A Personal DEI Scorecard

An example of a personal DEI scorecard is shown in Table 5.1 using the same elements as the personal DEI strategic plan in the previous step. In addition to capturing objectives, goals, strategies, and measures, it also tracks the baseline from Step 1: Inventory (assessment), the target from Step 2: Imperatives, and the actual results you have achieved after you leveraged Step 3: Insights to inform and implement the strategies from Step 4: Initiatives. The score is a measure of your performance ranging from 0 (poor performance) to 100 (excellent performance) in achieving your target. It is simply calculated as follows:

The total score represents the average across all scores.

An Organizational DEI Scorecard

An example of an organizational DEI scorecard can be found in Table 5.2 using the same elements as a portion of the organizational DEI strategic plan in the previous step. In identical fashion to the personal DEI scorecard, it captures objectives, goals, strategies, and measures; baseline, target, and actual figures; a score and a total score.

A Personal DEI Dashboard

An example of a personal DEI dashboard is shown in Figures 5.1 through Figures 5.8. There are several mobile apps that allow you to track activities that could be used to develop a personal DEI dashboard including nTask, Strides, Coach.me, Way of Life, ATracker, Habitica, Toodledo, Timelines, and Goals on Track.¹ The examples provided herein were developed using Strides based on the personal DEI strategic plan previously shown in Table 4.7. As you can see from the figures, the app allows you to enter your DEI strategies and measures as daily goals (Figure 5.1), maintain daily journal entries of progress toward goals (Figure 5.2) with associated notes (Figure 5.3), track and visualize your progress for tasks (Figure 5.4), break tasks into subtasks (Figure 5.5) with associated notes (Figure 5.6), track and visualize your progress for subtasks (Figure 5.7), and receive positive encouragement (Figure 5.8).

An Organizational DEI Dashboard

Examples of an organizational DEI dashboard can be found in Figures 5.9 through 5.11. These dashboards are meant to be illustrative, not exhaustive, and depict DEI minimum viable metrics (MVMs) and KPIs—a core set of essential DEI metrics that every organization should consider tracking (with organizational and/or industry comparators, if available):

• DEI Strategic Plan Scorecard—A scorecard representing the current status of the DEI strategic plan's objectives, goals, strategies, and measures with the ability to drill down. By tracking this data, you can effectively gauge progress, determine impact, engender accountability, evaluate results, and generate findings to comprehensively demonstrate DEI outputs and outcomes. The scorecard is depicted on the left‐hand side of Figure 5.9, while the drill‐down for Objective #2 is depicted on the right‐hand side of Figure 5.9.
• Workforce: Diversity (Representation)—Disaggregated representation data by demographics and management status. By tracking diversity data, you can effectively monitor how representative your workforce is overall and benchmark it against the general population, your industry, departments and divisions, and the geographies where you have offices, do business, and/or deliver products/programs/services. This representation is depicted in the upper left‐hand corner of Figure 5.10 while the benchmarking is depicted in the lower left‐hand corner of Figure 5.10.
• Workplace: Inclusion Index—A composite index or measure of inclusion and/or belonging or some related measure disaggregated by demographics. By tracking an inclusion and/or belonging index, you can effectively monitor how people are experiencing your organizational culture and climate as a leading indicator. This is depicted in the lower right‐hand corner of Figure 5.10.

  

  

  

• Workplace: Equity (Internal)—Rates of change across hiring, promotions, retention/separations (including voluntary and involuntary losses), and complaints disaggregated by demographics. By tracking these rates of change you can effectively monitor equity or inequity across the entire human resources (HR) lifecycle as a leading indicator. This is depicted in the upper right‐hand corner of Figure 5.10.
• Marketplace: Equity (External)—A composite index or measure of customer or stakeholder satisfaction and/or outcomes disaggregated by demographics. One popular and simple measure is the Net Promoter Score (NPS), which asks respondents to rate their answer to the question, “On a scale of 0 to 10, how likely are you to recommend our organization/product/service to a friend or colleague?” By tracking NPS, or something comparable, you can effectively monitor how equitably you are meeting the needs of your customers or stakeholders as a leading indicator. This is depicted on the left‐hand side of Figure 5.11.
• Community—A measure of community diversity, inclusiveness, well‐being, and equity for office locations and other geographies of particular interest including partner communities for social and economic investment including recruiting, hiring, philanthropy, corporate social responsibility (CSR), environmental sustainability, supplier diversity, and the like. By tracking these indicators, you can pinpoint areas that can most benefit from social and economic investment. This is depicted on the right‐hand side of Figure 5.11, which also represents an image from BCT's Equitable Impact Platform™ (EquIP™), which was previously cited as a “What Works” model for organizations and is highlighted again in the conclusion.

