Branding Cannabis — Now’s The Time To Get It Right
Thomm Bonno
Cannabis presents a once-in-a-century opportunity to make transformative impacts on our troubled world.
"Cannabis presents a once-in-a-century opportunity to make transformative impacts on our troubled ...
My longtime carpenter was working on my home the other day and we got to talking. He asked me in his thick Irish accent about the cannabis industry in California and what happened to it. “It used to be for helping people but now it’s all about the money,” he said, while shaking his head in disbelief.
My heart sank when I heard his words. It was even more painful when I had to agree with him because he’s right...and not just in California.
The nascent cannabis industry used to have a good reputation with the public because medical cannabis operators like Harborside (my former company) were focused on wellness products and messaging. Our mindful communication with the public tapped into something that was already there.
Almost everyone in America knew someone with cancer who got better from marijuana during chemo. The media helped us tell stories of people with serious illnesses finding relief from cannabis. Even children with epilepsy made national news by benefitting from weed. After years of this branding work, pop culture defined the industry as a good force in society.
That perception is quickly changing with adult-use legalization and the injection of billions of dollars of capital to scale the industry. Like all things involving large transactions, greed moves goodness right off the headlines.
The media is now fixated on the capital and not the consumer. The culture of private planes and big exit events has permeated the branding of the cannabis industry in the minds of the public.
Some may say this is a good thing, as it further normalizes cannabis and assimilates it into the mainstream. What could be more normal than chasing a buck? I say it’s a troubling development that could jeopardize widespread access to legal cannabis in our society. When you’ve been doing this as long as I have, you remember the setbacks and how long it takes to recover from them. You see patterns over time that repeat themselves.
Prohibition does not come in one fell swoop. It happens bite by bite so the public supports each bite. This is what happened with things like urinalysis testing for cannabis in the workplace. If the perception of the industry is bad, the public gets more open to the bites.
The enemies of cannabis are not fools. They will pounce on any negative public perception to whittle away at legalization and restore prohibition. They will bare their teeth and then try to take their best bite.
First it may be to ban consumption clubs. Then onto potency limits and empowering local NIMBYS to block access to licenses. Next it will be taking away home growing (or not granting it in the first place) or lowering possession limits, and on and on until legalization becomes the twin cousin of prohibition.
Cannabis consumers will be pushed back into closets and punished for emerging with joints in hand. And the public won’t mind a bit. They may even support it if the industry does not get its branding house in order.
People want to support legalization but we have to give them good reasons and healthy examples to follow. It’s up to all of us to remember where cannabis came from and make sure the wellness roots of our industry remain center stage. And we have to restore justice and make sure our industry is inclusive. Those are the stories we need to tell. This is how we create positive vibes in the minds of the public.
Happy Danksgiving
Drinking Dom while flying on a private jet with pretty people consuming your weed brand might be a little out of touch with ordinary people. It can also cause resentment because most people don’t live like that. And it makes them wonder what the cannabis industry is for after so many decades of difficulty and injustice. It raises questions about legalization in the first place, and this is the last thing the industry needs right now.
If we act too transactional and allow the chase for global domination to take a hold on our branding, a backlash could occur. And it could take a long time to regain the trust of the public. The brand of the cannabis industry is at stake. Now is the time to get it right. More than that, cannabis presents a once-in-a-century opportunity to make transformative impacts on our troubled world. That is the branding we should be working towards and pushing out to the masses.
This is our most rewarding work because it’s about our legacy as much as our purpose. If we do a good job, I’m hoping a couple years from now my carpenter friend will compliment all of us on turning it around. Maybe he’ll say something like, “It looks like the cannabis industry finally got it right, thank you for making the world a better place.”
Follow me on Twitter or LinkedIn. Check out my website.
Andrew DeAngelo
Andrew DeAngelo
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I’m a cannabis business consultant and strategic advisor with a track record of enacting systemic social change... Read More
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Doing Good Data Means Doing No Harm
Nov 17, 2021,01:31pm EST
Doing Good Data Means Doing No Harm
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Tableau
Renee MacLeodBrand Contributor
TableauBRANDVOICE| Paid Program
Innovation
Data analysis and data communication are fundamental to the way people and businesses understand concepts, make decisions and create solutions.
