Dashboards and performance measurements: proposal for a clear display of performance indicators

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Nelson Rojas
September 7, 2021
50
min read
Web apps
"We visualize data to harness the incredible power of our visual system to detect relationships and trends."[1]

Now, in order to determine which are the indicators that originate the progress of an organization, Parmenter [3] identified two categories of measure indicators: results and performance. Each is responsible for different performance indices. In the first case, the derived measurements are the product of more than one work team, which does not allow discriminating to determine which teams are following the course of the CSF and which are adrift, although it allows observing the combined work index. This prevents solving specific problems  since these indicators lack specificity and represent culminated events at all times, especially useful for general conclusions.

On the contrary, in the second case, the measurements provided by this type of indicator are anchored to a specific team or to a set of teams that work around a common goal, in which case, positive or not, performance is the responsibility of that team in particular. Consequently, the measurements resulting from this indicator do discriminate making it possible to address problems in real time with the specificity required.

As can be inferred, it is necessary to know how to differentiate between the variables of each one of these indicators, because if confused, performance can be measured with result variables, which will inevitably lead to a wrong conclusion about the performance of the organization. This is why it is important to know the variables measured by each of these indicators in detail.

Results indicators

According to Parmenter, these indicators are classified into two types: Performance Indicators (RI) and Key Results Indicators (KRI). In both cases, the measurements are the compendium of more than one team.

-Result Indicators (IR)

These are indices, whose objective is to measure the degree of achievement of the activities of more than one team in a wide time frame in past time and it can be monthly, quarterly, weekly, or daily. This is an overview of the activities that teams have or have not accomplished [4]. Daily or weekly sales analysis is an example of an IR variable, as multiple teams may be involved. In fact, according to Parmenter, all financial performance variables such as liquidity, liabilities, asset turnover, or profitability, among others, could be considered IR [5]. Nevertheless, these variables are not identical in all cases, because depending on the sector in which the organization is framed, these variables may differ. If we take into account Parmenter's proposal [6], in the case of the private sector, IR could include some variables such as:

  • The previous day's sales.
  • The number of initiatives implemented from the most recent customer satisfaction survey.
  • The number of initiatives planned to be implemented next month to improve punctuality.
  • The number of initiatives implemented from the personal survey.

In the case of governmental or non-profit organizations, some RI variables can be, for example:

  • The number of hospital beds used weekly.
  • The percentage of coverage of the services supported by the organization.
  • The number of people in treatment.
  • The percentage of investment covering low-income countries with a high burden of disease.

The common feature between the private and public sector variables is that they can be financial or non-financial in nature, such as customer retention and acquisition, repeat sales, or hours of training.

-Key result indicators (KRI):

Similar to IRs, these indices measure the activities carried out by many teams in the past. The difference is that they no longer measure the degree of achievement of the activities, but instead provide the organization with an overview of the progress. According to Parmenter, these indicators will only tell you whether a profit has been made or not. That is why they are of little benefit to management, and because they were past events, they do not allow corrective actions. Variables that, according to Parmenter, measure KRIs in the private sector, may include:

  • Net profit before taxes.
  • Net profit on key product lines.
  • Customer satisfaction.
  • The return on invested capital.
  • Employee satisfaction.

Parmenter also states that in the government or non-profit sector, these indices measure other types of variables such as:

  • The availability of the main services offered, for example, average waiting time for the service.
  • The punctual implementation of infrastructure projects.
  • Membership numbers (for professional organizations).

It is also clear that as IRs, these types of indicators can be financial or non-financial.


Performance indicators

As with IRs, these indicators are classified into two: performance indicators (PI) and key performance indicators (KPI).

-Performance indicators (PI):

Two differences separate them from the IRs. First, they are only non-financial indices. Second, they concern a specific team. According to Parmenter, these indices help teams align with their organization's strategy, but they are not crucial to it [7]. Similarly, following Parmenter again, within the IP variables that can be measured in the private sector, there are:

  • The abandonment rate.
  • Late deliveries to customers.
  • Planned dropouts from reports, meetings, processes that are no longer working.
  • The number of innovations implemented by each team or division.
  • Organized sales calls for the next week, two weeks, etc.
  • The number of hours of training.

As in the case of IRs, the variables in the government or non-profit sector vary, focusing on measuring other aspects that, according to Parmenter, are related to:

  • The number of media coverage events.
  • The date of the next customer focus group.
  • The date of the next research project on the client's needs and ideas.

-Key performance indicators (KPI):

They are indices that do not measure financial aspects, but critical success factors (CSF) that focus on the objectives of an organization, which in turn are derived from the mission, vision, and values. These indices determine the actions to take to correct an action. Unlike KRIs, their measurements covers hours, days or, at most, weeks and helps management to take corrective actions in real-time. The measurements of these indicators are derived from a specific group or from a set of groups that have a common goal. In this regard, Parmenter states that among the variables that KPIs measure in the private sector can be listed as: 

  • Late deliveries to key customers. 
  • The overdue project lists.
  • The number of initiatives implemented after staff satisfaction.
  • The number of innovations planned for implementation.
  • The number of dropouts.
  • Important projects awaiting decisions.
  • Complaints from key customers.
  • Key customer inquiries that have not been answered.
  • The date of the next visit to the main clients.

While in government or non-profit agencies, according to Parmenter, the KPIs could include other variables such as:

  • Emergency response time during a specified period.
  • Date of the next new service initiative.

Importance of precision in measurement indicators

From all the above, we can conclude that not all performance indices are KPIs. There are key differences that must be identified to avoid erroneous conclusions that can be the result of measuring incorrect variables. This fact is not uncommon and many organizations today use these indices in an inappropriate way, which is why Parmenter states that “it is a myth to consider all performance measurements as KPIs” since not all of them focus on CSFs. If you want to really measure the performance of an organization, it must focus on CSFs, and it is the KPIs that focus on them.

 Image I. Parmenter performance measurement indices.



A picture speaks louder than a thousand words: the power of visualizing data

When we speak of measurement we are on an abstract plane whose expression is eminently numerical. The reading of these measurements must then be mathematical, which implies a high level of conscious attention that entails processing time, even with the assistance of specialized computer programs. In contrast, new work methods require results in record time, which is why the question arises about how to manage these complex numerical expressions in the face of the immediacy of lean methodologies, for example.

It should be noted that within cognitive psychology studies, an area called preattentive processing[8] is developed, where among other aspects, the visual properties prior to attention (preattentive visualize attributes) are researched such as color, shape, movement, or spatial position [9]. It is a visual process in which information from the environment is unconsciously extracted, thus being stored in the subconscious. Due to this fact, the knowledge that arrives in this way is assimilated without conscious effort facilitateing the understanding of what, for example, is presented through a design, since visual relationships are established in fractions of a second that speed up the understanding.

