“What constitutes a good KPI example?”, “How should KPIs be measured?”, “Which KPI is suitable for our organization?”, and “How well will employees understand and participate in tracking these KPIs?” These questions often loom large for companies seeking to select the right KPIs to accurately measure their performance and progress toward strategic objectives.
According to The KPI Institute’s (TKI) State of Strategy Management Practice Global Report – 2023, choosing the right KPIs ranks as the second most significant obstacle in strategy planning.
The report further reveals a concerning trend regarding the challenges associated with working with KPIs. Results indicate a surge in the hurdles associated with KPI selection compared to the previous year.
Several factors contribute to the challenging nature of KPI selection, including the need to align with strategic objectives; the common practice of defining initiatives before KPIs rather than defining KPIs and targets first and then developing initiatives to reach them; clearly differentiating between strategic and operational KPIs at the departmental level; and focusing too much on task-related KPIs rather than impact KPIs at the employee level.
3 stages of KPI selection
Selecting the right KPIs requires careful planning, analysis, and collaboration across various organizational areas. A rigorous KPI selection process typically involves three major stages (see Figure 1).
Your initial step in the process is to set a clear direction for KPI selection by recognizing the business objectives and goals that must be attained. This is essential to ensure that all personnel are working towards the same objectives and that progress can be efficiently monitored. This stage clarifies the necessity and application of measurement while precisely defining the intended purpose of the KPIs.
Next, conduct thorough research to gather a range of KPI examples. This serves a dual purpose: educating your internal stakeholders and fostering meaningful discussions about KPIs. This process, labelled as the KPI expo, entails compiling a comprehensive list of KPIs that will later be filtered based on a set of criteria.
You should review both internal and external data sources (see Figure 2) to leverage existing practices while also gaining insights into industry best practices. The KPI expo can include existing KPI lists from various organizational levels, which may already be in use or have been tested within your organization.
In the next stage, use intelligence gathering and conduct workshops to identify suitable KPIs. You can obtain insights from a diverse range of stakeholders, including clients, suppliers, employees, and management. This approach will foster broader buy-in and support.
TKI recommends the following selection methods to ensure the identification of relevant KPIs:
Question framing: Guide discussions toward relevant contexts and gather participant perspectives. Questions might include, “How many KPIs should we select?” or “What is the procedure for validating the selected KPIs?”
Value flow analysis: Examine the flow of value within business processes—from inputs to outcomes—to understand how objectives can be measured from different perspectives.
KPI balancing: Avoid narrow perspectives by selecting at least two complementary KPIs per objective, ensuring the measurement of both quantity and quality, subjectivity and objectivity, and efficiency and effectiveness.
Additionally, among the existing criteria in practice, TKI suggests using these five to ensure KPI relevancy:
Measurable: Can the KPI result be quantified?
Accessible: Can your organization feasibly gather the necessary data?
Specific: Does the KPI address a specific issue you have?
Actionable: Does it provide information for decision-making?
Balanced: Does it reflect various facets of performance?
The final stage in the KPI selection process involves monitoring the selected KPIs for necessary recalibrations. This can be achieved through two key activities: KPIs documentation and the performance review meeting.
KPI documentation can reveal limitations associated with data collection or reporting and gaps in the cost-benefit analysis of the KPI’s usage. Develop a comprehensive set of information for each selected KPI to facilitate data collection, reporting, and analysis.
Use a standard template, known as a KPI documentation form (see Figure 3), capturing each KPI’s details, definition, calculation formula, target, data source, reporting frequency, KPI owner, and data custodian. For more examples, you can explore TKI’s comprehensive repository of KPIs at smartKPIs.com.
The first reporting and performance review meeting for the new KPIs will reveal their utility for decision-making. It provides managers with an overview of how the KPIs cover all aspects of the business and helps identify necessary adjustments to the corporate scorecard, ensuring that the most relevant data is available for decision-making. Facilitate this first meeting through your strategy office.
After this final stage, your KPIs can be maintained as initially selected, recalibrated and updated, or even phased out of use based on their effectiveness and relevance to your organizational goals.
By following these stages, you can select and implement KPIs that accurately measure performance and support strategic objectives, ultimately driving your business success and growth.
Ready to take your KPI selection to the next level? Head over to the KPI section on our website for more in-depth articles and expert advice.