Anyone who communicates with data needs to be mindful of the impact of the stories they tell. Sometimes they can do more harm than good. The reality is that unintentional harm can result from data that is misrepresented or misused—from reinforcing damaging stereotypes to compounding systemic racism and discrimination.
To influence change and advance the understanding of what it means to use data with empathy and fairness, the Urban Institute, in partnership with Tableau Foundation, created the “Do No Harm Guide: Applying Equity Awareness in Data Visualization.” This resource offers data communicators actionable insights to help ensure their research, analysis and visualizations incorporate principles of diversity, equity and inclusion. As a group of growing data communicators and data-driven organizations, we all must recognize that data points are more than marks on a graph—they represent real people.
Inspired By A Growing Conversation
The idea to create the “Do No Harm Guide” grew in the wake of the Black Lives Matter movement. Its creators, Jonathan Schwabish, senior fellow at the Urban Institute, and Alice Feng, senior data scientist at Natera, wanted to use their data viz experience to contribute to the bigger, growing conversation about race. The focus of their work expanded as they conducted conversations with nearly two dozen experts, uncovering a greater necessity to examine how people and organizations collect data, where the data comes from, why it’s necessary to respect and include the people you research, and how to explore the entire research ecosystem.
Topics include:
How the concept of empathy relates to data, research and visualizations.
What it means to approach data with an equitable lens.
How racial stereotypes can be reinforced and groups can be harmed by data that is not grounded in principles of inclusion and fairness.
Key Recommendations
In my conversation with Schwabish and Feng, it became clear that the guide should be an essential resource for any data communicator and organization, and that there is increasing interest in learning to do no harm with data. As Feng noted, “It’s an evolving document that will grow and expand as feedback is received, as the field matures and as more people think about these issues.”
Let’s look at 10 recommendations from the guide that can help anyone who works with data be more aware of its impact and learn to become more mindful, empathetic and inclusive when telling data stories and when talking about data with people or communities.
Graph chart showing average female height per country, represented by pink figures of varying sizes in dresses, with sizes of figures ranging from 5 feet to 5 feet, 5 inches.
Figure 1: The size differential among people in this chart creates ambiguity about the intent and could be interpreted as offensive. URBAN INSTITUTE, CITED FROM @REINA_SABAH
01 Critically Examine Your Data
Before you begin to visualize your data, consider the context of your data. Equity awareness begins with gaining a holistic understanding of the story behind the data. Where does it come from? Who is included and excluded from it? How was it collected? Why was it collected? And who benefits or is harmed by it? As Feng and Schwabish note in the guide, “If I were one of the data points on this visualization, would I feel offended?”
02 Use People-First Language
If your data is about people, make it extremely clear who they are, remembering that your data reflect real lives and experiences. It could include your co-workers, prospects or customers, candidates and more. Data labels should lead with the person, not their characteristics. In visualizations, you should strive to use people-first language: For example, “people with disabilities” is preferable to “disabled people.”
03 Label People, Not Skin Color
Nine small squares in different colors and shades stacked in a square with gray directional arrows and labels shown at the top and at the right of the square that read “More Black” and “More Poverty” in which the darkest square represents the “most Black” and “most poverty”.
Figure 2: This legend was later changed from “More Black” to “Larger Black Population” to put emphasis on people, not skin color. URBAN INSTITUTE, RECREATED FROM TABLEAU DASHBOARD.
Language is living, breathing and ever-changing. It’s only logical that certain labels that were previously used are no longer acceptable. They might, in fact, be offensive. In your data analyses, the best approach is to use full labels, such as “Black people” not “Blacks.”
The language in Figure 2 is not as inclusive as it could be. “Poverty” refers to an experience, not a static description, and “More Black” refers to skin color, not people. More inclusive language might be “Larger proportion of people experiencing poverty” and “Larger proportion of the Black population.”
04 Order Labels In Purposeful Ways
Have you stopped to consider who shows up first in a table, graph or visualization? Surveys and other data collection methods frequently order responses hierarchically and in ways that reflect historical biases. It’s the order in which groups are listed in visualizations or narratives that can impact how the data is consumed or interpreted. Listing “white” or “male” first, for instance, can imply that it’s the dominant or more important group.
Consider alternative ordering or sorting, such as study focus, specific story or argument, quantitative relationship, alphabetical order, or sample size.
05 Consider Missing Groups
It’s important to acknowledge who is or is not included in data and charts. One way to do this is using notes and narrative that offer essential context for viewers who may not understand why groups are or are not represented.