If we look at the images below, we will notice that in box 1, more effort is needed to identify how many 9s are inside the box. This is because we are doing a search based on mindfulness. Now, if we do the same in box 2, the work will be done in a fraction of the time, since, being highlighted in red, the vision processes this attribute immediately, with which the color contrast is presented as a trait to emphasize items or categories.

Image 2. Contrast through the visual property of color. Taken from Wexler, S. et al. (2017).


In the case of a more complex action, such as the quantification of the frequency of appearance of each number, other attributes are required, since the contrast by colors in box 3 would still require a conscious search to group each element with a respective color. This resulting in time and effort, so to quantify it, it is more accurate to use other visual attributes such as length or position.


Image 3. Longitudinal representation of the frequency of appearance. Taken from Wexler, S. et al. (2017).


In box 4, the frequency is represented by longitudinal bars that narrow or widen according to the number of repetitions that a certain number has, indicating not only how many times the 9 appears, but that this is the third most repeated digit, all of which you can guess in seconds and at a glance.

As can be deduced from the previous images, it is difficult to establish differences between patterns or trends in a numerical sequence, but if the values are modeled by visual attributes that describe their behavior, by action of pre-attention processing, it is easier for the user`s brain to understand the behavior of a set of numbers that measure a certain phenomenon. There are approximately 12 that we can list as follows:

Image 4. Preattentive visualize attributes. Taken from Wexler, S. et al. (2017).


Our short-term memory is not designed to store much information, so pre-attention processing is an essential strategy to activate it, and graphics are an example of this, since they use visual attributes, thus helping to understand data that, by its abstract nature or its quantity, can be overwhelming. This fact is what has given rise to data visualization as a hybrid discipline between art and science.

The data dashboard

From the above, we have been able to establish that the performance indicators are expressed by complex numerical variables that need to be interpreted in record time. Thanks to the capacity for processing prior to attention, it is possible to do so through visual attributes such as color, size, length, or orientation, which activate a set of intuitive and instantaneous relationships that lead us to identify proportion, frequency, quantity, or trend of a certain phenomenon.

From the above, we have been able to establish that the performance indicators are expressed by complex numerical variables that need to be interpreted in record time. Thanks to the capacity for processing prior to attention, it is possible to do so through visual attributes such as color, size, length, or orientation, which activate a set of intuitive and instantaneous relationships that lead us to identify proportion, frequency, quantity, or trend of a certain phenomenon.

Having said that, it is possible to harmonize these dynamics in a graphic representation, whose visual attributes activate the processing prior to attention facilitating the understanding of complex variables. The question is how to integrate these graphic elements into a tool that allows all its elements to be properly managed. This tool is what in data visualization has been called data dashboard because it allows us to observe the course of one or more parameters to detect possible anomalies through special monitors. 

In its deep structure, a dashboard connects to nominal, ordinal, or numeral data files, but in the surface structure, all of this data is displayed in the form of tables, line graphs, or bar graphs to help understand specific metrics of a department or organization.

According to Durcevic [10], a dashboard could be defined as a tool that provides a centralized, interactive means of monitoring, measuring, analyzing, and extracting relevant business insight from different datasets in key areas while displaying information in an interactive, intuitive and visual way. This definition provides some essential features such as the interactive character that adds to the intuitive character and the visual attributes that intervene in this process.

Dashboards and performance indicators


Currently, there are a wide variety of ways to classify data boards; however, after studying it in detail, the classification of IDashboards [11] is quite interesting. This classification establishes four types of dashboards: Business Dashboard, Executive Dashboard, KPI Dashboard, and Project Dashboard, which seem to fit the performance indicators described by Parmenter, considering some focus on monitoring data related to KRIs, others on IRs, and many others on PIs or KPIs.


- Business Dashboard: monitors the tracking of business metrics and business intelligence initiatives, as well as operational data [12]. It is an outline that provides a view of the progress of the company over a relatively long period, bringing it closer to the characteristics of KRIs, as it is usually the product of the combined work of several teams and is based on past events which can be financial or non-financial.

-Executive Dashboard: Its function is to monitor aspects related to the administration of the organization, which measures how the teams or departments carry out their objectives, whether financial or non-financial, which brings them closer to IR.

-KPI Dashboard: This type of dashboard monitors the indicators related to the CSFs, the KPIs. It measures tangible goals and objectives for each team in real-time and it is where the real performance of the organization can be seen.

-Project Dashboard: monitors the progress and completion of a project, which implies that it tracks these factors in real-time in each work team, information that is generally directed to the project manager, characteristics that place this type of dashboard within the category of IP. According to IDashboards, "with the help of a project management dashboard, you can simply open the dashboard and see exactly where the project is, make adaptations or changes as needed, and provide an accurate assessment of when the project will be completed.” [13]

When looking for a dashboard definition, you generally think only of the KPI Dashboard and it is assumed that everyone should fit this schema. Nonetheless, the dashboard is closely related to performance indicators. We must pay close attention to this fact, because, as Parmenter expressed it, “it is a myth to consider all performance measures as KPIs”, believing it carries the usual consequences that we have pointed out previously.


The same, but not quite: the KPI myth

Dashboards allow us to visualize a large amount of information through tables, graphs, and infographics. However, as Marr states, some KPI dashboards are so full of detail that it is impossible to decipher important information [14], so in their design, it is necessary to concentrate on data that helps in decision-making, since although a software is only a "performance management enabler" [15] , it should be able to guide the user in an accurate way to establish what that data is, which is achieved through a clear classification of each of them.

The key to this, according to Marr, is "to focus on showing the main KPIs for decision making." [16] Although we partially agree, this statement infiltrates the myth that everything a dashboard displays is a KPI. The fact is that KPIs focus on critical success factors; therefore, they are essential, so that statement is rethought and we must say that a dashboard should differentiate KPIs from other performance indicators that report, but are not key. 

If you look closely, you can see that decision-makers, CEOs, or boards of directors generally need to analyze KRIs, while a head of human resources requires RIs, and a project manager requires PIs and KPIs. Certainly, all are performance indices in one way or another, but they are not the same, since each one has a specific function and receptor. The problem of this fact does not seem to be so obvious in some dashboards, in which it is difficult to determine the type of indicator that is displayed at a glance, so it would be very useful if a software allowed to establish these differences, making it possible to determine the receiver and, based on it, clearly establishing the type of performance indicator that is required: (RI, KRI, PI, KPI).

Research objective

 

It should be remembered that in his book, Parmenter warnsthat the confusion between result and performance indicators leads to a wrongconclusion of the performance, if a lack of clarity that these indicators havein a dashboard  is added, the possibility of a wrong conclusion growsexponentially.