Key performance indicators (KPIs) have been the north star guiding business strategy for decades. These criteria measure not only sales and revenue but also customer satisfaction as well as employee engagement.However, as the business landscape continues to evolve at an unprecedented pace, the need for deeper insights and more agile measurement arises. This is where the potential of generative artificial intelligence (GenAI) shines, opening doors to a new era of KPI innovation.
GenAI goes beyond automation to produce entirely novel content. It is a creative catalyst, opening up unprecedented possibilities for KPI innovation. Forget rigid, one-dimensional metrics. Powered by GenAI, KPIs become fluent, adaptive, and poetic, capturing not only the whats but also the whys and what-ifs.
Reimagining KPIs for exponential growth
From static to dynamic: GenAI is capable of integrating dynamic KPIs, meaning they can evolve alongside the company that uses them. KPIs also fit seamlessly into a changing market, with trends and strategies naturally shifting along the way.
Unveiling the unseen: Traditional KPIs often fail to hit the nail on the head by overlooking key, intangible factors that could affect performance. GenAI, however, can delve much deeper. With the help of GenAI, it is possible to determine brand sentiment before a particular campaign is launched, anticipate employee engagement within remote teams, or even predict customer turnover before it happens.
Personalized insights, enhanced action: Data mountains no longer need to be intimidating.GenAI transforms data into personalized narratives, crafting stories tailored to individual stakeholders. Sales teams can access actionable insights, marketing managers can monitor real-time customer sentiment, and CEOs can explore what-if scenarios for strategic foresight. This data-driven storytelling fosters informed decision-making and ignites action across the organization.
A practical guide to unlocking GenAI’s potential for KPI innovation
To effectively utilize GenAI tools like Gemini and ChatGPT for KPI innovation, follow these guidelines:
Define goals and challenges: Clearly articulate objectives, whether uncovering customer sentiment or anticipating market shifts.
Frame specific prompts: Use concise prompts such as “generate potential KPIs for measuring brand sentiment on social media.”
Provide relevant context: Enhance responses by furnishing background information about your industry, business model, and existing KPIs.
Experiment and refine: Iterate prompts, rephrase questions, and provide feedback to improve AI understanding.
Collaborate with experts: Involve human expertise in evaluating and implementing AI-generated insights.
While GenAI’s potential for KPI innovation is undeniable, it thrives on synergy, not substitution. The point is this: human guidance is essential. Act now, invest in your future, and become a master of the new KPI era by enrolling in The KPI Institute’sCertified KPI Professional course.
Today’s organizations drown in information waves. When leveraging data for actionable insights needed to drive strategic decision-making and sound performance measurement, visualization makes that data comprehensible and accessible. Specifically, key performance indicator (KPI) data visualization aims to communicate key performance metrics and trends in a way that is clear, concise, and impactful.
KPI data visualization benefits for organizations
KPI data visualization offers a multitude of benefits for organizations seeking to make data-driven decisions:
Enhanced data understanding: Visualizing KPIs makes it easier and faster to grasp complex data sets, identify patterns, and uncover hidden trends that would otherwise remain obscured in numerical form. KPI visualization provides insights regarding the entity’s current situation and helps a better understanding of the market.
Improved decision-making: Providing a clear and concise overview of key performance metrics, empowers decision-makers as KPI data visualization prioritizes evidence rather than intuition.
Effective communication and collaboration: Visual representations of KPIs facilitate effective communication and collaboration across teams by enabling stakeholders to share insights, align strategies, and achieve desirable goals. Additionally, KPI data visualization fosters accountability by transparently tracking performance against established goals, motivating individuals and teams to take ownership of their results, and promoting a data-driven culture within organizations to encourage data-informed decision-making at all levels.
Popular formats for KPI data visualization
The art of data visualization lies in presenting complex information in an informative and engaging way for all stakeholders. The most popular and effective techniques are as follows:
Charts and graphs: Bar charts and line graphs are effective ways to show trends and comparisons. Bar charts are effective in category comparison within a single measure. The line graph is mostly used to visualize changes in one value relative to another.
Maps and heatmaps: These visual tools are perfect for showcasing geographical data and identifying areas of concentration or dispersion.
Dashboards: Combining multiple visualizations on a single screen provides a comprehensive overview of KPIs (see Figure 1).