Visualizing Data

The following are tips—adapted from the National Equity Atlas, produced by PolicyLink and the University of Southern California (USC) Equity Research Institute (ERI)—for visualizing data and creating effective scorecards and dashboards with deeply disaggregated data to power your DEI reporting.²

Steps to creating a scorecard or dashboard:

1. Decide what story you are trying to tell with the data and what next steps you hope the audience will take to advance the DEI journey.
2. Choose your mix of quantitative and qualitative data visualizations based on the key DEI issues of your DEI journey.
3. Create great data displays using best practices.
4. Review your data visualizations and narrative to make sure they tell a cohesive story.

Decide What Story You Are Trying to Tell with the Data

DEI scorecards and dashboards should tell a clear story about you and/or your organization, highlighting what the issues are, why they matter, and how others can take action to make meaningful progress on DEI. We will discuss DEI storytelling in great length later in this step but, in the context of scorecards and dashboards, when displaying data, you should be able to answer:

1. What does the data show?
2. Why does it matter?
3. What are the solutions?

These three basic guiding questions can also help you in designing your scorecard or dashboard. Each element of your data visual should support your articulation of those three questions, and focusing on the goal of your data visual can also help you eliminate unneeded components that may be taking up valuable space or distracting your audience.

Choose Your Mix of Quantitative and Qualitative Data Visualizations

There are a wide variety of data visual types you can choose from. Below are some of the quantitative and qualitative data visual types for displaying disaggregated data for DEI scorecards and dashboards, based on the comparisons you want to highlight in the data.

Visualizing Quantitative Data

Among options for visualizing quantitative data are bar charts, column charts, grouped bar charts, trend lines, dot plot graphics, and maps. Table 5.3 provides guidance on how to choose a chart type and examples are provided thereafter.

Comparing between a Few Groups

For example: Compare differences by race and ethnicity

Consider using: Bar Chart

As shown in Figure 5.12, bar charts are useful for showing categorical data, such as data by race or by gender, where you are showing comparison between groups. A horizontal bar chart makes it easy for viewers to compare between bars to recognize which bars are longer and which are shorter. Vertical gridlines provide a quick reference to estimating length and comparing differences, and labels provide exact percentages or numbers, which are particularly useful when comparing between groups with smaller differences.

Comparing between Many Groups

For example: Compare units, departments, divisions, or locations

Consider using: Column Chart

As shown in Figure 5.13, column charts are vertical bar charts, and are also useful for comparison between groups, particularly when there are more than seven categories. They are also useful for illustrating ranking across many groups, such as helping users to identify how their city or state compares with other cities and states.

If you'd like to:	For example:	Consider using:
Compare between a few groups	Compare differences by race and ethnicity	Bar chart
Compare between many groups	Compare units, departments, divisions, or locations	Column chart
Compare between groups and subgroups	Compare differences between groups by race and gender	Grouped bar chart
Show gaps and change over time	Show different rates over time by management status	Trend line
Show clusters and gaps between groups over time	Show distribution between equity scores for different years	Dot plot graph
Display and compare geographically related	Compare differences between and across office locations	Map

Note that the labels for the categories can be displayed at an angle to maximize space.

Comparing between Groups and Subgroups

For example: Compare differences between groups by race and gender

Consider using: Grouped Bar Chart

As shown in Figure 5.14, grouped bar charts allow you to include additional subcategories in your comparison, for example, when you are showing differences between groups by race and gender. Grouping the bars together shows rates by race/ethnicity, while using two different colors for gender allows viewers to also compare each gender across racial groups.

Show Gaps and Change Over Time

For example: Show different rates over time by management status

Consider using: Trend Lines

As shown in Figure 5.15, trend lines are a useful way to illustrate change over time. Using markers can help users identify key points on your chart, and using different colors for each line makes it visually clear for comparison between different groups represented.

