I’m a user experience designer at YML and am passionate about motion graphics and photography. I love to prototype, build and bring emotion and delight to digital experiences. I had the pleasure of collaborating with the Cafe X team to animate, prototype and deliver their in-app animations.
Cafe X is a barista robot with an automated system that looks to ensure accuracy, efficiency and eliminate all human error while keeping the quality craft of your beverages.
Around a year ago, YML collaborated with their team to create a set of animated illustrations within the Cafe X App:
The goal was to echo a sense of humanity, cheerfulness, and humor throughout crucial and memorable moments of the App.
After exploring different styles, we landed on a set of cheerful illustrations with bright colors, along with bouncy and lively animation to contrast the minimal and industrial feel of the App.
Most Apps forget what a nuisance it is to be bombarded with permission requests without context. This was the first crucial moment of the experience since it’s critical for the system to know the nearest kiosk available.
Having a looping animation here alongside the conversational text was designed to help and educate the user, and encouragethem to enable it.
Order customization is an emotional moment in the experience. The user gets to be creative and make their beverage perfect. So this is where — in my opinion — the most humorous animations occurs.
We decided to have a cow mascot that would react to the user milk type selection. We wanted to make this character feel alive, emotional and responsive to the user’s input, so even when he was not selected, he would hide and take a peek behind the milk carton.
The Shopping Cart
Another key moment in the App was access to the cart.
We all know that abandoned carts are common in e-commerce experiences. So having an animated icon in sync with the card modal was used to bring attention and emphasis to complete this user flow.
Waiting for Your Order
Finally, the last key moment of the experience was the waiting time between an order being placed and being completed. The possible lack of physical presence of the user could create anxiety due to the uncertainty of their order status.
So we created three animations for each of the steps: Order queued, now making and now ready. Each one transitioning to the next one as the order progresses in real-time.
Thoughtful micro-interactions and animations are an indication of awareness for your user’s emotions. That’s why they’ve seen a peak in the design community in recent years. At YML, we believe discreet, yet delightful, design moments like these drive positive feelings about a brand, and often influence user’s actions.
We continue to partner with the Cafe X team and are eager to continue helping them evolve in a dynamic brand.
A people-first approach is neither easy to create or quick to implement. But it is the secret sauce at the core of the biggest and best brands in the world today.
Customer experience is a strategy that all digital insiders know has to be a focus if they want to have a lasting impact in their industry. However, the execution of customer experience isn’t as easy as just coming up with a plan to leverage emerging technology and building digital products. It’s as much about igniting cultural change within a company as it is about planning for the evolution of the experience.
At YML, we’ve designed a dynamic and thorough people-first strategy built to cultivate cultural change.
That people-first approach is what is missing from the majority of CX initiatives — and it shows.
Executives who have made a push for a CX strategy have not seen a tangible business improvement. 20% of companies scored 9-10 for seeing a Return on Investment, with 14% of companies scoring 0-2 (Confirmit, 2018).
The public doesn’t believe they have reaped much benefit from CX initiatives.
54% of U.S. consumers say customer experience at most companies needs improvement (PWC, 2018).
Culture and legacy technology systems have been major reasons for people not seeing the consumer benefit of CX initiatives.
54% of organizations cite culture as the primary challenge to becoming more agile, followed by the inflexibility of legacy technologies (Confirmit, 2018).
The companies who are reaping the rewards of CX initiatives, whom are mainly located in Silicon Valley, are the ones who have unequivocally added benefit to people’s lives.
The S&P Index is largely a Technology Index as of 2018, including companies such as Alphabet/Google, Facebook, Apple, Microsoft, Amazon (Seeking Alpha, 2018).
What differentiates the Silicon Valley behemoths and startups is the people-first approach.
A people-first approach comes with a shift in mindset that is drastically different from the historical business executive mindset. You suddenly are talking about the broad spectrum of all people, internally and externally, instead of just customers, and ultimately revenue. You are talking about emotions as opposed to products. Instead of technology solutions, you are building conversational tools. Lastly, whereas a business-centric mindset is one that optimizes based on minimizing risk and maximizing revenues, a people-first mindset is one that optimizes for transparency and intrinsic value.
In the short term, when first making this cultural shift, these optimization goals can constrain each other. In the long run, a people-first approach will maximize revenue, reduce risk, build loyalty with your team, and, quite frankly, keep your business relevant.
But this is a very difficult story to tell when in a boardroom meeting. Often times a savvy executive can make the initial case for investing in CX, but isn’t able to clarify the full scope of that CX investment, which includes a gradual and tangible, cultural change to people-first. What ends up happening is that the first part of the project may go well and the customer may come first, but then the returns on revenue and reduced risk are not immediately recognized and therefore the mindset shifts back to business as usual.
The trick is to trust the strategy. Trust consistency of message and approach.
Here are some examples of companies optimizing for people-first.
Netflix created an easy to cancel monthly subscription experience along with reminders to cancel after the trial period so that customers never felt like they were overcharged or cheated in someway. However, this people-first change, optimizing towards transparency, had an estimated loss of $50M in subscription revenue. At the time, that was still a small percentage of overall revenue and in making the change towards transparency it built long term trust. As a result of improved brand perception, they continue to increase their monthly subscription base, hitting their highest level of subscribers in Q1 2019.
In 2016 McDonald’s invested in elevating the interior environment of their stores to feel more premium, along with adding in self-ordering digital kiosks and table service. Investing in improved interiors is a table stakes strategy. Let’s face it — they needed to make this people-first investment just to stay relevant. It is table stakes because the outcome will get you to a net-neutral spot; it’s not going to increase customer base, it’s just going to make sure you don’t lose customers at a faster rate than if you did not implement that update. A clean, premium eating environment is the expectation. But the digital kiosk paired with the improved interior is what took the strategy to a level that would actually increase sales.
The digital kiosk solved a customer pain point of waiting in lines in a way that was hard for competitors to copy right away. Their strategy was to ensure their experience met standards and then improved the standards of the industry. This investment didn’t start to see a return until 2018 for stores within the test. McDonald’s has many other competitive pressures, such as new restaurants with the perception of better quality food and convenience offered through delivery overriding in-store speediness. But refreshed strategy may not be enough to overcome these new customer expectations. Changing expectations raises the importance of adopting a people-centric approach that will allow you to rethink the entirety of the business and how it can pivot from an existing model to a new one.