Undoubtedly, the function of a management software should be to facilitate tasks such as performance analysis through visualization. If this maxim is not fulfilled,  we are facing a serious design problem. This fact has prompted us to carry out a case study to determine what type of performance indicators are displayed in a set of 50 dashboards belonging to various industries, and also if these indicators are clearly differentiated from each other.

Performance indicators and their display on dashboards

The theory states that two categories of indicators stand out in performance measurement: result indicators (RI, KRI) and performance indicators (PI, KPI), but from the point of view of practice, which of these indicators do the dashboards display? Furthermore, could they be classified accordingly? And if possible, how easy is it for the recipient to determine the role of each of these indicators? In this regard, what the cases analyzed during this study tell us is described below.

Business Dashboards and Executive Dashboard

As we pointed out in previous lines, the result indicators have a relevant function in these dashboards, which is corroborated in image 1, which shows a sales analysis dashboard. When detailed, it can be seen that, along the first and second row, the level of sales is represented and a map of the areas in which sales are concentrated. Said data is a very general summary that indicates only the increase or decrease in the level of sales, important information, but which, as Parmenter points out, is only an overview in past tense of goals that have been achieved or not; a trait that characterizes IR.

On the other hand, at the end of the second row, as well as in the third and fourth, a set of tables is displayed with data referring to the total income, the traffic in the networks, and the level of customer satisfaction. This data provides a global vision of the organization's progress from a financial and non-financial point of view, which suggests that this data could fit into the KRI category.

Image 1. Sales analysis  dashboard  1.[17]


Similarly, image 2 shows another sales dashboard with slight differences. Nevertheless, as in the previous case, the first and second row show the level of sales in percentage and a graph of the activity in different latitudes. All this is the summary of sales during an extended period that provides a retrospective in relation to a past period; a feature that agrees with the characteristics of the IRs.

The third and fourth rows display the results of a period that indicates the total profit, expenses, as well as the total number of visits and the number of clients with respect to the previous month. These data indicate how much the financial and non-financial aspects have progressed or decreased compared to the previous period ; a distinctive feature of the KRIs.

Finally, in the fifth row, a graph is displayed that represents the type of search that visitors carry out, an important aspect for SEO, but which only has an informative aspect, which places it within the IRs.

Image 2. Sales analysis dashboard 2. [18]


On the other hand, unlike the previous ones, image 3 shows the dashboard of a marketing campaign, where an income graph is appreciated in the first row, indicating the profit margin and total income from the campaign, financial indicators of progress which, according to Parmenter, are associated with the KRIs. Next, in the same row, an infographic is displayed detailing the number of transactions, their average value, and the estimated duration of the customers. These variables are the result of a finished period, concluding that they are RI.

In the second row of this dashboard, a graph with the campaign metrics is also displayed: impressions, clicks, and number of conversions. Secondly, another infographic that gives an account of the number of leads, conversions, the cost of the campaign, and the conversion rate, undoubtedly specific achievements of the campaign related to IRs. Finally, a graph is presented indicating the ROI, a variable that measures the financial progress of the campaign, therefore a KRI.

Image 3. Dashboard of a marketing campaign. [19]

In summary, this dynamic has been the orientation of a large part of the sample, that is, dashboards that generally focus on inspecting the monitoring of commercial metrics, operational data, and aspects related to the administration of the organization measure the performance of various teams regarding the development of their objectives and the achievement of their goals. It should be noted that due to these functions, this type of dashboard is intended for the CEO or the board of directors, and even the human resources manager, that is why they can be included in the category of Business Dashboards, and even that of Executive Dashboard, which are mainly focused on the visualization of IRs and KPIs.

Project Dashboards and KPI Dashboards

Although Business Dashboards and Executive Dashboards are the most frequent in the sample, we have been able to verify the existence of two other types that, unlike the previous ones, are characterized by mainly displaying performance indicators, so they should be within another classification. 

As can be seen, image 4 shows a dashboard similar to the previous ones, with indicators that measure results such as the level of sales, the number of conversions, the sales value per user, among others. All these indicators, as we observed in the previous dashboards, are associated with the IRs. On the other hand, it is also possible to identify what a PI could be. We refer to the abandonment rate, which, according to Parmenter, is an indicator that monitors performance. In e-commerce, the increase in this rate indicates that there is a performance problem, but it does not indicate what the cause is, so it is not as crucial as  the shipping costs of a product or the loading time of the pages that are concrete causes of abandonment may be.

Image 4. E-commerce analysis dashboard. [20]

Image 5 shows a dashboard with a similar structure. In its left column, you can see the set of IRs that summarize the achievements of the organization such as the number of orders placed, the average number of orders per customer, income, and quantity per week, orders per hour of the day, as well as the rate of deliveries on time. However, on the right, highlighted in red, there is another indicator that shows late deliveries and losses due to those delays. This is a wake-up call for teams to align themselves with the objectives that the organization has set for itself. For this reason, Parmenter defines this type of variable as PI  because, although they are not crucial, they guide teams on the path of the organization's strategies.

Image 5. Delivery analysis dashboard. [21]

Now, image 6 shows a more specific dashboard and not as regular as the previous ones. It shows the performance of a set of airlines. Before analyzing it, it should be noted that for airlines "on time and punctual delivery" [22] is a CSF and cancellation of flights is an indicator that measures the performance of this factor. All airlines must deal with it, so cancellation of flights can be considered as a KPI since it accounts for the performance of this CSF.

In the left column of this dashboard, you can see a high percentage of canceled flights per day, which is a study to determine the causes reduced to three although the weather is the most relevant as the lower graph of the center expresses. In this way, the cancellation reasons become another KPI. In turn, this leads to establishing a contrast between the flights and the departure delay, another KPI that allows determining the performance of the different airlines in the face of climatic factors. As can be seen from the graph below, these data allow us to determine which airlines perform more efficiently in the face of the weather factor causing the delays. Logically, those who cancel their flights the least will be the most successful. Due to these factors, we can classify this dashboard within the KPI Dashboards category, since all the data it displays is directly related to one of the CSFs of this type of industry.

Image 6. Airlines performance dashboard. [22]

The measurement of these dashboards generally covers hours, days or, at most, weeks and they help management to take corrective actions in real time. The measurements of these indicators are more relevant for project managers than for the CEO or the board since they are in charge of making the most appropriate corrections to guide the performance of the teams. From the data of these dashboards, the results that decision-makers require are generated. For this reason, this type of dashboard falls into the category of Project Dashboards and KPI Dashboards.

What do we see on dashboards?

From the analysis we have carried out, several aspects emerge. Firstly, not everything that is displayed in the dashboards is KPIs, as Parmenter states. In fact, in the sample, a large majority of the dashboards only display the RIs and KRIs, in a few cases the RIs and PIs, and rarely only the RIs or KPIs.

Image 7. Indicators that display the dashboards.