Figure 1. An example of medical center management performance dashboard | Source: The KPI Institute (2023), Medical Practice Dashboard
Major principles for effective KPI data visualization
Clarity and simplicity: Prioritize clarity and simplicity in data visualizations by avoiding cluttered charts and excessive complexity that may obscure insights.
Contextualization: Provide context for visualized KPIs by including relevant information, such as benchmarks, targets, and historical trends.
Visual Hierarchy: Establish a clear visual hierarchy to guide the viewer’s attention towards the most important KPIs and trends.
Storytelling: Utilize data visualizations to tell a compelling story, highlighting key insights and communicating performance trends effectively.
KPI data visualization has emerged as a transformative tool to support organizations in extracting meaningful insights from their vast data repositories. The first move for effective KPI data visualization is to embrace data culture across all organizational levels. The second step is to determine data constraints, such as the type of data, the number of variables, and the type of pattern one is trying to show (comparison, part-to-whole, hierarchy, etc.).
If you want to achieve effective KPI visual representations to support the decision-making process,? sign up for The KPI Institute’s Certified Data Visualization Professional course.
Image source: grapestock from Getty Images | Canva
In modern business, focusing on customer experience (CX) is no longer a nice-to-have, but rather a necessity for businesses of all sizes. However, defining a successful customer experience can be difficult because many touch points form the customer journey. By using online surveys, companies can gain quantitative information about the customer experience to actively monitor trends that develop over time. Based on customer feedback, organizations can identify areas for improvement, adjust their strategies accordingly, set better goals for their key performance indicators (KPIs), and strive to deliver the seamless experiences that today’s consumers expect.
Customer experience KPIs
Research shows that CX is now competing with traditional factors such as price and quality in influencing customer loyalty and advocacy. According to Forbes, 77% of consumers consider CX just as important as the main product or service itself. PWC reported that even beloved brands risk losing 32% of their customers after one negative interaction. In addition, poor CX burdens the company with costs. To address this, this article outlines five critical CX KPIs that can be systematically monitored, evaluated, and optimized to help address customer service problems and strengthen a company’s connections with its customer base.
1. % Customer satisfaction score (CSAT)
This KPI measures how customers rate particular interactions with a company, such as getting a response from customer care or processing a return. Users can score their satisfaction with the experience on a scale from “very dissatisfied” to “very satisfied” by responding to an automated questionnaire sent to them. Monitoring the ratings depends on a company’s objectives, but the general rule is that anything above 85% is excellent, and anything below 60% requires rapid attention.
Calculation: CSAT = (Number of Positive Responses / Total Number of Responses) x 100
2. # Net promoter score (NPS)
The NPS, considered the most famous CX KPI, reflects the willingness of consumers to recommend a product to friends and acquaintances. To calculate NPS, a company can conduct a survey of customers from one query: “What is the probability that you will recommend the product to your friends?” The answer is given on a 10-point scale, where 0 is “I will not recommend it in any case” and 10 is “I will definitely recommend.” The respondents can be divided into three groups depending on the scores obtained: promoters, passives, and detractors. The majority of companies consider a score above 80 as excellent, a score between 50 and 80 as very good, and a score below 50 as good.
An extension of the NPS index, the creation of the WoMI was motivated by criticism towards the traditional NPS. Researchers believed that the NPS made the incorrect assumption that if a customer does not recommend a product or service, then they are automatically considered detractors. This led researchers to make adjustments to the KPI in order to better reflect reality. It tracks the recommendation, but from the opposite perspective: “What is the probability that you will discourage people from doing business with the company?” This can be rated on a scale of 0 to 10. Those who choose 9-10 on the scale of “dissuading” are categorized as “true detractors.” The threshold varies from one industry to another. It is better to have a lower score, as the target for most companies is less than 10%. To gain a comprehensive understanding of your company’s position among customers, we suggest employing both approaches to obtain a complete picture.
WoMI = (Number of Promoters – Number of Detractors) / Number of Respondents * 100.
4. Consumer Effort Score (CES)
The CES index, which was developed in 2010, is related to the idea that the more effort the product or service requires from customers, the less likely they are to stay with the company. As cited in an article, research by the Corporate Executive Board (CEB) shows that 94% of customers who have an effortless experience are likely to make repeat purchases. The KPI could be measured by the customer’s response to a statement like: “Thanks to the service/product of company X. I was able to easily cope with my problem.” with a rating scale of 1 to 7. Most companies typically receive CES scores ranging from 5 to 5.5. A score exceeding 6 is generally considered above average.