In both of these instances with Netflix and McDonalds, the immediate impact on the business metrics (revenue, profit) went down. In the long run, these CX strategies resulted in heightened retention over time. Brand perception and revenue drastically improved. They illustrated how creating a people-first culture will help mitigate the initial shock of investment and reduce risk over the long run because the investments made are directly informed by people’s emotions.
At YML we have created a step by step hierarchy to help you understand what actually goes into creating a people-first cultural mindset. Breaking it down into steps can help your teams understand where they are in maturity. The plan is also a tool to understand what steps were missed in the past. The key to this model is that it implies a high level of collaboration from stakeholders from historically siloed teams at every step.
Levels to Creating a People-First Culture:
Feel What People Feel
Extensive marketing research that looks beyond your customers, your competitors’ customers and the points of interaction with you and your competitors
Employees from each team pretending to be your own customer
Employees from each team pretending to be a service rep that interacts with the customer
Empathize to Solve Problems
Build your strategy around the crucial moments of emotions in step 1
Identify what part of the strategy is table stakes vs. what will move customer expectations
Projects that only have table stakes will fail because that only postpones the inevitable of customers churning, it will not promote long term engagement
Ideas that will move customer expectations should be prioritized despite being harder to develop (See how to prioritize innovation with Innovation Index)
Igniting Cultural Change
All team members should be aware of the new people-first research and strategy
The people-first strategy should be outlined in terms of how every person and team can help implement this new strategy and what is expected of them
New rules of engagement defined, highlighted by a culture of not being afraid to fail, must be adopted. This about making a transition from fear of change to perceiving of smart risk-taking as admired
Talk the Way People Talk
Your backend systems and content need to reflect the nomenclature of the way people talk, as opposed to the way an industry insider speaks.
The backend systems must be able to support people’s desired navigation
This sometimes can be a significant change to legacy data architecture.
Build The Experience
Design, develop and deploy
Continuous Optimizing of The Experience
Must have the ability to move quickly and make quick decisions.
Much of this is about empowering mid-level employees with the ability to have more decision making power.
Creating New Customer Expectations
Continuous pulse on changing expectations and creating new solutions to meet those new expectations
Creating new technology
Taking a new technology to solve an unsolved problem
Each step is crucial, and completion of a step without completing the one before it will invalidate all steps. In addition, the investment in each level is additive and represents a cost that is continuously incurred. This means the investment does not go away once a team has leveled up. The result for each step will be unique to every brand and even the approach to all steps is not a one-size fits all. Even if you meet the requirements in each step there are still some cultural habits that will undermine this entire investment.
Habits to Avoid in Order to Preserve a People-First Mindset
Don’t forget to create advocates across all teams. Be sure to allow lines of communication for input and collaboration from all teams. This is a high-collaboration sport.
Don’t say the investment will end with a specific project. Your teams should be continuously optimizing the project and there is no end to the investment. Remember, the CX leaders are actively investing billions every year in creating new expectations (i.e., Steps #1-#7 never go away).
Don’t a business case around just Step #5. Steps #1-#4 are crucial to making sure the investment incurred in Step #5 is not wasted.
Leveraging emerging technology without contextualizing why and how people would use it creates costly mistakes. That can only come once you have hit step #7 and shouldn’t come sooner.
Not investing in robust people-first research. This seems simple enough, but most companies think they have the right research based on satisfaction scores from customers. This is too narrowly focused for a people-first approach.
Not properly communicating the people-first research and initiatives built from it to all teams in the entire company. Teams need to understand what this shift means for them and how they can support it.
Not allowing for employees to feel comfortable about outcomes that weren’t positive. Not everyone will get it right the first time, but they should learn from why it didn’t work. That insight will get teams to the next big thing.
Not expecting team structure shifts in order to become more agile.
Not expecting major changes to database warehousing teams. Usually CX initiatives are considering just what it takes to build a website or app, but fail to consider that the systems that they may read from are not set up to comply with the new people-first strategy.
A people-first mindset should permeate the underlying thinking of all teams. It should be an iterative process that produces long term business results.
It should unite and empower all employees to stand up for what’s right for the customer.
Employee thinking should be able to shift seamlessly between their executive persona and people persona. And most importantly, it should allow employees to feel like people feel because, at the end of the day, all of us are just people.
To say the stakes with voice interactions are high would be an understatement. This is the moment for voice technology.
Voice has the power to capture attention like never before because it hooks directly into the mechanism for how people think. It removes the friction of reading, clicking and translating like with other technologies.
However, voice-based AI is highly constrained in terms of what it can and cannot do:
Voice can only perform tasks that it was programmed to do, which can result in inaccuracies
The user is not aware of all the potential tasks that can be completed
Obviously, voice is not suitable for tasks that require sight
These constraints make the design of voice one with little room for error.
At YML, we think about building products (including voice projects) in the form of an infinity loop, a repeated steps of moments that are continuously optimized as you learn more.
Below we outline how UX and Data Strategists can partner in each moment for a voice-based AI project to reduce risk of voice AI going terribly wrong.
1. DEFINE - Align tone and personality of the conversation
Having a clear, distinct vision is essential for voice.
The utility of the conversation is the most important part of the vision. At this point in time, the voice-based AI has not mastered the art of casual conversation where it can react to what the person has said and feed them what they are anticipating to hear through compliments and relatability.
AI is programmed to learn in smaller verbal tasks and take the learning of the smaller tasks and associate learnings to other tasks (though progress is being made there).
UX should define the utility, personality and context of the conversation. Why is this interaction important to have? At what point should the conversation happen, particularly if the conversation is prompted by another interaction? What is the intended outcome of the conversation? What qualities of our brand will this voice represent?
We must provide evidence for why voice is the right channel to design for in a given interaction, especially by understanding its context. For example, a bedroom voice interface that reduces volume to 25% at late night and is less wordy understands we don’t want loud robotic voices at midnight. Practically, a feature like that could be documented in a user flow.
