Scaling Research by Activating the Frontline

Innovation is the name of the game in UX Research; we are often being asked to find creative ways of gathering insights from end users with smaller teams and even smaller timelines and budgets for recruitment. As we continue to seek out ways of reaching people, there’s an often untapped source of research insights who are working with our target users day in and day out: frontline employees. This is a key strategy, particularly when dealing with any protected or vulnerable population, such as patients or children, who are often very difficult to access for a variety of (very good!) reasons.  

Frontline employees are the boots-on-the-ground people who are interfacing with users every day. Depending on the industry and problem space they might be receptionists, call center employees, nurses, cashiers, etc. They spend their time putting out fires and hearing directly from customers about what’s working and what isn’t. 

So, where do I start? 

First things first, activating any group to be part of research often starts with building relationships. Frontline employees are busy people who are usually being managed by busy people who are often concerned about preserving their teams’ bandwidth and protecting their time. To reach them you’ll need allies, and allies start with relationships. Start by getting to know their managers and team leaders (or whatever the equivalent role is). SME (Subject Matter Expert) interviews can be a great method here, both to learn more about pain points and also to help people understand that you’re there to help them and their teams with their jobs. Research is a way of letting people be heard, and that’s a valuable thing you can do for them.

Once you’ve built a relationship with the managers and team leads, you can start asking about getting access to their teams who are interfacing directly with your target audience. 

I’ve built relationships…now what? 

Now that you’ve gotten access to the frontline employees, there are a couple different research methods we suggest considering. This is your chance to get the inside scoop about what kinds of pain points exist for users and employees, what kinds of tools they use, what kinds of ideas or suggestions they have for improvement, and more. Keep in mind that while research can be hugely impactful, if you’re not careful it can also be very time-consuming and extractive – meaning it takes knowledge, expertise, energy, etc from people without giving anything of value back. So consider how much bandwidth, time, and energy people have when planning your research, as well as what you may be able to give back to them. 

Two non-extractive options we’ve leveraged in the past are: 

Diary studies 

Diary studies are an unmoderated research method that asks someone to keep a log about their experience at certain times or in response to certain triggers such as after speaking to a customer or using a piece of software. You can ask people to take photos of key moments, record their emotions or activities during or after certain events, or provide reflections on changes they might have made or ideas they have. Diary studies are a great way to turn your frontline employees into researchers themselves by having them think about and interrogate their own workflows, softwares, and scripts when interacting with end users. 

Diary studies can be very impactful because they are straight from the participant’s unfiltered perspective and are designed to happen in the moment, so they are less likely to be misremembered. Some drawbacks include people forgetting to fill them out at the right times – or at all, especially if they are busy – or providing unclear information that is difficult to follow up on and get additional clarity. 

Passive prompt wall

This is a good method to use if your participants all share a physical space – such as an office  or breakroom. Setting up an installation such as oversized post-it papers with markers and prompts that participants can fill out on their off time can provide you with first-hand insights about how people are feeling, what they’re hearing from users, and what ideas they might have for how to improve the products or services they deal with day-to-day. 

Some watchouts to this method is that you need to be mindful of how you word your prompts so they are easy to understand and you’re surfacing relevant information. There’s always a risk of people responding with unserious, off-topic responses with unmoderated forum-type research, so have a plan in place to vet some of the more suspicious answers you receive (possibly from those SMEs you interviewed earlier).  

I’ve gathered my research, what do I do now? 

Congratulations on gathering research from frontline employees! Now it’s up to you to synthesize your insights and pull out the necessary takeaways. Consider conducting 1:1 interviews or focus groups to follow up on interesting themes and patterns. If you are developing concepts or prototypes out of your insights, frontline employees can be a great group of people to start gathering some validation on your ideas. 