CES = (Sum of response scores) ÷ (Number of responses)
5. Customer churn rate
Simply put, the churn rate is the number of users who stop any interaction with the company. Depending on the industry, this could mean that customers deleted their account, did not re-buy, or simply decided to switch to a competitor. In its simplest form, customer churn can be calculated by comparing the number of customers lost to the total number of customers. By dividing one metric by another, one can get the customer churn rate as a percentage of the total base. The most common acceptable churn rate is 5-7% annually.
KPIs must be monitored and measured in order to improve CX. To do so effectively, a system that accurately collects data from all channels should be considered. This allows requests to be categorized and common issues to be identified. In-depth interviews with both loyal and dissatisfied customers should be conducted to understand the root cause of any problems, as some of which could be related to support services. Consistency in tracking and improving CX KPIs is the key to ensuring decisions and actions in customer service adapt to changing customer sentiment and meeting their needs.
Take your CX to the next level! Visit smartKPIs.com for a comprehensive, 360-degree view of CX KPIs. For more in-depth articles on KPIs, click here.
The lifecycle of a Key Performance Indicator (KPI) is a dynamic process involving definition, recalibration, and—sometimes—abandonment. From establishment to practical application and ongoing evolution, KPIs undergo several steps to effectively measure performance, and prioritizing data reliability at every stage is crucial to achieving their intended purpose.
The foundation of reliable data
The first stage of the cycle, KPI selection, may seem simple, but it is a complex process intertwined with various interdependencies and calibrations with the organization’s objectives.
Establishing data reliability should start from this initial step, and involving employees as primary sources for KPI selection is an effective approach. Their valuable knowledge about the data generated from their activities enhances the reliability of the selected KPIs. Additionally, considering data availability and reliability as criteria for the selection further enhances overall data trustworthiness.
KPI documentation plays a pivotal role in ensuring reliability. Adopting a standardized documentation form establishes a solid foundation for rigorous and dependable data collection and reporting. This approach provides clear guidelines for defining KPIs, including unambiguous calculation formulas, ensuring that the collected data accurately reflects the intended purpose of each KPI.
Establishing dependable data collection
During the activation of KPIs, data reliability depends on the meticulous consideration of data sources, robust data-gathering methods, and the establishment of a strong governance structure. It is imperative to utilize trusted and verified data sources that are up-to-date, accurate, and aligned with the KPIs being measured. Accountability for KPI data should be established by clearly designating KPI owners and data custodians. Furthermore, adopting a standardized data collection process that incorporates technology-driven solutions significantly enhances accuracy.
Communicating meaningful insights
The analysis and reporting of KPIs are significant in ensuring the correct organization and communication of data to key stakeholders. Errors in data analysis have the potential to result in misleading insights, which can have negative effects on decision-making. Therefore, correctly identifying relevant KPI content and conveying meaningful insights derived from KPI data to various stakeholder groups within the organization is essential.
Continuous improvement
Finally, data reliability can be enhanced through the process of refreshing KPI documentation. This ongoing effort involves recalibrating KPIs after their initial establishment and customizing them for optimal use.
Attention is given to both the content of the KPIs and the standardization of their format. Standardizing KPI content establishes uniform guidelines and criteria for measurement and reporting, ensuring data reliability and consistency. This step refines the measurement and reporting processes, facilitating accurate and dependable data for decision-making purposes.
Monitoring KPI data reliability: The role of the Data Custodian
The Data Custodian is critical in upholding the reliability of data. They actively participate in the design of performance data collection, receipt and storage, processing, analysis, reporting, dissemination, and even archival or deletion of data. They implement measures to validate and verify the accuracy, consistency, and completeness of the data. This involves conducting regular data audits, resolving discrepancies or anomalies, and implementing data cleansing processes to ensure data integrity.
To evaluate the reliability of KPI data, the Data Custodian can monitor % KPIs with reliable data. This metric measures the number of reported KPIs that contain reliable and trustworthy content out of the total number of KPIs reported, according to smartKPIs.com.
In conclusion, to succeed in a data-driven world, organizations must prioritize data reliability along the KPI lifecycle. By implementing the strategies and practices discussed above, organizations can unlock the true potential of their performance measurement systems and empower stakeholders with reliable insights for better decision-making.