Understanding the tone and the personality is not something a data person typically creates (or even understands in the real world), however, in voice this is a critical element because the personality is actually a data requirement. For example the answers to the following questions are data requirements:
How human does the voice need to sound?
How should the AI respond?
They should also start identifying any current or potential datasets that may be relevant to help train the AI in the subsequent product phases. They will need to work with a variety of teams to collect and get it into a format that can be easily used during training.
2. DESIGN - Examining vocal vs graphic UIs
Fundamentally, the way we think about the design of sound is different from sight.
Of course there’s overlap, but it’s interesting to take a closer look. For example, a designer strives for visual consistency. Repetition and visual hierarchy help us stay organized when looking at an interface.
But with speech, that kind of repetition gets rather annoying. Therefore, we should think of the journey as a carefully crafted conversation full of familiar variety.
In an app or website, the way people interact is relatively constant. GUI interaction occurs in a fairly regular rhythm of cognitive load. Mentally navigating the interface, reading text, and executing tasks requires a sustained level of attention through out.
It’s a very different situation for voice.
People make the first move, unprompted, and the system responds immediately. And, due to the transient quality of sound, people need to give their full attention to process the response. The luxury of closing an alert dialog without reading it on a GUI is not afforded by voice, nor is the action of reading and re-reading information. Instead, our full attention is required during voice interaction, and absolutely no attention when not interacting.
Therefore, voice experiences should feel like a conversation - an interaction that we want to give more of our attention to when it matters - in order to have the highest likelihood of re-engagement.
UX should define a framework for the desired flow of the conversation.
Similar to designing for GUIs, the overall flow of the interaction needs to be designed, as well as defining the user intent the system should be recognizing.
UX should be asking questions like:
How can we remove friction in the process? Is this how someone would actually think about this interaction? Is the system doing everything possible to pick up on the nuances of speech and trying to move the conversation forward?
Even in the case that the engineering team leverages machine learning techniques to let the AI learn the conversation flow on its own, this framework will help the team identify if it is producing the intended results.
For example, at YML we recently worked with a Fortune 500 insurance company to reimagine their self-service digital strategy, which involved a concept for using in-home voice assistants to handle basic transactions like paying a bill.
Along each step of the conversation, we outlined how the system should move the conversation forward by capturing user intent, setting the variables of intent, and the next action to be taken - all packaged into a helpful and professional voice that emanates confidence and security.
The data strategy team should partner with UX to understand the basic conversation framework and then work with the engineering team to understand their methodology for building the dialog model.
The data strategy team member will need to be able to translate the constraints of each methodology whether its’ rule-based or machine learning-based.
For example, Amazon Alexa skills experts recommend that the conversation has no hierarchy.
This makes sense when designing skills - which typically are a one use product. This is because it prevents questions to have to go through a menu-like conversation (think pretty much any credit card company call centers first line of defense, having to answer a multitude of yes’ or nos before just getting directed to someone).
Though the implications of having no hierarchy mean that:
The skill does not have to go through a rule-based system to answer the question (positive)
However, the conversation can get repetitive leading to an outdated dataset in which the AI is making conversation from, reducing engagement overtime (negative)
This synthesis of the UX framework and engineering approach is important in this step because it will provide input on how to evaluate the success, the learning methodology and optimization strategies post-launch.
3. DEVELOP - Bringing the vision to life and defining metrics
This step is owned by the engineering teams, but this step should entail having regular meetings with both UX and data strategy to ensure that the assumptions they are making are in line with the overall vision from UX and data strategy.
This is also where the AI starts to learn from the team.
Part of defining conversation flows requires defining trigger words in order to move forward in the task. These are documented in the user flow, and are launching points for a task.
During development, UX can conduct usability testing. The classic task-based metrics (effectiveness, efficiency, and satisfaction) are still relevant here, in addition to qual research (in-home ethnography, surveys, interviews, etc.) to learn how customers respond to the design in context.
Data strategy should be listening in to how the AI is progressing over time. If it is not producing the anticipated results, the data strategy expert will need to evaluate why. It may be because the dataset is biased, it may be due to the training dataset not being reflective of the task at hand.
Once the issue is identified, the data strategy expert can make recommendations as to how the dataset should be modified.
Also in this phase the data strategy expert should be outlining a measurement strategy for how the AI will be evaluated based on its current progress. Datasets that will evaluate the performance also need to be built into the development phase. This measurement strategy should include workflows and resources needed to update the AI as it encounters new phrases, as this can be a manual process post-mvp launch.
4. DEPLOY - Monitor, measure, and understand
Voice-based AI is a product that needs constant optimization to not only ensure that it continues to work as anticipated, but also to keep audiences engaged.
If the experience starts to lose it’s initial utility or becomes repetitive, the usage of the product will plummet. Teams should be monitoring and optimizing based on the workflows outlined in the data strategy to ensure the sustained quality of the product.
In addition to refining the design, UX can provide insight into why any failures may be happening.
Was there an insight missing from the define period that changed the perspective of the utility of the conversation? Or is there a technical failure happening? Is the developed conversation mismatched from what was designed? Maybe the personality feels off.
All of this needs to be caught as soon as possible and translated into any new requirements for refinement.
To get deeper insight, UX should review transcripts from all conversations had, as these will provide rich qualitative data to help understand how the product is performing.
The data teams should be analyzing the number of failed conversations, understanding why they failed and making recommendations on how to teach the AI based on these conversations.
This is when the measurement strategy workflow outlined in “Develop” is working.
The data strategy team member will likely need to ensure that the work flows are increasing in efficiency overtime through monitoring the AI KPIs. This is what will lead to continuous optimization of the product infinity loop.
The qualities of voice-based AI defined in this process result in the underlying identity of a brand.
It’s a high impact touchpoint, that when it goes wrong, goes really wrong.
Though, it also has the potential to reach people in new ways. It is the personification of a brand and has the potential for businesses to create new relationships with their customers.
To protect your brand from a potentially high-risk situation, partner your UX and Data Strategy teams together.
Talking about good customer experience is easy. It’s just doing it that is hard.
You’d think it’d be easy for me to talk about it because I have spent the last 15 years talking about it to people who do it every day — clients and designers.