What is relevant about this finding is that some of these dashboards are advertised as KPI dashboards, when in fact they only visualize general results through indicators such as RI and KRI; therefore, it is not possible to do a performance analysis since these indicators only allow to know, as Parmenter says, “whether the horse took off or not”, but not if it is running well.\

Image 8. Dashboards that are advertised as KPI dashboards.

Second, in most of the sample, the arrangement of the indicators on the dashboard seems to be random, which makes it difficult to establish a hierarchy, as can be seen in image 9, from those indicators it is not possible to deduce a classification at a glance. The consequence of this dispersion is that, although thanks to pre-attention processing, it is easy to read the data from a graph, it is canceled because each element has to be grouped with its respective category to be able to determine if it is key or not. We are thus reduced to a search based on conscious attention, which implies more time and effort so that reading a graph as the one in image 9 becomes a difficult task.

Image 9. Arrangement of the indicators on the dashboard [23]

Third, it has not been possible to find a dashboard in which all the result indicators are found; on the other hand, in the cases in which the KPIs are displayed, it has been observed that these are isolated from the rest of the indicators.

Image 10. Isolated KPI Dashboard.[24]

Conclusions

This study began with a key question: what do dashboards visualize? This simple question triggered a large study in which we have had to touch on aspects as diverse as performance measurements, visualization, and the UI that characterizes Dashboards.

You might think that the answer to a question like this is given: dashboards display KPIs. However, a statement by Parmenter questioned this answer since from his point of view “it is a myth to consider all performance measures as KPIs”. This is  because there are a variety of performance indicators. So, would they be visualizing the dashboards more than the KPIs? Indeed, this is why we conclude that not all performance indices are KPIs, and there are key differences  imperative to identify to avoid misconceptions in performance analysis.

Then, the dashboards display a set of indicators that can be both results and performance. These indicators are manifested through tables, graphs, and infographics that can saturate a dashboard so much, making it impossible to differentiate between result and performance. This fact, added to the lack of clarity of the performance indicators, maximizes the possibility of generating wrong conclusions about the performance of an organization.

Now, the function of good management software should be to facilitate tasks such as performance analysis through visualization. If this maxim is not met, we are facing a serious design problem. This fact has prompted this case study to determine what type of performance indicators are displayed in a set of 50 dashboards belonging to various industries, and also if these indicators are clearly differentiated from each other. The results of this study are as follows:


1. From a theoretical point of view, it has been established that not all performance indices are KPIs. In addition, there are fundamental differences that must be identified to avoid errors produced by the measurement of incorrect indicators.

2. The indicators that measure performance are classified into:

-Outcome indicators such as IRs and KRIs.

-Performance indicators such as PIs and KPIs.

3. It was determined that a large number of dashboards in the sample focus on surveilling the monitoring of business metrics and business intelligence initiatives, as well as operational data and aspects related to the administration of an organization and the performance of teams. These traits coincide with the RI and the KRI. The recipient of these types of dashboards is the CEO or the board of directors, even the human resources manager, so they can be included in the category of Business Dashboards and Executive Dashboards.

4.In the sample, it was also possible to find a third type of dashboard that focuses on visualizing those indicators whose function is to help teams align with their organization's strategy, that is, the PIs. The content of these dashboards is more relevant for project managers than for the CEO or the board since they are in charge of making the most appropriate corrections to channel deviations. For this reason, this type of dashboard falls into the category of Project Dashboards.

5.The sample also showed the existence of a fourth type of dashboard whose data is directly related to the CSF through the KPIs, which are the indicators that really measure performance, for that reason they fall within the category of KPI Dashboards. The recipient for this type of dashboard is, mainly, the project manager.

6.Some of these dashboards are advertised as KPI dashboards when in fact they only visualize general results through indicators such as RI and KRI; therefore, it is not possible to run a performance analysis, since these indicators only allow us to know, as Parmenter says, if “ the horse took off ”.

7.The arrangement of the indicators on the dashboard appears to be random, which makes it difficult to establish a hierarchy. The consequence of this dispersion is that, although thanks to the processing prior to the attention it is easy to read the data of a graph or an infographic, this is canceled since each element must be grouped with its respective category to determine if it is key or not.

8.It has not been possible to find a dashboard in which all the result indicators are found; on the other hand, in the cases in which the KPIs are displayed, it has been observed that these are isolated from the rest of the indicators.

References

[1] Wexler, S., Shaffer J., Cotgreave A. (2017). The Big Book of DashBoarDs: Visualizing Your Data Using Real-World Business Scenarios. New Jersey, Wiley.
[2] Spitzer, D. (2001). Transforming Performance Measurement: Rethinking the Way We Measure and Drive Organizational Success. New York: AMACOM.
[3] Parmenter. D. (2015). Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. New Jersey, United States.
[4]Parmenter. D. (2015). Ibid
[5] Parmenter. D. (2015). Ibid
[6] Parmenter. D. (2015). Ibid
[7] Parmenter. D. (2015). Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. New Jersey, United States.
[8] American Psychological Association. APA Dictionary of Psychology. Recovered: https://dictionary.apa.org/preattentive-processing.
[9] Interaction Design Foundation. Preattentive Visual Properties and How to Use Them in Information Visualization. Recuperado de: https://www.interaction-design.org/literature/article/preattentive-visual-properties-and-how-to-use-them-in-information-visualization.
[10] Durcevic, S. (2020). An Introduction To Data Dashboards: Meaning, Definition & Industry Examples. Recovered: https://www.datapine.com/blog/data-dashboards-definition-examples-templates/.
[11] IDashboards. (2020). What is a Dashboard?. Recovered: https://www.idashboards.com/guides/what-is-a-dashboard/.
[12] IDashboards. (2020). Ibid
[13] IDashboards. (2020). Ibid
[14] Marr, B . What Is A KPI Dashboard - And How Do You Create The Best One For Your Business?. Recovered: https://www.bernardmarr.com/default.asp?contentID=1344.
[15]Marr, B . Ibid
[16]Marr, B . Ibid
[17] Recovered: https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[18] Recovered: Ibid https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[19] Recovered:  https://marketplace.clicdata.com/v/7e5yFi2rLRqc 
[20]Recovered:  https://marketplace.clicdata.com/v/7e5yFi2rLRqc
[21] Recovered: https://www.akveo.com/blog/how-insights-delivery-dashboard-can-assist-your-business
[22] Parmenter. D. (2015). Ibid
[23] Sisence Recovered: https://trial.sisense.com/app/main#/dashboards/5b50010804f55e804a01bc37
[24] Recovered: https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[25] Sisence Recovered: https://trial.sisense.com/app/main#/dashboards/5b50010804f55e804a01bc37
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Illustration by
Daniel Rojas
Web apps

Dashboards and performance measurements: proposal for a clear display of performance indicators

September 15, 2021
By 
Nelson Rojas
"We visualize data to harness the incredible power of our visual system to detect relationships and trends."[1]

Now, in order to determine which are the indicators that originate the progress of an organization, Parmenter [3] identified two categories of measure indicators: results and performance. Each is responsible for different performance indices. In the first case, the derived measurements are the product of more than one work team, which does not allow discriminating to determine which teams are following the course of the CSF and which are adrift, although it allows observing the combined work index. This prevents solving specific problems  since these indicators lack specificity and represent culminated events at all times, especially useful for general conclusions.