Show Clusters and Gaps between Groups over Time

For example: Show distribution between equity scores for different years

Consider using: Dot Plot Graph

As shown in Figure 5.16, dot plots are useful for showing distribution comparison between categories, and also show patterns of that distribution. They are efficient for when comparing between groups. One way to highlight differences between multiple groups and to bring attention to particular groups of focus is to change the shape and size of the dots.

Display and Compare Geographically Related Data

For example: Compare differences between and across office locations

Consider using: Maps

As shown in Figure 5.17, maps are used to illustrate differences between geographies and allow users to quickly compare across multiple geographies. Maps can help users contextualize data in a familiar frame of reference and take in multiple data points at once.

Visualizing Quantitative Data In her article “How to Visualize Qualitative Data,” Ann K. Emery of Depict Data Studio outlines several ways to bring qualitative data to life.³ Among the options are word clouds including packed bubbles, icons beside descriptions and responses, color‐coded phrases, and closed‐ended data beside open‐ended data. Descriptions and examples are provided below.

Word Clouds Emery writes, “Here's the most obvious strategy for visualizing text‐based data: the word cloud, also known as a tag cloud. Frequent words or phrases are shown in larger, bolder font. Less‐frequent words or phrases are shown in a smaller font. Data visualization novices love to love word clouds, while data visualization experts love to hate word clouds. Word clouds are okay for visualizing one‐word descriptions [and for before/after comparisons], but not for visualizing all your qualitative data. I'm not advocating for run‐of‐the‐mill word clouds where you simply dump your interview transcripts into a word cloud and hope for the best. Simply looking at how often a word or phrase appears in your dataset is not a sufficient way to analyze your data! Instead, I'm talking about intentional word clouds—when you've considered other options and have purposefully chosen a word cloud as your visualization of choice.”

Figure 5.18 provides an example of a before/after word cloud depicting one‐word descriptions of an organization's culture before and after embarking upon a DEI journey.

Figure 5.19 shows the same data in the before/after word cloud using packed bubbles, which are similar to word clouds. Whereas word clouds depict word frequency via font size, packed bubbles depict word frequency via bubble size.

There are a multitude of no‐cost and low‐cost tools for generating word clouds. Two of my favorites are: www.jasondavies.com/wordcloud/ and www.freewordcloudgenerator.com.

Icons beside Descriptions and Responses Using icons beside descriptions and responses is almost a no‐brainer, especially to break up long sections of text and make them more visually appealing.

Figure 5.20 shows a series of icons used to visually enhance a summary of barriers facing women to becoming executives.

Color‐Coded Phrases Color‐coded phrases are an easy and effective way to visually depict themes within qualitative data. It is recommended that you color‐code both the words and the background/highlighting of the words for easier readability using colors with high contrast such as black letters against a green background/highlight.

Figure 5.21 shows the same focus groups transcripts that were presented previously in Step 1: DEI Inventory using color coding to represent challenges and opportunities for women and people of color. While you cannot discern the colors in this printed text, the responses at the top are presented with black letters against a red highlight, while responses at the bottom are presented using black letters against a green highlight.

Closed‐Ended Data beside Open‐Ended Data Presenting closed‐ended data beside open‐ended data can be an effective way to visualize both quantitative data that captures what people think/feel and qualitative data that describes why they think/feel that way. Figure 5.22 shows closed‐ended and open‐ended data side by side from an unconscious bias seminar evaluation.

Word clouds, icons besides descriptions and responses, color‐coded phrases, and closed‐ended data beside open‐ended data are all visual representations of qualitative data that can be helpful both in analyzing qualitative data and when results are being communicated. Other options to consider include flow charts, matrixes, diagrams, sketches, drawings, images, cartoons, and analogies.

Choosing between DEI Scorecards and Dashboards

Table 5.4 summarizes the key differences between DEI scorecards and dashboards.

For people trying to decide between a scorecard and a dashboard, the good news is that you can have the best of both worlds. Given the range of personal goal‐tracking, habit‐tracking, task‐tracking, and planning apps, tools, and platforms, it is relatively easy to create a personal DEI scorecard and dashboard all in one (a list of options and an example was provided earlier). These tools support the monitoring and tracking of a scorecard with the trend analysis of a dashboard. However, if you prefer to keep it simple, you can use a simple template, like the one illustrated previously, that can be found on BCT's website.

For organizations trying to decide between a scorecard and a dashboard, the decision is determined by what is the best fit for you and/or your organization and what arrives at the right cost/benefit, while recognizing that you can also do both.