And I have often wondered why is it that all these hours get spent — often on conference calls or in long meetings — by people trying to do the same thing, but in constant disagreement about how it should be done.
A colleague of mine, his wife works as a United flight attendant. That's not her below 🙂
His wife says that on every trip, without fail, at least one customer complains. And they are so bitter, so vitriolic, and they get so angry that they say things like:
“United is the worst.” “You have just lost yourselves a customer.” “I am never going to fly United again.”
But she smiles professionally, all the while thinking:“Of course you will. You will go on Kayak and you will pick the cheapest option—you will consider your milage plan—and I will see you next time.”
In short, improving the customer experience sounds cool, but it will no doubt raise the cost of a United flight. And this might actually turn off more customers than it’s worth.
I was recently having dinner with my wife, and she asked me, “What are some of the questions you have been asked a lot by clients recently?” (A fun date night, right?)
Well, I thought, something I have been asked a lot is,“Yeah, yeah, yeah. This customer experience thing sounds cool. But how will it move the needle?” I have been asked this question in many different ways. By many different clients. At many different organizations.
And, look, I get it. No one wants to invest in all this trendy customer experience goodness, but not see any actual results. Or worse still, see negative results, and they get fired.
For example, I was at a meeting with the head of e-commerce from a major airline, and he said to me that their most vocal customers — the ones who complain the most bitterly — are in fact the ones that are most profitable.
Probably because they have to pay extra for all the things they didn’t plan for—extra bags, extra legroom seats, extra food, etc. Which got me thinking.
First-of-all, is all revenue good revenue? And is it worth putting short-term profits ahead of long-term customer lifetime value?
It has taken me many years as a designer to reach this state of business-minded enlightenment. And finally I have come to the conclusion: Clients don’t actually hire us to make their customers happy. They hire us to make their businesses better.
*And sometimes (sometimes) it’s the same thing.
Now, I realize this might strike you as a little odd. I mean, is this a creative person giving us a business lecture? Just please stick with me.
You see, in the beginning — when I was a young and idealistic designer — I wanted to make things that were beautiful. I wanted them to be just drop dead gorgeous. And I didn’t care about much else.
I call this my aesthetic design phase.
All I wanted to do was create porn. Not real porn. Visual, aesthetic, product porn — and I was lucky to get to do this for brands like Nike and Xbox.
Then, as my career matured, I began to develop more empathy for people. I wanted to create experiences that helped people, were loved, and talked about. Experiences that tackled really high-value life moments, like shopping for a car — like the work I did with Audi, or buying a house — like work I led with Trulia.
I call this my experience design phase.
And then, when I matured again, I developed a deeper understanding for the clients I served. I began to appreciate and better understand their decision making process, and how they are optimizing to make more money.
I think all great designers must go through this evolution. It is the holy trinity of design.
First it was aesthetic problems. Then, experience problems. And lastly, now it’s business problems.
Designers that don’t graduate along this path… well usually, they fall short of their promise, and their careers are stunted. They aren’t opening their minds to this business imperative.
Some years ago, I was given some advice to buy my clients’ stocks on Robinhood — a beautiful, designer friendly app, if you don’t know it. I bought just a hundred bucks worth, here or there. I bought Nike. I bought Activision. I bought NVIDIA (that one went gangbusters). I’m definitely not a power-investor, by any measure, but it gave me valuable insight into my clients’ world — the business of business.
At YML we did work for First Data on their Clover point-of-sales system, and a year ago I bought some of their stock. It’s been quite a ride, but I have nearly doubled my money.
Now, I am no expert in macro-economics, but that trough on the right of the graph pretty much happened all across the stock market — because of the China tariffs, the fed raising interest rates, reports of economic slowdown, and maybe the Mueller investigation, too.
Right at the bottom of that trough we had a meeting with the head of the Clover team. It didn’t go too well. She was obviously distracted and when she was engaged, she was asking very tough, business-minded questions. Maybe it was bad timing, but it was also a reminder of how significant business realities are, each and every day.
In the past, I have heard promising designers, sometimes Creative Directors even, saying things like:
"Money is evil."
"Business is for other people."
Clients...they just don't think like us." (But, of course, they all still want a raise, come review time.)
And it is true, most clients don’t think — or talk — like us. Or real people, for that matter. Imagine if they did.
I mean, I don’t know about you, but as a real person, I often find myself wishing there was more info.
Or, looking for a solution that is more scalable.
And, who isn’t absolutely thrilled when they fall into the correct user segment?
But designers aren’t any better. They are just different. I mean, that must be an awesome Kleenex site!
What I have learned, over the years, is that clients and designers are often talking about the same thing. But they come at it from different angles.
It's like they are speaking different languages. It leads to a lot of disconnects, frustration, lengthy meetings, and rather cantankerous conference calls.
Let me tell you a true story. Many years ago, I was on an hours long conference call to discuss a website with a client. And we were talking round in circles when this happened.
"I want you to uplift the branding quotient," the client said.
"Do you mean make the logo bigger?" one of our designers asked.
"Yes" the client said.
And that is a true story.
It’s a perfect example of where we are talking about the same thing in different ways. And it’s this sort of disconnect that makes it a lot harder for anyone to actually buy or sell work. Therefore, I find my day job is partly to play the role of translator.
As translator, I have spent years helping clients understand designers, and I help designers understand clients. And I have discovered it works like this.
Designers love to create simple, human, 1:1 experiences. They obsess over all the small details, crafting quality experiences that connect with people on a personal, emotional level.
And clients, well, they love scalable, enterprise-ready solutions that are 1 to many. They, quite rightly obsess over how it will make them a gajillion dollars.
But, of course, these things aren’t at odds. They are 2 sides of the same coin, and they have mutual benefit. Each one makes the other better.
It was this realization that has led me to not only be a better consultant to my clients — because I learned to speak their language — but it also made me a better designer — because I learned to understand their business.
The business of business.
It might seem obvious, but design is a tool for making businesses better.
We are not artists. Plain and simple.
At Y Media Labs — where I am the Chief Creative Officer — we have this way of thinking built into our DNA. And every day, we strive to use our superpowers of strategy, design and technology to make a lasting impact.