On the contrary, in the second case, the measurements provided by this type of indicator are anchored to a specific team or to a set of teams that work around a common goal, in which case, positive or not, performance is the responsibility of that team in particular. Consequently, the measurements resulting from this indicator do discriminate making it possible to address problems in real time with the specificity required.

As can be inferred, it is necessary to know how to differentiate between the variables of each one of these indicators, because if confused, performance can be measured with result variables, which will inevitably lead to a wrong conclusion about the performance of the organization. This is why it is important to know the variables measured by each of these indicators in detail.

Results indicators

According to Parmenter, these indicators are classified into two types: Performance Indicators (RI) and Key Results Indicators (KRI). In both cases, the measurements are the compendium of more than one team.

-Result Indicators (IR)

These are indices, whose objective is to measure the degree of achievement of the activities of more than one team in a wide time frame in past time and it can be monthly, quarterly, weekly, or daily. This is an overview of the activities that teams have or have not accomplished [4]. Daily or weekly sales analysis is an example of an IR variable, as multiple teams may be involved. In fact, according to Parmenter, all financial performance variables such as liquidity, liabilities, asset turnover, or profitability, among others, could be considered IR [5]. Nevertheless, these variables are not identical in all cases, because depending on the sector in which the organization is framed, these variables may differ. If we take into account Parmenter's proposal [6], in the case of the private sector, IR could include some variables such as:

  • The previous day's sales.
  • The number of initiatives implemented from the most recent customer satisfaction survey.
  • The number of initiatives planned to be implemented next month to improve punctuality.
  • The number of initiatives implemented from the personal survey.

In the case of governmental or non-profit organizations, some RI variables can be, for example:

  • The number of hospital beds used weekly.
  • The percentage of coverage of the services supported by the organization.
  • The number of people in treatment.
  • The percentage of investment covering low-income countries with a high burden of disease.

The common feature between the private and public sector variables is that they can be financial or non-financial in nature, such as customer retention and acquisition, repeat sales, or hours of training.

-Key result indicators (KRI):

Similar to IRs, these indices measure the activities carried out by many teams in the past. The difference is that they no longer measure the degree of achievement of the activities, but instead provide the organization with an overview of the progress. According to Parmenter, these indicators will only tell you whether a profit has been made or not. That is why they are of little benefit to management, and because they were past events, they do not allow corrective actions. Variables that, according to Parmenter, measure KRIs in the private sector, may include:

  • Net profit before taxes.
  • Net profit on key product lines.
  • Customer satisfaction.
  • The return on invested capital.
  • Employee satisfaction.

Parmenter also states that in the government or non-profit sector, these indices measure other types of variables such as:

  • The availability of the main services offered, for example, average waiting time for the service.
  • The punctual implementation of infrastructure projects.
  • Membership numbers (for professional organizations).

It is also clear that as IRs, these types of indicators can be financial or non-financial.


Performance indicators

As with IRs, these indicators are classified into two: performance indicators (PI) and key performance indicators (KPI).

-Performance indicators (PI):

Two differences separate them from the IRs. First, they are only non-financial indices. Second, they concern a specific team. According to Parmenter, these indices help teams align with their organization's strategy, but they are not crucial to it [7]. Similarly, following Parmenter again, within the IP variables that can be measured in the private sector, there are:

  • The abandonment rate.
  • Late deliveries to customers.
  • Planned dropouts from reports, meetings, processes that are no longer working.
  • The number of innovations implemented by each team or division.
  • Organized sales calls for the next week, two weeks, etc.
  • The number of hours of training.

As in the case of IRs, the variables in the government or non-profit sector vary, focusing on measuring other aspects that, according to Parmenter, are related to:

  • The number of media coverage events.
  • The date of the next customer focus group.
  • The date of the next research project on the client's needs and ideas.

-Key performance indicators (KPI):

They are indices that do not measure financial aspects, but critical success factors (CSF) that focus on the objectives of an organization, which in turn are derived from the mission, vision, and values. These indices determine the actions to take to correct an action. Unlike KRIs, their measurements covers hours, days or, at most, weeks and helps management to take corrective actions in real-time. The measurements of these indicators are derived from a specific group or from a set of groups that have a common goal. In this regard, Parmenter states that among the variables that KPIs measure in the private sector can be listed as: 

  • Late deliveries to key customers. 
  • The overdue project lists.
  • The number of initiatives implemented after staff satisfaction.
  • The number of innovations planned for implementation.
  • The number of dropouts.
  • Important projects awaiting decisions.
  • Complaints from key customers.
  • Key customer inquiries that have not been answered.
  • The date of the next visit to the main clients.

While in government or non-profit agencies, according to Parmenter, the KPIs could include other variables such as:

  • Emergency response time during a specified period.
  • Date of the next new service initiative.

Importance of precision in measurement indicators

From all the above, we can conclude that not all performance indices are KPIs. There are key differences that must be identified to avoid erroneous conclusions that can be the result of measuring incorrect variables. This fact is not uncommon and many organizations today use these indices in an inappropriate way, which is why Parmenter states that “it is a myth to consider all performance measurements as KPIs” since not all of them focus on CSFs. If you want to really measure the performance of an organization, it must focus on CSFs, and it is the KPIs that focus on them.

 Image I. Parmenter performance measurement indices.



A picture speaks louder than a thousand words: the power of visualizing data

When we speak of measurement we are on an abstract plane whose expression is eminently numerical. The reading of these measurements must then be mathematical, which implies a high level of conscious attention that entails processing time, even with the assistance of specialized computer programs. In contrast, new work methods require results in record time, which is why the question arises about how to manage these complex numerical expressions in the face of the immediacy of lean methodologies, for example.

It should be noted that within cognitive psychology studies, an area called preattentive processing[8] is developed, where among other aspects, the visual properties prior to attention (preattentive visualize attributes) are researched such as color, shape, movement, or spatial position [9]. It is a visual process in which information from the environment is unconsciously extracted, thus being stored in the subconscious. Due to this fact, the knowledge that arrives in this way is assimilated without conscious effort facilitateing the understanding of what, for example, is presented through a design, since visual relationships are established in fractions of a second that speed up the understanding.