Sometimes, there are charts that show data in broader racial groupings rather than at a disaggregated level where nuances are better understood. For example, in the United States, many charts on race and ethnicity only show white people, Black people, and Hispanic or Latinx people, but not other groups. According to Feng, “When reporting at aggregated levels, we miss lots of variation. This creates implications in understanding issues, knowing what people or communities need help, and what kinds of programs or policies to design that will make a difference.”
To demonstrate how aggregating racial groups can mask variations across more detailed information, the corresponding figure shows the estimated 2019 poverty rates for 139 racial groups recorded in the U.S. Census Bureau’s American Community Survey. Dots show estimated poverty rates for all 139 groups and the overall poverty rate for major racial groupings frequently used in analyses. As you can see, the poverty rate for some of these groups varies widely.
Graph showing variation in poverty rates by race (American Indian/Native Alaskan, African American, White, Asian/Pacific Islander and other) and poverty rate (0% to 40%)
Figure 3: Disaggregated poverty rates across racial groups reveal variation that is missing when metrics are presented only for overall groups. URBAN INSTITUTE, CREATED FROM U.S. CENSUS BUREAU’S AMERICAN COMMUNITY SURVEY DATA
06 Use Color With Awareness And Care
The way we use color can inadvertently reinforce stereotypes, offend and perpetuate inaccurate depictions of people and groups. To use color with the best intent, check your choices. Avoid colors associated with stereotypical gender labels—pink for women and blue for men, for example. Avoid colors also associated with skin tones or race, such as light-to-dark, or incremental color palettes indicating different demographics. And be aware of emotional connotations associated with certain color hues.
Color-coded chart legend where a colored square (red to gray gradient) represents different races and ethnicities (Black, Hispanic, American Indian, Native Hawaiian, Asian, White, etc.)
Legend showing a problematic color scheme applied to data on race and ethnicity. The shades of red apply to people of color while the only group that has its own color is white people, suggesting that they are the norm or default to which all other groups should be compared.
Red can have negative connotations in Western culture—often associated with danger or aggression. The graduated color palette can also be misinterpreted as suggesting a hierarchy.
See the guide for an example of a color palette without hierarchical connotations. URBAN INSTITUTE, RECREATED BASED ON THE JUNE 2020 VERSION OF THE DIVERSITY DASHBOARD FROM THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY, OFFICE OF THE PROVOST.
Consider The Impact Of Icons And Shapes
Icons, by their very nature, are intended to convey broad meanings—but they can perpetuate harmful, offensive stereotypes when used carelessly. Choose them with intention.
It’s essential that any and all stereotypical, discriminatory and racist imagery be avoided; depict people as empowered and dignified versus being helpless.
Reach Out And Involve Communities
For data to be meaningful and relevant, it’s important to work with the communities at the center of it. According to Channing Nesbitt, social impact program manager at the Tableau Foundation, community input is key.
“Without their guidance and hearing how they live through these experiences, it leaves out part of the information that needs to be displayed and shared,” Nesbitt said. Start with building diverse research teams, work closely with the communities studied, and receive buy-in from members, policymakers and other stakeholders to help the research be embraced.
Maintaining relationships also demonstrates commitment, partnership and that you’ve listened to and clearly understand the collective voices.
Reflect Lived Experiences
We don’t all have the same life experiences. Our individual characteristics, such as ethnicity, gender, neurodiversity and age, can deeply impact how we approach data and the ways in which we communicate it.
To help identify what perspectives and viewpoints may be missing, consult people within and outside of your organization.
Understand The Needs Of Your Audiences
The value of data lies in how it is used, shared and understood by intended audiences. As data communicators, we’re all responsible for ensuring that content is clear, unambiguous and useful.
This requires due diligence across all aspects of our work, striving to ensure that the word choices, terminology and languages we publish in are fully optimized for audiences.
A Path To More Inclusive Analytics
Ensuring that people are fairly represented is the cornerstone of diversity, equity and inclusion, and for data communicators, it’s foundational to building credible, more equitable analyses.
While there is no one-size-fits-all approach for organizations working to strengthen and expand their inclusion initiatives and do better with data, the “Do No Harm Guide” provides a solid framework for understanding the questions to ask, practical ways to drive inclusive thinking and strategy—and above all—how to lead with empathy.
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