A lasting impact on the people that use our experiences. And on our clients’ businesses, too.
1 to 1. And 1 to many.
Formerly co-founder of Junior: the Rapid Invention Company, a product design accelerator for big brands, and before that, Executive Creative Director for AKQA, San Francisco, Stephen has over 15 years industry experience working at the top of the game. An accomplished product design and innovation leader, he created breakthrough work for brands such as Activision, Anheuser-Busch, Audi, eBay, Jordan, Levi’s, NVIDIA, Verizon, Visa, Xbox, and YouTube to name a few.
We were out of place no doubt. A Silicon Valley-based, technology-driven, design and innovation agency surrounded by some of the most elite marketers and advertisers in the industry, if not the world, in midtown New York City at The Times Center.
But then we started talking. The room quieted, and the audience was suddenly captivated.
Check out our presentation from CCO Stephen Clements and product strategist Shayna Stewart. Together they illuminated something that related to all parties in the room, whether representing an agency or brand — design is a tool for making businesses better. We're not creating art for art's sake. We're creating to make businesses better.
That idea is rooted in our DNA at YML, and it's how we make lasting impact.
YML's 2019 Women's Day T-shirt designed by Sadhvi Konchada
Last year at this time, YML created some fun Women’s Day T-shirts for the team. Being really passionate about the topic, I decided to take the initiative to design this year's tees. Being born and raised in India and now working in such a multi-cultural workplace in the United States, diversity is a topic I hold close to my heart. I knew that was the theme I wanted to explore. As I was in the process of designing it, I shared a draft with our Chief Creative Officer, Stephen Clements, who posed a question which really made me think. He said, “Diversity is a topic so big, so vague, and so well explored by other people. Ideas begin with insights. Otherwise they aren’t really ideas. Insights challenge people. They surprise them. They make them think about an old problem in a new way. What’s your insight?” I paused. I thought. I dug deeper, until I found my insight that empowered me to write this poem —
“There are a world of problems that women have to deal with. Differences between them shouldn’t be one of it.”
The war with patriarchy has lasted centuries,
And the world still fails us.
She and I might have our differences.
The color of my skin,
The language of her words,
The music that makes our bodies sway,
Our childhood memories so unlike.
Our struggle so alike.
The world has failed us both.
Someone speaks over her,
She says “Sorry” before speaking her mind,
She’s paid less than she deserves,
The world has failed her.
Her heart beats fast as she walks alone at night,
She changes her path to avoid passing a group of men,
The world has failed her.
She’s told what to wear,
What to eat,
What to do,
How to be.
The world has failed her.
This is just the tip of the iceberg,
Of how the world has failed us.
You see our struggle and do nothing,
You have failed us both, too.
This is not your fight.
This is not my fight.
This is our fight.
To make the world better.
To stand with her.
To stand up for her.
To fight for her.
To empower her.
And can I ask,
If I’m in need,
You do the same for me?
Sadhvi Konchadais a UI/UX designer at Y Media Labs. She enjoys telling stories, most times with color, and sometimes with words.
In the digital industry we all aim towards the aspirational, yet colloquial goal of innovation. Yet more and more, true innovation is harder to come by. We believe this is due to the way roadmaps are prioritized. The frameworks that product leaders use for prioritization tend to overemphasize the manipulation of features that are already in place. The metrics, Level of Effort (LOE), Scale, and Customer Value, used in the framework do not favor injecting any new concepts.
It favors optimizing existing concepts.
Recently when working with a client to prioritize ideas within their roadmap, we created what is called the Innovation Index. In this case, our client and team brainstormed on all of the possible ideas for a second phase of a recent app that was built.
The problem we ran into ranking all of the ideas was a lack of data to support one feature over another as the first iteration of the app was yet to be launched. Therefore no data had been captured and we were too early in the process of vetting more ideas to gather consumer feedback. From our need to evaluate ideas objectively in lieu of usable data, the Innovation Index was born.
To create this index, we first did some research toward an objective definition of innovation. We landed on two important pillars:
From there, we took the list of ideas generated by our client and our team and researched if any of these ideas already existed. If the idea didn’t exist, we gave the idea a score of 5. If it did exist we ranked the idea with a score of 1-4, heuristically representing market saturation. Therefore, 5 was a completely distinct idea and 1 was an idea that has a high market saturation.
Secondly, we ranked the ideas on if the proposal was a more efficient way of solving the problem. If the idea was ranked as a 5 in the market saturation scale (meaning a completely distinct idea), it automatically got a score of 5 for being more efficient. Otherwise, we evaluated the ideas if they were more efficient approach to solving a problem that has already been solved by someone else.
That’s it, the Innovation Index is made up of two scales: Market Saturation & Efficiency. These concepts mapped back to the pillars of innovation, which helped focus our next steps on differentiation as opposed to directly competing with existing products. In the end this exercise prioritized our product planning to helping an underserved audience of about 18.6M people.
After using the Innovation Index in a roadmap with no data, I started to think about how it would apply to a roadmap with data already in place. I discovered that without including the Innovation Index, the metrics used to prioritize a roadmap (LOE, Scale, and Consumer Value) were actually working against innovative ideas. Here we dive into just how this plays out:
Level of Effort
LOE asks how easy is it to bring an idea to market. The reasons for an ‘easy’ LOE estimate is slightly different for each team, but both result in prioritization of ideas that already exist.
If the idea is deemed easy by the technology team, that means they either have already done this before or that there is significant documentation already published. It also is indicative that all data elements are readily accessible. Typically, data elements that are readily accessible are already in use -- i.e. the idea is an optimization of an existing feature.
If the easy LOE estimate comes from the design team, it means that a proposed feature will likely have a small impact to the ecosystem. Designers spend less time when they do not have to think through the way that users move through the experience. When they do not have to think through the experience, that means they are manipulating or adding something to an existing page. This type of one-dimensional change is typically not symptomatic of building a new, innovative idea. Therefore an LOE of Easy and even Medium are deleterious to innovation.