If we look at the images below, we will notice that in box 1, more effort is needed to identify how many 9s are inside the box. This is because we are doing a search based on mindfulness. Now, if we do the same in box 2, the work will be done in a fraction of the time, since, being highlighted in red, the vision processes this attribute immediately, with which the color contrast is presented as a trait to emphasize items or categories.

Image 2. Contrast through the visual property of color. Taken from Wexler, S. et al. (2017).


In the case of a more complex action, such as the quantification of the frequency of appearance of each number, other attributes are required, since the contrast by colors in box 3 would still require a conscious search to group each element with a respective color. This resulting in time and effort, so to quantify it, it is more accurate to use other visual attributes such as length or position.


Image 3. Longitudinal representation of the frequency of appearance. Taken from Wexler, S. et al. (2017).


In box 4, the frequency is represented by longitudinal bars that narrow or widen according to the number of repetitions that a certain number has, indicating not only how many times the 9 appears, but that this is the third most repeated digit, all of which you can guess in seconds and at a glance.

As can be deduced from the previous images, it is difficult to establish differences between patterns or trends in a numerical sequence, but if the values are modeled by visual attributes that describe their behavior, by action of pre-attention processing, it is easier for the user`s brain to understand the behavior of a set of numbers that measure a certain phenomenon. There are approximately 12 that we can list as follows:

Image 4. Preattentive visualize attributes. Taken from Wexler, S. et al. (2017).


Our short-term memory is not designed to store much information, so pre-attention processing is an essential strategy to activate it, and graphics are an example of this, since they use visual attributes, thus helping to understand data that, by its abstract nature or its quantity, can be overwhelming. This fact is what has given rise to data visualization as a hybrid discipline between art and science.

The data dashboard

From the above, we have been able to establish that the performance indicators are expressed by complex numerical variables that need to be interpreted in record time. Thanks to the capacity for processing prior to attention, it is possible to do so through visual attributes such as color, size, length, or orientation, which activate a set of intuitive and instantaneous relationships that lead us to identify proportion, frequency, quantity, or trend of a certain phenomenon.

From the above, we have been able to establish that the performance indicators are expressed by complex numerical variables that need to be interpreted in record time. Thanks to the capacity for processing prior to attention, it is possible to do so through visual attributes such as color, size, length, or orientation, which activate a set of intuitive and instantaneous relationships that lead us to identify proportion, frequency, quantity, or trend of a certain phenomenon.

Having said that, it is possible to harmonize these dynamics in a graphic representation, whose visual attributes activate the processing prior to attention facilitating the understanding of complex variables. The question is how to integrate these graphic elements into a tool that allows all its elements to be properly managed. This tool is what in data visualization has been called data dashboard because it allows us to observe the course of one or more parameters to detect possible anomalies through special monitors. 

In its deep structure, a dashboard connects to nominal, ordinal, or numeral data files, but in the surface structure, all of this data is displayed in the form of tables, line graphs, or bar graphs to help understand specific metrics of a department or organization.

According to Durcevic [10], a dashboard could be defined as a tool that provides a centralized, interactive means of monitoring, measuring, analyzing, and extracting relevant business insight from different datasets in key areas while displaying information in an interactive, intuitive and visual way. This definition provides some essential features such as the interactive character that adds to the intuitive character and the visual attributes that intervene in this process.

Dashboards and performance indicators


Currently, there are a wide variety of ways to classify data boards; however, after studying it in detail, the classification of IDashboards [11] is quite interesting. This classification establishes four types of dashboards: Business Dashboard, Executive Dashboard, KPI Dashboard, and Project Dashboard, which seem to fit the performance indicators described by Parmenter, considering some focus on monitoring data related to KRIs, others on IRs, and many others on PIs or KPIs.


- Business Dashboard: monitors the tracking of business metrics and business intelligence initiatives, as well as operational data [12]. It is an outline that provides a view of the progress of the company over a relatively long period, bringing it closer to the characteristics of KRIs, as it is usually the product of the combined work of several teams and is based on past events which can be financial or non-financial.

-Executive Dashboard: Its function is to monitor aspects related to the administration of the organization, which measures how the teams or departments carry out their objectives, whether financial or non-financial, which brings them closer to IR.

-KPI Dashboard: This type of dashboard monitors the indicators related to the CSFs, the KPIs. It measures tangible goals and objectives for each team in real-time and it is where the real performance of the organization can be seen.

-Project Dashboard: monitors the progress and completion of a project, which implies that it tracks these factors in real-time in each work team, information that is generally directed to the project manager, characteristics that place this type of dashboard within the category of IP. According to IDashboards, "with the help of a project management dashboard, you can simply open the dashboard and see exactly where the project is, make adaptations or changes as needed, and provide an accurate assessment of when the project will be completed.” [13]

When looking for a dashboard definition, you generally think only of the KPI Dashboard and it is assumed that everyone should fit this schema. Nonetheless, the dashboard is closely related to performance indicators. We must pay close attention to this fact, because, as Parmenter expressed it, “it is a myth to consider all performance measures as KPIs”, believing it carries the usual consequences that we have pointed out previously.


The same, but not quite: the KPI myth

Dashboards allow us to visualize a large amount of information through tables, graphs, and infographics. However, as Marr states, some KPI dashboards are so full of detail that it is impossible to decipher important information [14], so in their design, it is necessary to concentrate on data that helps in decision-making, since although a software is only a "performance management enabler" [15] , it should be able to guide the user in an accurate way to establish what that data is, which is achieved through a clear classification of each of them.

The key to this, according to Marr, is "to focus on showing the main KPIs for decision making." [16] Although we partially agree, this statement infiltrates the myth that everything a dashboard displays is a KPI. The fact is that KPIs focus on critical success factors; therefore, they are essential, so that statement is rethought and we must say that a dashboard should differentiate KPIs from other performance indicators that report, but are not key. 

If you look closely, you can see that decision-makers, CEOs, or boards of directors generally need to analyze KRIs, while a head of human resources requires RIs, and a project manager requires PIs and KPIs. Certainly, all are performance indices in one way or another, but they are not the same, since each one has a specific function and receptor. The problem of this fact does not seem to be so obvious in some dashboards, in which it is difficult to determine the type of indicator that is displayed at a glance, so it would be very useful if a software allowed to establish these differences, making it possible to determine the receiver and, based on it, clearly establishing the type of performance indicator that is required: (RI, KRI, PI, KPI).

Research objective

 

It should be remembered that in his book, Parmenter warnsthat the confusion between result and performance indicators leads to a wrongconclusion of the performance, if a lack of clarity that these indicators havein a dashboard  is added, the possibility of a wrong conclusion growsexponentially.

Undoubtedly, the function of a management software should be to facilitate tasks such as performance analysis through visualization. If this maxim is not fulfilled,  we are facing a serious design problem. This fact has prompted us to carry out a case study to determine what type of performance indicators are displayed in a set of 50 dashboards belonging to various industries, and also if these indicators are clearly differentiated from each other.