Research is an ever-evolving practice, and finding new ways to learn about what works and what doesn’t can sometimes feel like a moving target. But if you build relationships early and expand your participants to include not just those experiencing the pain points first hand, but to include the people who are experiencing them second-hand as well, you can capture more data in richer and more informed detail than ever before.

Interested in how you can activate your frontline employees? Drop us a line!

Stretching Lean Budgets Strategically

Every business hits times when the budget gets tighter — it’s an inevitable part of being in it for the long haul. For a lot of industries, their short-term futures are a bit unpredictable right now, leading to questions about how to best set up their business to weather any twists and turns. 

In the face of uncertainty, many organizations scale back as quickly as possible to alleviate the pressure on their overhead. While understandable, rushed decisions can sometimes be short-sighted decisions, making it harder for those businesses to rebuild once lean times have passed. 

Just as strategy is important in times of growth, it’s also key in times of reduction. Whether you’re the one facilitating trims or absorbing them as best you can, read on for our take on putting strategy into leaner times. 

Center existing customers

While you can’t completely lose sight of expansion, the math is simple — it’s much less expensive to retain an existing customer than it is to acquire a new one. In moments when efficiency with available budgets is essential, the best move is often to invest the majority of your efforts in customer retention through the products, services, and/or tech systems your teams may already be running. This means maintenance, yes, but it also means uncovering new ways to provide benefits for them, ensuring they will return to you. Growth is important, and should not be forgotten, but it’s important to balance such endeavors with true investment in preserving what’s working for you today. 

Step back and learn, and go “lightweight”

We’ve seen huge payoffs for organizations that take budget setbacks as opportunities to zoom out on their business and take a closer look at their products and services. What makes the most sense to focus on in this new climate? Where is infrastructure/development urgently needed, and where can it wait? Which projects are going to best prepare the company for when the market forges ahead? In all likelihood, a change affecting your business also means changes for the partners and clients around you. How might these circumstances affect your short- and long-term success strategies? 

In lean times, it’s also very important to get to the learnings quickly so you can pivot if needed. Consider stepping back to ask what the scrappier, more agile version of your process might look like. You want to be investing efforts in the right places, so getting that feedback loop on a quicker cycle is key.  

Consider how projects are shelved

When an organization tightens the belt, it’s almost certain that internal priorities will need to shift. This often involves shelving longer-term projects, and refocusing resources to work on lower-hanging fruit that will generate income in the short term.

Once the worst of the budget drought has passed, though, most organizations will want to pick up where they left off on those shelved projects. The problem is that many times, the  employees with the institutional knowledge to restart those projects have been shuffled around in a reorg, laid off, or have left the company out of fear for the business’s future. Countless times, we’ve seen work either need to get redone because there was not enough context to pick it back up again — or, get restarted from scratch only to realize midway through that much of what they’ve worked on had already been done.

While it may not be realistic to avoid any kind of turnover or layoffs, consider using the lower-budget times to thoroughly document any mid-flight work that needs temporary shelving. This includes the work done to date, by whom, what was learned and the impact moving forward, and what still needs to be learned or done. Taking the time to do this in “quieter” times is hugely important to not wasting effort when your business is finally in recovery and expansion mode. 

Judicious use of outside help 

It’s hard to justify spending any money when your budget is limited. That said, given the overall fear of making the wrong decision that can pervade stressful times, it can be helpful to call on outside eyes for perspective and strategic support. Things like day-long prioritization workshops, short research sprints, or new tech trainings can be sensible ways to spend less money but still get a lot of impact and keep initiatives moving forward.

Another smart way to use outside support in tighter times is as short-term personnel augmentation. When you can’t commit to retaining FTEs for each role you need, hiring an agency can be a smart way to access a wide array of skill sets for less money.

Plan like the storm will pass — with the right strategy, you can help make sure it does. And if you’re looking for a partner in weathering that storm, we’d love to hear from you.