Scale measures the potential number of users reached by the idea. If it’s high, then it gets prioritized over a niche solution. However, when you think about some of the most innovative brands today like Amazon, PayPal, Etsy, and Tesla, they all started by servicing niche markets. Often when innovative technologies and ideas are first created, the full breadth of implicated use cases are still unknown. In the case of PayPal, they worked from the insight that it was very challenging for auction houses (a small but extremely active part of Ebay’s user base) to collect mobile payments. PayPal was born from this insight. Ten years later, it’s rare that you find a retailer that does not support purchases through PayPal.
Augmented reality is another recent technology that hasn’t benefited from publicly scaled use cases yet, but we see companies like Google making significant investments. There’s value in testing early and learning fast, if you encounter an idea that may be small scale but is potentially innovative. I would recommend prioritizing it and position it to leadership as a learning opportunity for the team.
This metric is our most vague as it has the potential to be defined differently across multiple Indexes or use cases. We can’t completely rule out that this metric in some cases can be aligned to innovation, but in most cases I see that it is not.
Typically it is discovered through user validation or market research. CV often goes against innovation for two reasons:
The first - you may not be talking to the right group of people. In a recent study, we identified a target persona which clearly did not want certain innovative ideas because they weren’t geared towards that particular persona. This is also a factor when you have extremely small sample sizes. The users you are talking to just may not see the value of the idea. Second, I see studies that outwardly ask users what they want, what could be improved upon. This is important to do in order to find major usability issues, but it’s not the metric that will get you to focusing on innovation. It’s best to use a metric that prioritizes building a prototype of innovative idea that solves a problem that the users didn’t know they had. Then, subsequently present the prototype to potential users (pending you feel confident in your sample) to get feedback on usability. This methodology is better than asking users what they want as a means to prioritizing what you build.
Steve Jobs epitomized this very thought and opined -
Over the years the conversation within the creative realm, especially around design, has blurred as the industry reaches to explain the differences between the capabilities, process, and expectations of design. Our work has transformed further with the growth of digital technology. Today, we can we do anything we dream up. Fantasy is now reality. With this in mind, companies are looking for inventive ways to differentiate themselves from equally digitally savvy competition.
The latest trend is an emphasis on Customer Experience -- which we define as the relationship between an organization and its customers throughout the relationship lifecycle, delivering on the individual’s expectations in each moment of the journey.
Moments can be classified as an interaction with a product, the look of the application, or even a conversation with a call center representative. Basically, any direct or indirect communication with an organization will define how the customer experience is delivered.
Now, how do you design for a better Customer Experience? The design industry has aesthetics, interactions, experiences, and services -- typically conflated to align with job postings, client request, and the like. However, as a product of craft, it is critical first to recognize their functional differences.
Interaction Design is the detailed design of how users interact with a single touchpoint comprised of features.
Experience Design is the combination of interactions across multiple touch-points within a user’s journey.
Visual Design is the balance between aesthetic elements, aimed towards improving/enhancing the brand, and guiding users through the experience.
Service Design is the strategic connection of experiences across user journeys to create seamless user transitions.
Each design practice has its own set of research activities and methods to achieve its stated goal. Each holds a valuable and necessary place in the design process to be successful. One practice cannot replace the other. However, when stacked together they become an unbreakable offering for the Customer Experience.
Still with me? Hopefully, we’ve clarified some of the structure for success.
Service Design is so much more than a buzzword though. Lately, it’s been defined as a method of design-thinking, an activity to sell-in a better Customer Experience, or a process to showcase the connection between an experience and backend technologies. Designers might say it’s the combination of these things plus so much more.
In our view, Service Design looks at the entire ecosystem of an organization, both front and backstage interaction points, across the lifecycle of the Customer Experience. Having a clear view of the entire operation that makes up the organization and everyone involved will allow a design team to ideate against opportunity spaces and create a one-of-a-kind service.
Service Design isn’t exclusively digital either. Most services will have an element of both physical or human interactions. Digital can be the connection between the customer and these experiences. Below are some reasons companies should leverage service design and the methods to support it:
Bridge the gap between the silos. Often, organizations aren't considering how an experience fits into the current-state journey and affects others who deliver on the service. Other times, it can showcase what’s currently being worked on, successes and failures, and even possible obstacles.
Design together by being together. When running workshops, bringing people together from across the organization allows them not only to learn from each other, but more importantly to meet for the first time, put a face to a voice, and form relationships IRL. Additionally, working together increases the speed of delivery since everyone is on the same wavelength (and timezone).
A helpful tool to popularize. Being able to view how future experiences work in harmony with both the current and future state of a service showcases the impact and projected results -- arming clients with the information to demonstrate the potential of the service.
Now that we have a shared understanding of what Service Design is and why to use it, let's talk about what it takes to execute.
McDonald’s Big Mac has its’ special sauce. Coca-Cola Classic has its’ secret recipe. Service Design has blueprints. To illustrate, designers use the method of service blueprinting to document the findings and propose suggestions as well as concepts to support the conclusions. Service blueprinting is just one method of many in a designer’s toolbox. However, when combined with the right design research activities, ongoing collaboration, and sound methodologies, I’d argue it’s the most useful artifact a design team can produce.
A service blueprint is the combination of experiences that explores the relationships between business goals, emotions, mindsets, pain points, touch points, and technology ultimately creating a holistic view of the current system and a shared vision of the future. This future vision aims to showcase every experience needed to deliver on the service that meets, and exceeds, the demands of the users.
Think of it as professional sports. Consider the relationship of fans watching a game and all that goes into making it happen. The players, coaches, field, uniforms, announcer, and Jumbotron are all considered the front stage. This is the first-hand experience of the fan.
The professional league, team’s owner and front-office, athletic trainers and team personnel, venue staff and vendors, camera guy for the kiss cam, etc. could be considered backstage in that they all are critical to the experience of that fan but might not be a primary interaction.
However, there’s a lot more that goes into making the event unique and might be considered more important to the fan’s experience or even than the game itself. Service Design requires investigation and consideration from the moment this person became a fan of the team. Explore the implications of the fan’s decision to purchase a ticket to this particular game and who’s else is attending. Suggest how the fan will get to and from the game and all the activities done before kickoff. Allow the fan to have quicker entry into the venue. Help the fan make the right choice on what to eat. This doesn’t stop at the end of the game either. By delivering a better customer experience the fan will have a reason to keep coming back and will tell all their friends about the experience.