Performance indicators and their display on dashboards

The theory states that two categories of indicators stand out in performance measurement: result indicators (RI, KRI) and performance indicators (PI, KPI), but from the point of view of practice, which of these indicators do the dashboards display? Furthermore, could they be classified accordingly? And if possible, how easy is it for the recipient to determine the role of each of these indicators? In this regard, what the cases analyzed during this study tell us is described below.

Business Dashboards and Executive Dashboard

As we pointed out in previous lines, the result indicators have a relevant function in these dashboards, which is corroborated in image 1, which shows a sales analysis dashboard. When detailed, it can be seen that, along the first and second row, the level of sales is represented and a map of the areas in which sales are concentrated. Said data is a very general summary that indicates only the increase or decrease in the level of sales, important information, but which, as Parmenter points out, is only an overview in past tense of goals that have been achieved or not; a trait that characterizes IR.

On the other hand, at the end of the second row, as well as in the third and fourth, a set of tables is displayed with data referring to the total income, the traffic in the networks, and the level of customer satisfaction. This data provides a global vision of the organization's progress from a financial and non-financial point of view, which suggests that this data could fit into the KRI category.

Image 1. Sales analysis  dashboard  1.[17]


Similarly, image 2 shows another sales dashboard with slight differences. Nevertheless, as in the previous case, the first and second row show the level of sales in percentage and a graph of the activity in different latitudes. All this is the summary of sales during an extended period that provides a retrospective in relation to a past period; a feature that agrees with the characteristics of the IRs.

The third and fourth rows display the results of a period that indicates the total profit, expenses, as well as the total number of visits and the number of clients with respect to the previous month. These data indicate how much the financial and non-financial aspects have progressed or decreased compared to the previous period ; a distinctive feature of the KRIs.

Finally, in the fifth row, a graph is displayed that represents the type of search that visitors carry out, an important aspect for SEO, but which only has an informative aspect, which places it within the IRs.

Image 2. Sales analysis dashboard 2. [18]


On the other hand, unlike the previous ones, image 3 shows the dashboard of a marketing campaign, where an income graph is appreciated in the first row, indicating the profit margin and total income from the campaign, financial indicators of progress which, according to Parmenter, are associated with the KRIs. Next, in the same row, an infographic is displayed detailing the number of transactions, their average value, and the estimated duration of the customers. These variables are the result of a finished period, concluding that they are RI.

In the second row of this dashboard, a graph with the campaign metrics is also displayed: impressions, clicks, and number of conversions. Secondly, another infographic that gives an account of the number of leads, conversions, the cost of the campaign, and the conversion rate, undoubtedly specific achievements of the campaign related to IRs. Finally, a graph is presented indicating the ROI, a variable that measures the financial progress of the campaign, therefore a KRI.

Image 3. Dashboard of a marketing campaign. [19]

In summary, this dynamic has been the orientation of a large part of the sample, that is, dashboards that generally focus on inspecting the monitoring of commercial metrics, operational data, and aspects related to the administration of the organization measure the performance of various teams regarding the development of their objectives and the achievement of their goals. It should be noted that due to these functions, this type of dashboard is intended for the CEO or the board of directors, and even the human resources manager, that is why they can be included in the category of Business Dashboards, and even that of Executive Dashboard, which are mainly focused on the visualization of IRs and KPIs.

Project Dashboards and KPI Dashboards

Although Business Dashboards and Executive Dashboards are the most frequent in the sample, we have been able to verify the existence of two other types that, unlike the previous ones, are characterized by mainly displaying performance indicators, so they should be within another classification. 

As can be seen, image 4 shows a dashboard similar to the previous ones, with indicators that measure results such as the level of sales, the number of conversions, the sales value per user, among others. All these indicators, as we observed in the previous dashboards, are associated with the IRs. On the other hand, it is also possible to identify what a PI could be. We refer to the abandonment rate, which, according to Parmenter, is an indicator that monitors performance. In e-commerce, the increase in this rate indicates that there is a performance problem, but it does not indicate what the cause is, so it is not as crucial as  the shipping costs of a product or the loading time of the pages that are concrete causes of abandonment may be.

Image 4. E-commerce analysis dashboard. [20]

Image 5 shows a dashboard with a similar structure. In its left column, you can see the set of IRs that summarize the achievements of the organization such as the number of orders placed, the average number of orders per customer, income, and quantity per week, orders per hour of the day, as well as the rate of deliveries on time. However, on the right, highlighted in red, there is another indicator that shows late deliveries and losses due to those delays. This is a wake-up call for teams to align themselves with the objectives that the organization has set for itself. For this reason, Parmenter defines this type of variable as PI  because, although they are not crucial, they guide teams on the path of the organization's strategies.

Image 5. Delivery analysis dashboard. [21]

Now, image 6 shows a more specific dashboard and not as regular as the previous ones. It shows the performance of a set of airlines. Before analyzing it, it should be noted that for airlines "on time and punctual delivery" [22] is a CSF and cancellation of flights is an indicator that measures the performance of this factor. All airlines must deal with it, so cancellation of flights can be considered as a KPI since it accounts for the performance of this CSF.

In the left column of this dashboard, you can see a high percentage of canceled flights per day, which is a study to determine the causes reduced to three although the weather is the most relevant as the lower graph of the center expresses. In this way, the cancellation reasons become another KPI. In turn, this leads to establishing a contrast between the flights and the departure delay, another KPI that allows determining the performance of the different airlines in the face of climatic factors. As can be seen from the graph below, these data allow us to determine which airlines perform more efficiently in the face of the weather factor causing the delays. Logically, those who cancel their flights the least will be the most successful. Due to these factors, we can classify this dashboard within the KPI Dashboards category, since all the data it displays is directly related to one of the CSFs of this type of industry.

Image 6. Airlines performance dashboard. [22]

The measurement of these dashboards generally covers hours, days or, at most, weeks and they help management to take corrective actions in real time. The measurements of these indicators are more relevant for project managers than for the CEO or the board since they are in charge of making the most appropriate corrections to guide the performance of the teams. From the data of these dashboards, the results that decision-makers require are generated. For this reason, this type of dashboard falls into the category of Project Dashboards and KPI Dashboards.

What do we see on dashboards?

From the analysis we have carried out, several aspects emerge. Firstly, not everything that is displayed in the dashboards is KPIs, as Parmenter states. In fact, in the sample, a large majority of the dashboards only display the RIs and KRIs, in a few cases the RIs and PIs, and rarely only the RIs or KPIs.

Image 7. Indicators that display the dashboards.

