7 Factors in Driving Success with Key Performance Indicators

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The ability of management to steer their organization toward achieving success is directly dependent upon the information they have before them and their decision-making process. Having the right information at the right time requires a data and analytics ecosystem that can present accurate and timely data in an easy-to-understand manner. A best practices approach to analyzing data is to start with highly summarized information and then investigate those areas that are outside the bounds of expectation. Summarized information in the form of measures or Key Performance Indicators (KPIs) provide individuals with the information they need to assess performance and make informed business decisions.

Key Performance Indicators

Relevant information can be presented in different forms. KPIs are meaningful, predefined measures that provide individuals with the information that they need to assess previous actions. KPIs can then be compared to target performance and provide individuals with the ability to assess past performance. For example, if the goal is to improve customer satisfaction, then several KPIs can help to monitor that goal, including order cancellations, response times to customer inquiries, and customer churn. Looking at the customer churn KPI in greater detail, the purpose of this KPI is to monitor the rate of customers who stopped being a customer. This KPI should raise several questions such as:

  • Why did the customer stop being a customer?
  • Was there something we could have done differently to save that customer?
  • How does the current customer churn rate compare to target performance?
  • Is the churn rate indicative of a historical trend?

While KPIs present individuals with meaningful information for decision-making purposes, there are several factors that one must consider.

1. Defining the indicators of performance. KPIs can be difficult to define because the definition requires knowing what performance to measure and how to measure them. In addition, consensus from the individuals who are being evaluated based upon the KPI is critical. Without a commonly accepted definition of a KPI, it will not be accepted or used.

2. Obtaining the necessary data. Once the KPI has been defined, the necessary data needs to be acquired and curated. Depending on the complexity and number of the operational systems of the organization, this task can become quite daunting. Ideally, the information that is needed is already stored within a repository such as a data lake or data warehouse.

3. Calculating the values according to the KPI definition. Applying the business rule or calculation to a set of data in order to derive a KPI requires a clear understanding of its definition by the individual who is responsible for this task. Incorrect calculations are primarily caused by a lack of understanding.

4. Performing timely updates. The frequency at which KPIs need to be updated is important for ensuring the data is available and scheduling the calculation of the measures. Keeping the KPIs updated on a periodic or on an as needed basis is critical to providing individuals with current meaningful information for decision making.

5. Visualizing KPIs. Data, by itself, can be overwhelming and difficult to analyze. Through visualization, graphical representations of data can highlight important aspects within the data and assist the viewer in focusing on important items within the set of data being analyzed. In certain cases, visualization of information can assist the viewer in being more efficient with his/her analysis.

6. Presentation of KPIs. When presenting KPIs in the form of a report or a series of KPIs in a dashboard, it’s important to understand logical groupings and the number of measures. Too many KPIs presented together in one form is overwhelming to most individuals, so less is more. Also, the grouping of KPIs by subject matter or ranking of importance to the viewer makes them easier to interpret.

7. Analytics Catalog and Enterprise KPIs. Establishing common enterprise-wide business definitions and KPIs for individuals within an organization to use and access is critical to supporting fact-based decision making. An Analytics Catalog makes information available by providing business and data definitions as well as access to and discovery of KPIs, reports, and dashboards for insights and investigation.


In order to effectively make informed business decisions, individuals must be able to easily locate  relevant information. Curating reports and dashboards into a single, central Analytics Catalog simplifies the ability to quickly access and view KPIs - especially when those indicators may have been created in different underlying tools or applications. By centralizing KPI access, individuals can quickly see and assess relevant and timely information so that they can make informed and ideally better decisions.

The Analytics Catalog within ZenOptics Analytics Hub centralizes reports and dashboards from across the analytics ecosystem to establish an internal KPI marketplace for organization. Individuals can quickly and easily access enterprise KPIs, standard business definitions, and the supporting analytic assets to assess performance and further investigate what the indicators are communicating. To learn about ZenOptics Analytics Hub, please visit: https://zenoptics.com/platform

To learn about how ZenOptics delivers a KPI marketplace for its customers, please request a demo at https://zenoptics.com/demo

Published January 24, 2024
About The Author

Jonathan Wu has more than 30 years of experience in the field of Data and Analytics, which began with defining the reporting requirements for developing a multi-currency portfolio fund accounting system at Wells Fargo Nikko Investment Advisors in the mid-1990s. He has practical experience designing, developing and implementing data and analytics solutions at organizations such as Silicon Graphics (acquired by HPE), Visa, Pfizer, and the State of Hawaii Department of Health. Jonathan has held various executive leadership positions with several leading Data and Analytics companies beginning with the co-founding of BASE Consulting Group in 1994. In 2003, BASE merged with Knightsbridge Solutions and was subsequently acquired in 2006 by Hewlett-Packard to establish their Information Management Practice. In 2007, he joined Sand Hill Angels (SHA), a group of Silicon Valley executives and accredited investors that are passionate about entrepreneurialism and the commercialization of disruptive new technologies through startup companies. In 2016, Jonathan was elected Chairman and CEO of Diyotta, a pioneer of serverless data integration technology in the cloud and a SHA portfolio company, which was acquired by ThoughtSpot. He is currently the COO for ZenOptics, a SHA portfolio company. In addition to his primary work activities, Jonathan served as a Business Intelligence columnist for DM Review and Information Management magazine for many years, and a faculty member of TDWI/Transforming Data With Intelligence, Santa Clara University and the University of California, Berkeley Extension.

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