This comprehensive view of the future is critical for organizations to align across leadership, business functions, and technology stakeholders setting a solid foundation to work towards collectively.
With all this said, service design and the method of blueprinting is not required for every client. If the client is expecting a defined solution from a blueprint, they may be sadly disappointed. What the client will get is a series of validated concepts that their organization can deliver against for the foreseeable future -- each with moments that deliver against all user demands and expectations. When the client starts to implement a blueprint, remind them of the importance of experience design and the research methods used. It’s not another round of research, going deep into that particular experience to understand specifics.
Clearly, defining the client request will direct you as to whether service design and blueprinting is the right practice to leverage. Service design is built around the value in research and the knowledge gained. Trust in the findings and insights is hard however. It can lead to some pretty tough conversations with organizations around misalignments, conflicts of interest, and weak links on a team. If not everyone is on board, it’s not going to be a fun time.
Everything in design has its place and purpose. You’re not going eat McDonald’s for an anniversary dinner nor will you mix Coca-Cola with a nice glass of bourbon.
One thing to remember: A service blueprint is just a glimpse into the future and needs to be treated as a living document that can be revisioned, changed, and expanded on. Technology changes everyday in ways that can help to deliver more unexpected and delightful moments to users. The need to adapt accordingly must be baked into the service blueprint.
With the foundation set, it’s much easier to make decisions on how to approach new initiatives. If done correctly, the service blueprint will showcase gaps, both high and low, in the current service, and beyond the proposed solutions, to produce a long-term roadmap outlining the opportunity and timeframe needed for success.
One of the best was a cartographer, fresh out of college — a cartographer is a map maker, if you don’t know. He was a Frenchman, lovely guy, and I remember his interview well. He said there are not a lot of opportunities in the map making world, but it was his passion. He was a talented designer, his maps were beautiful, and he knew how to code. A project he showed me was an interactive map of Afghanistan and Pakistan, showing drone strikes and the estimated number of casualties at each location. He had sourced the live data from public records, and turned it into a human story. It was very moving. I was blown away. Very humbly he asked, “What could a map maker do here, at a digital agency?” I had to think for a minute, but my answer was “We make maps of the internet.” Sure, it was glib, but it sparked his imagination and the conversation turned to mapping the abstract realm of the worldwide web. He became one of the best UX and systems thinkers I have ever met. He could visualize the tangled mess of connections, user journeys, data points, etc. and redesign them with a simple precision that made me want to cry.
Over the years I have hired many folks with different strokes: architects, fashion designers, industrial designers, even one guy—an embedded programmer—who made parking meters. And they all taught me a valuable lesson: amazing talent can come from anywhere, all they need is a compelling portfolio and a chance to tell their story.
Cool right? Here’s how.
At YML, before we consider interviewing anyone, we look at their portfolio—comparing it to all the other candidates’. A portfolio is your calling card—it should not just show what you have done, but what you can do, what you want to do. We have all seen plenty of portfolios and have a pretty quick read on good vs. bad ones. A good portfolio shows work that’s ambitious and inspiring, and very well executed. Thoughtful, beautiful designs, process breakthroughs, clever ideas, and slick interactions, all jump out of the screen. As do glaring errors, typos, thoughtless designs, awkward process decisions, unworkable interactions, etc.—these will all get a candidate blacklisted, struck off the list of potential hires. Great work is important, but an exceptional portfolio site should be a good user experience too. Consider the audience: busy executives. Trust me, we don’t read much, so don’t write much. Let the work do the talking, focus your words on big, significant ideas, compelling points, quotes and callouts. Curate only your best work, because one bad project gets an instant rejection. If in doubt, don’t show it, or better still, dig deeper and make it great.
Additionally, we prefer real portfolio sites. Dribbble is okay, Behance too, but if you’re shooting for a senior position, you will need a bit more vision, process and/or storytelling to support your work. At best, Dribbble can be very good place to show your interaction and visual design—but at its worst, it’s superficial eye candy. For more on this, read this fantastic article, The Dribbblisation Of Design.
Okay. So that’s how to get a foot in the door. What’s next? The interview, of course. Here’s a mental checklist we apply to interviewees, when we meet them:
1. Energy: Do you bring it? Do you take it? For me, this is the number one criteria. I can feel it when I meet someone. Are they inspired? Do they inspire? Is this a job or a lifestyle? We work in small teams, oftentimes in small rooms, with big clients. People who bring energy, who inspire others to do great work, they are the magic ingredient for this model.
2. Empathy: Do you have feeling? Can you connect? We create products and experiences for people from all walks of life. We must understand them first, so we can design something they want. Empathy, listening, and responding is key to the design process. And it’s important in how we work together as well—we, of course, don’t tolerate jerks—even if they are talented.
3. Culture fit: Do you fit in, but add something as well? We have a fantastic, inspiring, collaborative, nurturing culture of talented grownups, and we want to preserve it and enhance it. However, we aren’t seeking uniformity. Diverse backgrounds, approaches and opinions are welcome, and help make our work and our culture better.
4. Presentation: How well do you communicate your work?
We look for excellent communicators—both verbal, written and visual—ultimately entrusting them to present our work to clients and internal stakeholders. For entry and mid level positions, just going through some portfolio projects will do just fine — but for senior hires, a presentation is required. A good presentation is a clear articulation of the problem, and the path from strategy to design.
5. Experience: Do you know how to get things done? This is definitely not a question of length of experience, which is irrelevant. Instead, it’s an assessment of the kind and quality of experience—a candidate’s understanding of the tools and processes, pitfalls and opportunities, common in the job. Inexperienced people won’t hit the ground running, or worse, they can misdirect the process, waste time and resources and negatively affect the quality of our work.
6. Attitude: Are you all in? Do you want it?
Skills can be taught. Attitude can’t. In an industry that’s always changing, someone with a good attitude looks for challenges and is constantly thinking of ways to improve and progress. We want people with positive attitudes that are upbeat, eager, and solutions focused. We find they thrive on feedback, embrace change, and they own it with a smile.