What is relevant about this finding is that some of these dashboards are advertised as KPI dashboards, when in fact they only visualize general results through indicators such as RI and KRI; therefore, it is not possible to do a performance analysis since these indicators only allow to know, as Parmenter says, “whether the horse took off or not”, but not if it is running well.\

Image 8. Dashboards that are advertised as KPI dashboards.

Second, in most of the sample, the arrangement of the indicators on the dashboard seems to be random, which makes it difficult to establish a hierarchy, as can be seen in image 9, from those indicators it is not possible to deduce a classification at a glance. The consequence of this dispersion is that, although thanks to pre-attention processing, it is easy to read the data from a graph, it is canceled because each element has to be grouped with its respective category to be able to determine if it is key or not. We are thus reduced to a search based on conscious attention, which implies more time and effort so that reading a graph as the one in image 9 becomes a difficult task.

Image 9. Arrangement of the indicators on the dashboard [23]

Third, it has not been possible to find a dashboard in which all the result indicators are found; on the other hand, in the cases in which the KPIs are displayed, it has been observed that these are isolated from the rest of the indicators.

Image 10. Isolated KPI Dashboard.[24]

Conclusions

This study began with a key question: what do dashboards visualize? This simple question triggered a large study in which we have had to touch on aspects as diverse as performance measurements, visualization, and the UI that characterizes Dashboards.

You might think that the answer to a question like this is given: dashboards display KPIs. However, a statement by Parmenter questioned this answer since from his point of view “it is a myth to consider all performance measures as KPIs”. This is  because there are a variety of performance indicators. So, would they be visualizing the dashboards more than the KPIs? Indeed, this is why we conclude that not all performance indices are KPIs, and there are key differences  imperative to identify to avoid misconceptions in performance analysis.

Then, the dashboards display a set of indicators that can be both results and performance. These indicators are manifested through tables, graphs, and infographics that can saturate a dashboard so much, making it impossible to differentiate between result and performance. This fact, added to the lack of clarity of the performance indicators, maximizes the possibility of generating wrong conclusions about the performance of an organization.

Now, the function of good management software should be to facilitate tasks such as performance analysis through visualization. If this maxim is not met, we are facing a serious design problem. This fact has prompted this case study to determine what type of performance indicators are displayed in a set of 50 dashboards belonging to various industries, and also if these indicators are clearly differentiated from each other. The results of this study are as follows:


1. From a theoretical point of view, it has been established that not all performance indices are KPIs. In addition, there are fundamental differences that must be identified to avoid errors produced by the measurement of incorrect indicators.

2. The indicators that measure performance are classified into:

-Outcome indicators such as IRs and KRIs.

-Performance indicators such as PIs and KPIs.

3. It was determined that a large number of dashboards in the sample focus on surveilling the monitoring of business metrics and business intelligence initiatives, as well as operational data and aspects related to the administration of an organization and the performance of teams. These traits coincide with the RI and the KRI. The recipient of these types of dashboards is the CEO or the board of directors, even the human resources manager, so they can be included in the category of Business Dashboards and Executive Dashboards.

4.In the sample, it was also possible to find a third type of dashboard that focuses on visualizing those indicators whose function is to help teams align with their organization's strategy, that is, the PIs. The content of these dashboards is more relevant for project managers than for the CEO or the board since they are in charge of making the most appropriate corrections to channel deviations. For this reason, this type of dashboard falls into the category of Project Dashboards.

5.The sample also showed the existence of a fourth type of dashboard whose data is directly related to the CSF through the KPIs, which are the indicators that really measure performance, for that reason they fall within the category of KPI Dashboards. The recipient for this type of dashboard is, mainly, the project manager.

6.Some of these dashboards are advertised as KPI dashboards when in fact they only visualize general results through indicators such as RI and KRI; therefore, it is not possible to run a performance analysis, since these indicators only allow us to know, as Parmenter says, if “ the horse took off ”.

7.The arrangement of the indicators on the dashboard appears to be random, which makes it difficult to establish a hierarchy. The consequence of this dispersion is that, although thanks to the processing prior to the attention it is easy to read the data of a graph or an infographic, this is canceled since each element must be grouped with its respective category to determine if it is key or not.

8.It has not been possible to find a dashboard in which all the result indicators are found; on the other hand, in the cases in which the KPIs are displayed, it has been observed that these are isolated from the rest of the indicators.

References

[1] Wexler, S., Shaffer J., Cotgreave A. (2017). The Big Book of DashBoarDs: Visualizing Your Data Using Real-World Business Scenarios. New Jersey, Wiley.
[2] Spitzer, D. (2001). Transforming Performance Measurement: Rethinking the Way We Measure and Drive Organizational Success. New York: AMACOM.
[3] Parmenter. D. (2015). Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. New Jersey, United States.
[4]Parmenter. D. (2015). Ibid
[5] Parmenter. D. (2015). Ibid
[6] Parmenter. D. (2015). Ibid
[7] Parmenter. D. (2015). Key Performance Indicators: Developing, Implementing, and Using Winning KPIs. New Jersey, United States.
[8] American Psychological Association. APA Dictionary of Psychology. Recovered: https://dictionary.apa.org/preattentive-processing.
[9] Interaction Design Foundation. Preattentive Visual Properties and How to Use Them in Information Visualization. Recuperado de: https://www.interaction-design.org/literature/article/preattentive-visual-properties-and-how-to-use-them-in-information-visualization.
[10] Durcevic, S. (2020). An Introduction To Data Dashboards: Meaning, Definition & Industry Examples. Recovered: https://www.datapine.com/blog/data-dashboards-definition-examples-templates/.
[11] IDashboards. (2020). What is a Dashboard?. Recovered: https://www.idashboards.com/guides/what-is-a-dashboard/.
[12] IDashboards. (2020). Ibid
[13] IDashboards. (2020). Ibid
[14] Marr, B . What Is A KPI Dashboard - And How Do You Create The Best One For Your Business?. Recovered: https://www.bernardmarr.com/default.asp?contentID=1344.
[15]Marr, B . Ibid
[16]Marr, B . Ibid
[17] Recovered: https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[18] Recovered: Ibid https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[19] Recovered:  https://marketplace.clicdata.com/v/7e5yFi2rLRqc 
[20]Recovered:  https://marketplace.clicdata.com/v/7e5yFi2rLRqc
[21] Recovered: https://www.akveo.com/blog/how-insights-delivery-dashboard-can-assist-your-business
[22] Parmenter. D. (2015). Ibid
[23] Sisence Recovered: https://trial.sisense.com/app/main#/dashboards/5b50010804f55e804a01bc37
[24] Recovered: https://www.responsivemiracle.com/best-responsive-html5-dashboard-template/
[25] Sisence Recovered: https://trial.sisense.com/app/main#/dashboards/5b50010804f55e804a01bc37

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Written by
Nelson Rojas
Researcher
Translation by
Diana Morales
Illustration by
Daniel Rojas

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