Scorecards are relatively easier to implement and can be produced manually, again, with varying degrees of difficulty depending on the extent to which data is available, accessible, integrated, and centralized. Scorecards can be an excellent fit for organizations that are new to DEI, when the single topic of DEI is sufficient for their strategic purposes, and/or they do not have the data and technological infrastructure and capacity to support a dashboard. The downside of a scorecard is the inability to drill down and see historical trends across multiple topics. By comparison, dashboards provide these and other features and functionalities including automation, integration, customization, and personalization, across multiple topics including DEI, and can produce scorecards. While dashboards can require more effort to implement due to the organizational coordination, data integration, and technology implementation requirements, there are a growing number of tools that minimize the hurdles and streamline the process. Dashboards can be a good fit for organizations that are already along their DEI journey and have reasonably mature DEI programs. They are excellent for organizations that have multiple data sources and/or would benefit from an enterprise‐level, integrated, strategic, and operational view across multiple functions including but not limited to DEI. In summary, dashboards are highly recommended but only when there is a clear and compelling cost/benefit. Otherwise, a scorecard will more than likely suffice.

Now that we have fully explored DEI scorecards and dashboards, described best practices for their deployment, and discerned how to choose between them, I will turn our attention to evaluating results and determining DEI impact.

Collecting New Data

First, you must decide what portion of your assessment to re‐administer. For personal DEI assessments, we recommend re‐administering those that relate to competences, and perhaps adding new ones that relate to preferences and competences. With respect to competences, it is not uncommon to make progress against an assessment instrument and then regress or revert backwards, so by re‐administering the same instrument for competences, you are able to monitor these and other dynamics. Moreover, depending on your results, adding new instruments for preferences and competences offers fresh insights for your DEI journey. The question of whether to re‐administer a personal DEI assessment related to preferences is a nuanced one that I will answer in a moment.

You will recall that your overarching objective is to increase your level of competence in areas that are relevant to your DEI journey. It is not necessarily to change your preferences, but rather to develop an ability (i.e., a competence) to shift, stretch, flex, or expand into areas outside of your preferences and to mitigate blind spots. The immediate value of a personal DEI assessment is to know your preferences, so that you know your tendencies and your blind spots (and to understand the tendencies and blind spots of others), which only requires administering a personal DEI assessment for preferences once. Therefore, while it is useful to re‐administer a personal DEI assessment for competences, it is debatable whether it is useful to re‐administer one for preferences.

On this matter, the following are insights from Herrmann International based on research conducted with their HBDI^® assessment for thinking preferences:⁹

Longitudinal studies of hundreds of HBDI^® participants indicate that change can take place if there is a reason for it. Change seems to take place over a long period of time with an individual's desire and willingness to change, or with a change in their life's circumstances, or as result of a significant emotional event. Profiles do not change casually; rather, a dramatic change in the person's life is required to cause a change. Profiles often change when there is an event, or series of events, that has value‐shifting impact. Examples include a major change in the family (e.g., birth of a child, death, divorce), a major career change, going back to school, engaging in a completely different field of study, or maybe even going off to war. Changes to the profile in a 5% range can fairly easily occur, but usually the shape of the profile remains the same. However, if nothing has happened to the individual, and they continue to do the same things in the same way, then the profile will remain stable.

In other words, while the likelihood of preferences changing significantly is low and does not happen overnight, it does happen. Therefore, in addition to re‐administering your personal DEI assessment for competences, I recommend that you re‐administer your personal DEI assessment for preferences, too. This will either corroborate your prior results or illuminate changes. I also recommend combining a personal DEI assessment for preferences with a diverse 360° assessment because, as I cited in Step 1: DEI Inventory for People, the assessment not only reveals preferences and competences, covers a wide range of areas with depth, and seeks diverse perspectives on how well you function in diverse settings, but it also can be easily combined with other assessments. While you may not see significant changes in your personal DEI assessment for preferences within one to two years, you are almost certain to see changes in your diverse 360° assessment within one to two years, thus ensuring that you are receiving valuable feedback and data to inform your DEI journey.