7. Impact: Will you make a difference? Last, but certainly not least, we want people that we know will have an immediate, positive, lasting impact—on the work, on our clients, on YML. We’re building a world class design team, looking for complementary skillsets, backgrounds and approaches. We don’t want to hire the same kind of designer over and over again. We look for folks who will make our team greater than the sum of its parts.
One more thing
We definitely do not look for an Ivy League education—or any education for that matter. We simply don’t care if you went to Harvard, or never went to school, never studied, come from an underprivileged background, were homeschooled, or are completely self taught. So long as you do great work, have the right attitude, and know how to get the job done, you’re in.
And that’s it. If this sounds like you, or someone you know, get in touch. Also, any interview goes two ways. If you have thoughts on what you look for in an interview, we’d love to hear them.
Can software be beautiful? Certainly a great looking and intuitive interface which enables people using the app to accomplish their tasks with little effort and minimal friction could be called beautiful. Software developers are privy to another kind of beauty: The inherent beauty in well-constructed software that makes it easy for a software team to effortlessly integrate disparate pieces into a compound whole. Well-constructed software can be appreciated much the same way that a beautiful painting, a sculpture, a building or a piece of music can be appreciated.
But beautiful software is not necessarily great software. Ideally, great software is great because it empowers people. It can give them what could be described as superhero-like capabilities. We definitely want people to feel like superheroes when using our software, but we want them to identify more with Superman or Wonder Woman than with The Greatest American Hero. In other words, they should be able to achieve great things, but, unlike The Greatest American Hero’s Ralph Hinkley, they should not be rendered powerless without a sufficiently detailed instruction manual.
For software to empower people in this way, it must be designed from the ground up to be anticipatory. Great software often feels omniscient. It makes the difficult look easy, even though, ironically, making the difficult look easy is really quite hard. As Steve Jobs is said to have put it, “Simple can be harder than complex. You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”
As software developers, we must also strive to anticipate the events and conditions our software may be forced to deal with if we wish to create great software. The wireframes or mockups we receive from designers tend to focus on the so-called “happy path”. These are the things that the people using our software will hopefully be doing most of the time, and they include such things as writing great novels, sending money to friends, depositing checks, or collaborating and communicating with colleagues. These concepts are the things people would mention when describing our software to others.
Other events require error handling and recovery. These are the things which result from software being used in the real world. They are expected, but, hopefully, infrequent. Network requests may fail. The device may run out of memory or storage capacity. Great software accounts for these scenarios and provides a fluid though perhaps degraded experience in spite of their presence.
Finally, there are exceptional events. These are failures from which we cannot recover programmatically, and include hardware failures or assumptions about external dependencies which have held true in the past but which have since changed and upon which we can no longer rely.
Software is best constructed by taking the existence of these types of scenarios into account from the beginning instead of “bolting them on” later. To me, great software must be robust by design.
The benefits of robust-by-design software
Software that is built from the ground up anticipating the various ways things can go wrong is more likely to be of the necessary quality and to deliver a rock-solid user experience. Robust-by-design software will also be less likely to crash or behave in an unexpected manner in the course of operation.
In addition, the resulting software will provide a better user experience. Things will be more fluid, and errors, when they undoubtedly occur, will be handled smoothly. The app won’t unexpectedly jump between screens or overlay elements from the anticipated “good state” with elements from the “error state”. They won’t show blank screens or display a spinner ad infinitum. Furthermore, it will be easier to avoid these unwanted situations.
The app will also be more secure as it will not crash as often or continue to operate in an unexpected state. The software will also safely clean up after itself in these situations (i.e., close open files or overwrite memory to remove sensitive information) thereby also increasing security.
The app will also be easier to maintain as the code will be better constructed. It will be less likely that other developers will cause software to regress as these scenarios will be more explicit in the code. The app will also be easier to test as it will be structured as a collection of components, thereby helping with separation of concerns.
Creating robust-by-design software requires us to think about as many of the various scenarios that we can to make sure we cover all the things which can go wrong. This is a skill that software developers must hone. Modern software is quite complicated, and there are often many things that can go wrong at any time. But, like any skill, one can get better at anticipating these scenarios. The more we practice this approach, the more scenarios will be known to us and the better we will become at thinking about new ones.
Why being a 'defensive pessimist' matters
I often tell my colleagues that I spend more than 90 percent of my time working to make sure the software I create handles those scenarios which occur less than 10 percent of the time. A lot of that time is spent trying to find those scenarios which are not on the happy path. Thinking of those scenarios can be hard, making sure the software is able to handle those scenarios well is easier (though not easy). Making sure the software operates well in the presence of those scenarios is made easier when the need to do so is taken into account from the beginning.
Obviously there’s no expectation or requirement that we think of every possible thing that can go wrong, but the more such scenarios we think of the better. It makes it more likely that the scenarios we had failed to think of may be covered by the scenarios of which we did think. Furthermore, any new scenarios will be easier to incorporate later as we already have support for alternate paths and do not need to bolt those on well into the development cycle.
Another way to say this is that, as software developers, we should think about our software through the lens of “defensive pessimism”. Defensive pessimism is a cognitive strategy whose practitioners work through all the things which could go wrong and plan accordingly. According to a New York Magazine article on defensive pessimism, while it might seem better to expect things to go well and not worry about negative outcomes, it most certainly is not better. According to research conducted by Dr. Julie Norem, a psychology professor at Wellesley College and a leading researcher of the defensive pessimism concept, defensive pessimists actually benefit from all the worrying they do as they approach situations more fully prepared.
That’s exactly what we want to do when developing software. We could be optimists, and assume that everything will work out okay, but we will quickly find that that’s unrealistic in practice. We could be pessimists and assume everything will always go wrong, but then we’d never write any useful software.
Instead, we should strive to be defensive pessimists who create beautiful and useful software that is robust enough to remain beautiful and useful when the inevitable happens and things go wrong.
Software which anticipates our next action can feel magical. As software developers, we can create a more solid foundation for our software and make it more likely to achieve that vaunted status if we work on anticipating all of the various scenarios it may have to deal with and incorporate that support from the beginning.
As the saying goes, the devil is in the detail. In other words, the details are from where that beauty comes. Getting these details right will make it more likely that the software we create is in fact great software.