance Objectives

Why Operational Performance Monitoring ?

In the past, as today, businesses seek products, services, and offerings that allow them to remain ahead of their contenders. Continuous innovation, cost reduction and improved resource usage are just a few examples of better operational performance. One of the most well-known concepts of continuous improvement is Kaizen.

In general, operational performance objectives are measures evaluating the efficiency of an entire process. We are looking to identify ways to improve operations, such as developing a product or service to the end of its life. 

Eventually, performance measures allow managers or teams to assess process inputs (the resources allocated) and outputs (direct results of process steps or service activities) to make an informed decision.


Download and learn

  • Why do I need operational performance monitoring?

  • How can I introduce data collection?

  • Which methods do I use for data collection and analysis?

  • How can I apply benchmarking the right way?



"What gets measured is what gets done" is still true today. Operational performance objectives describe and focus long term goals and strategic objectives.

They also draw people's attention to what counts, what matters, and what is essential. Performance results are helpful for leadership and management because they are precise and actionable.

The connection between goals and performance has been demonstrated empirically: What gets measured gets attention. This can benefit the process already before operational improvements have been implemented or the measurement results are known.



SMART goals set a group up for success by making goals specific, measurable, achievable, realistic, and timely. The SMART method provides direction and helps organize and reach the team's goals.

Comparison of data is possible when you use measures of quantitative assessment. Unfortunately, not all data are immediately available in this format. In science, this is known as quantitative and qualitative research. When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.



Quantitative and qualitative data can be collected using various approaches. It is important to note that every method will produce different results. Therefore, deciding when to use a specific data collection method is critical to answering your measurement question. A rule of thumb for determining whether to use qualitative research methods is if you want to understand something like a concept, thoughts, or experiences to formulate a hypothesis. Use quantitative research to confirm or test a theory or hypothesis.



Once data is collected and analyzed, management and team still need one final step to gain the desired insights: the context. Data like a number is just a number. Its meaning (good or bad, important or trivial, expected or unexpected) is set externally. Its value is not inherent but rather depends on context. The context is what tells the story and will lead you to interesting, sometimes surprising results and insights.

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