At BCT, we recommend re‐administering a full organizational DEI assessment including quantitative (i.e., culture and climate survey) and qualitative (i.e., IDIs and focus groups) research methods. If you are unable to re‐administer a full organizational DEI assessment, for any number of reasons including cost and other circumstances, then you can explore the following alternatives, some of which were previously discussed in Step 1: DEI Inventory for Organizations:

• Develop a “Stratified Sampling Plan” that surveys a subset of your total employees but is representative of the population. This will reduce the number of people completing the survey.
• Deploy a “pulse survey,” that is, a shorter version of the survey, based on a subset of the original questions that is administered to only a subset of the entire organization. If designed properly to focus on the questions that matter most, a pulse survey can collect valuable information in a short amount of time.
• Reduce the number of questions in your in‐depth interview and focus group protocol. This will shorten the amount of time required from participants while still obtaining qualitative insights.
• Facilitate fewer IDIs and focus groups and/or only invite new voices to participate while ensuring that those voices are representative of the organization. This will reduce the number of people participating in IDIs and focus groups.

While we recommend re‐administering a full organizational DEI assessment, these alternative approaches are viable especially when underrepresented and/or marginalized voices are sufficiently represented in the assessment.

Second, to determine what data should be collected, you must determine the frequency to re‐administer your DEI assessment, which speaks directly to a related question: How long does it take for change to occur?

Evaluating Results

You will recall that Step 1: DEI Inventory involved administering a personal and/or organizational DEI assessment that generated a profile and a baseline, or reference data point, for your DEI journey. By re‐administering some or all of the prior DEI assessment, you can compare the current results to your baseline results while essentially establishing a new baseline or reference data point.

For example, let's assume that during Steps 1 through 4 for people you took the Antiracist Style Indicator (ASI) as a part of your personal DEI assessment, and it assessed you as an “underfunctioning” antiracist. It is likely that somewhere embedded within your personal DEI objectives and goals was something akin to this: “increase my level of antiracist competence from ‘underfunctioning’ to ‘functioning,’” based on personal DEI strategies and measures informed by the promising and proven practices of a “What Works” model. It is only by re‐administering the ASI in Step 5 that you will know whether you have fulfilled your objective and achieved your goal for antiracist behavior. The data produced by re‐administering the ASI becomes your new baseline or reference data point, which takes you back to Step 1.

As another example, imagine that during Steps 1 through 4 for organizations, your organizational DEI assessment involved BCT's DEI Workforce and Workplace Assessment™ (DWWA™) survey combined with focus groups with members of the LGBTQIA+ community, whereas the DWWA™ survey revealed that they experienced statistically significant higher incidents of bullying and discrimination reports. It is reasonable to assume that among your organizational DEI objectives and goals was something similar to this: “decrease incidents of bullying and discrimination reports by 50% and increase feelings of inclusion and belonging by 25% among members of the LGBTQIA+ community,” by leveraging the promising and proven practices of a “What Works” model that informs the DEI strategies and measures established by your organization. While you may be tracking discrimination reports in your HRIS, it is only by re‐administering the DWWA™ and the focus groups in Step 5, or something comparable, that you will know whether you have fulfilled your objective and reached your goal for bullying, inclusion, and belonging. The data produced by re‐administering the DWWA™ and the focus groups becomes a new baseline or reference data point, which takes you back to Step 1.

When you analyzed your personal and/or organizational DEI assessment data in Step 1: DEI Inventory, you began with a blank slate. For people, you sought to generate findings and insights to your personal DEI preferences or personal DEI preferences and competences. For organizations, you sought to find and identify insights to organizational DEI challenges and opportunities, such as statistically significant differences between subgroups (e.g., women vs. men vs. nonbinary; people who are visually impaired vs. people who are deaf and hard of hearing; employees in the domestic office vs. employees in the overseas office; etc.) and between intersections of subgroups (e.g., domestic women who are visually impaired vs. international men who are deaf and hard of hearing). Data is a mirror. What you see is a reflection of you and/or your organization. Here in Step 5: DEI Impact, you have the potential to generate three kinds of findings:

1. New findings—By using the same approach that you used to analyze your DEI assessment to analyze your DEI re‐assessment, you will uncover new findings and insights reflecting changes that have occurred since you conducted the prior DEI assessment. For example, one year later your personal DEI re‐assessment may reveal an unanticipated change in your personal DEI preferences due to a major change in your life's circumstances. Similarly, your organizational DEI re‐assessment may reveal a statistically significant and/or observable difference in uncivil behavior at an office location, that was not a finding from the baseline DEI assessment, due to an influx of new employees who are misbehaving.
2. Emergent findings—By tracking and monitoring your DEI reports you will glean emergent findings and insights to your outputs, or progress relative to strategies and measures, as well as your outcomes, or impact relative to your objectives and goals. For example, at the end of your first year, you may find that you have completed 95% of your measures (i.e., outputs) and 90% of goals (i.e., outcomes).
3. Comparative findings—By comparing current DEI measures, metrics, and key performance indicators (KPIs) to the past, you will illuminate comparative findings and insights; that is, measurable differences and/or statistically significant differences between your baseline DEI assessment and re‐assessment data. For example, one year later the comparison between the Intercultural Development Inventory^® (IDI^®) score of your personal DEI assessment may uncover a measurable increase from “minimization” (i.e., you de‐emphasize differences) to “acceptance” (i.e., you deeply comprehend differences). Along the same lines, one year later the DEI culture and climate survey of your organizational DEI assessment may uncover a significant decrease in the incidents of bullying toward members of the LGBTQIA+ community.

While it is the combination of emergent findings and comparative findings that allow you to comprehensively evaluate results in the present, the new findings will help inform next steps for the future.

Generating Findings

Generating findings represents the final piece of the puzzle to fully determining impact. This necessitates a close examination of the following results to paint a comprehensive picture of impact:

• For People:
  • Based on your personal DEI assessment and re‐assessment data, you should examine:
    • The extent to which your preferences—the things you tend to think, feel, and do—have changed or remained the same and the extent to which you have greater awareness and/or appreciation of your preferences and those of others.
    • The extent to which you have increased your level of competence—the ability to do something properly and successfully—and improved your knowledge, skills, and attitudes/attributes (KSAs) in the areas you have designated.
    • Depending on the personal DEI assessment tool(s) you selected, this may include examining the extent to which you are able to shift, stretch, flex, or expand into areas outside of your preferences and mitigate blind spots in the areas you have designated.
• For Organizations:
  • Based on your organizational DEI assessment and re‐assessment data (with disaggregated data), you should examine:
    • The extent to which the comparative results show significant and/or observable differences in the areas you have designated, as evidenced by quantitative data, which captures what people think/feel about a topic, and qualitative data, which captures why or how people think/feel that way.
• For People and Organizations:
  • Based on your DEI results data and reports (with disaggregated data)—scorecard and/or dashboard—including leading indicators, often related to equity and inclusion, that look forward at future outcomes and events, and lagging indicators, often related to diversity, that look back at whether the intended result was realized, you should examine:
    • The extent to which progress has been made because strategies have been executed and evaluated against measures (i.e., outputs).
    • The extent to which an impact has been achieved because objectives and goals have been accomplished and appraised against metrics and key performance indicators (KPIs) (i.e., outcomes).

The totality of the results and findings—new, emergent, and comparative—from your DEI reports and DEI re‐assessment (Step 1: DEI Inventory) will likely reshape, refine, or redefine the DEI objectives and goals you embrace (Step 2: DEI Imperatives), the DEI promising and proven practices or “What Works” model you adopt (Step 3: DEI Insights), and the DEI strategies and measures you pursue (Step 4: DEI Initiatives) thereafter, particularly given that certain objectives will likely be achieved, certain strategies will no longer be tenable, and certain promising and proven practices will no longer be relevant, while others will likely remain. In this regard, Step 5: DEI Impact does not signify the culmination, but rather, the continuation of your DEI journey and the cornerstone for a cycle of continuous learning, development, and improvement. The final part of Step 5: DEI Impact is DEI data storytelling or integrating the results and findings to craft and communicate compelling DEI stories.

DEI Data Storytelling

Data storytelling is the process of crafting a compelling narrative and sharing insights based on data using visuals. DEI data storytelling enables you to personalize the DEI journey, contextualize data, chronicle progress, synthesize findings, integrate results, and comprehensively demonstrate impact. When done effectively, DEI data storytelling can also inspire and motivate you and others to build momentum and take action. More specifically, DEI data storytelling offers three value propositions:

1. Humanize data and empower—Personal stories can get lost in any data‐driven approach. People are the “what” and the “why” for DEI. Personal stories must remain front and center. DEI data storytelling can help ensure that a diverse set of voices are uplifted representing a diverse range of lived experiences. In doing so, we humanize data by “putting a face” on it. Ngozi Adichie states, “Many stories matter. Stories have been used to dispossess and to malign. But stories can also be used to empower, and to humanise.”
2. Communicate lasting and emotional messages—Storytelling is among the most effective ways to communicate a lasting message. Research has found that stories are more memorable, more persuasive, and more engaging.¹⁷ For example, according to a study by Chip Heath at Stanford University, 63% of people can recall based on stories, while only 5% of people can recall based on statistics.¹⁸ In his article “The Neuroscience of Storytelling,” Erik Larson explains how stories engage more of the brain than data and facts. “When packaged into a story, your fact set has a bridge to the emotional part of the brain. What neuroscientists observed is that factual information only engages two parts of the brain, Broca's and Wernicke's area. This is in stark contrast to the spectrum of other parts of the brain engaged by a story, including movement, smell and emotion. People hear statistics, but people feel stories,”¹⁸ writes Larson. DEI storytelling enables people to feel the experiences of those who are different from them.
3. Inspire and motivate action—DEI storytelling can paint a clear and compelling picture of what has happened and why it has happened. When people can relate to these stories and see reflections of their lived experience, it can inspire them to see greater possibilities for themselves and others. In doing so, the lasting impression left by a well‐crafted DEI story can also represent a call to action. By seeing what is possible, and how to make it possible, DEI stories can motivate people to pursue new paths or recommit to existing ones. Interestingly, this hearkens back to the very beginning of our DEI journey in Step 0: DEI Incentives where we discussed intrinsic and extrinsic motivation. DEI storytelling can lead to intrinsic motivations such as self‐interest or internal desires, or extrinsic motivations by demonstrating benefits or rewards. In his article, “Storytelling for Action,” Peter Minimum, a market researcher, concludes, “The movement captured in a complete story is the best way to engage an audience and communicate an idea that results in action.”¹⁹

I will now explain the elements of DEI data storytelling.

The Three Elements of DEI Data Storytelling The three elements of DEI data storytelling are:

1. Data—A complete and integrated analysis of the relevant quantitative and qualitative data, including data from your assessment, measures, metrics, and KPIs, to paint a full picture and set the stage for the narrative.
2. Narrative—An oral or written storyline reflecting insights from the data analysis, context surrounding the data, messages being communicated, ideas sought to convey, and call to action.
3. Visuals—A visual representation of the data according to the narrative in the form of tables, charts, pictures, diagrams, graphics, infographics, videos, and the like.

These elements should combine to produce clear and compelling stories that are lasting and lead to desired change. Along these lines, in his Forbes article “Data Storytelling: The Essential Data Science Skill Everyone Needs,” Brent Dykes explains how these different elements work together to produce associated outcomes (see Figure 5.24):²⁰

When narrative is coupled with data, it helps to explain to your audience what's happening in the data and why a particular insight is important. Ample context and commentary are often needed to fully appreciate an insight. When visuals are applied to data, they can enlighten the audience to insights that they wouldn't see without charts or graphs. Many interesting patterns and outliers in the data would remain hidden in the rows and columns of data tables without the help of data visualizations. Finally, when narrative and visuals are merged together, they can engage or even entertain an audience. It's no surprise we collectively spend billions of dollars each year at the movies to immerse ourselves in different lives, worlds, and adventures. When you combine the right visuals and narrative with the right data, you have a data story that can influence and drive change.

A key takeaway is that while DEI data collection, data analysis, and data reporting are all distinct and important capabilities, DEI data storytelling is equally distinct and important. In fact, ineffective data storytelling can completely negate and undermine all its predecessor steps no matter have effectively they have been executed. It is therefore of paramount importance that DEI stories be crafted and communicated with care to honor the DEI journey and maximize impact.

Continuing the Five‐Step Cycle of Data‐Driven DEI

In conclusion, be mindful that you can tell your DEI story at every step along your DEI journey: after you’ve completed your assessment (Step 1: DEI Inventory), once you've established your objectives and goals (Step 2: DEI Imperatives), at the point when you have identified promising and proven practices (Step 3: DEI Insights) and arrived at strategies and measures (Step 4: DEI Initiatives) and, of course, when you have results to be shared (Step 5: DEI Impact). Whether you are sharing your DEI story in a 280‐character post on social media among friends and family, or in an 80‐page annual report that is widely distributed and released to the public, DEI is a never‐ending journey, so DEI storytelling is a never‐ending endeavor.