Leveraging AI in User Research

Grand Studio has a long history of working with various AI technologies and tools (including a chatbot for the underbanked and using AI to help scale the quick-service restaurant industry). We’ve created our own Human-Centered AI Framework to guide our work and our clients to design a future that is AI-powered and human-led and that builds on human knowledge and skills to make organizations run better and unlock greater capabilities for people. When ChatGPT hit the scene, we started experimenting right away with how it could improve our processes and make our work both more efficient and more robust. 

Given our experience with what AI is good at doing (and what it’s not), we knew we could use ChatGPT to help us distill and synthesize a large amount of qualitative data in a recent large-scale discovery and ideation project for a global client. 

Here are some takeaways for teams hoping to do something similar: 

1. Don’t skip the clean-up. As they say: garbage in, garbage out. Generative AI (GenAI) tools can only make sense of what you give them – they can’t necessarily decipher acronyms, shorthand, typos, or other research input errors. Spend the time to clean up your data and your algorithmic synthesis buddy will thank you. This can also include standardized formats, so if you think you may want to go this route, consider how you can standardize note-taking in your upfront research prep.

2. Protect your – and your client’s – data. While ChatGPT doesn’t currently claim any ownership or copyright over the information you put in, it will train on your data unless you make a specific privacy request . If you’re working with sensitive or private company data, do your due diligence and make sure you’ve cleaned up important or easily identifiable data first. Data safety should always be your top priority.

3. Be specific with what you need to know. ChatGPT can only do so much. If you don’t know what your research goals are, ChatGPT isn’t going to be a silver bullet that uncovers the secrets of your data for you. In our experience, it works best with specific prompts that give it clear guidelines and output parameters. For example, you can ask something like: 

“Please synthesize the following data and create three takeaways that surface what users thought of these ideas in plain language. Use only the data set provided to create your answers. Highlight the most important things users thought regarding what they liked and didn’t like, and why. Please return your response as a bulleted list, with one bullet for each key takeaway, with sub-bullets underneath those for what they liked and didn’t like, and why.” 

Doing the upfront human-researcher work of creating high quality research plans will help you focus on the important questions at this stage.

4. It’s true, ChatGPT gets tired. As with any new technology, ChatGPT is always changing. That being said,  the 4.0 version of ChatGP that we worked with demonstrated diminishing returns the longer we used it. Even though the prompts were exactly the same from question to question, with the input of fresh data sources each time, ChatGPT’s answers got shorter and less complete. Prompts asking for three synthesized takeaways would be answered with one or two, with fewer and fewer connections to the data sets. By the end, its answers were straight up wrong. Leading us to our final takeaway:

5. Always do an audit of the answers! Large language models like ChatGPT aren’t able to discern if the answers they provide are accurate or what you were hoping to receive. It’s also incredibly confident when providing its answers, even if they’re wrong. This means you can’t blindly rely on it to give you an accurate answer. You have to go back and sift through the original data and make sure that the answers it gives you line up with what you, the researcher, also see. Unfortunately this means the process will take longer than you were probably hoping for, but the alternative is incomplete, or incorrect answers – which defeat the purpose of synthesis in the first place and could cause the client to lose trust in you. 

Outcome: Did using ChatGPT speed up our synthesis significantly? Absolutely. Could we fully rely on ChatGPT’s synthesis output without any sort of audit or gut check? Not at all. We’ll keep experimenting with ways to incorporate emerging technologies like Generative AI into our workstreams, but always with research integrity and humans at our center. 

Interested in how GenAI might work for your organization? Drop us a line – we’d love to chat!

A New Way of Understanding Sports Fans

A lot of sports organizations think about their fan base in terms of subscription tiers. Their business strategy is largely about moving fans up those tiers, converting them to higher levels of monetization. Accordingly, they ask themselves questions like: what would it take for a fan to upgrade to a season ticket holder, an ESPN+ subscriber, or a daily reader of sports news? 

This approach makes sense. After all, a company is in the business of monetization. But to get a fan to upgrade, they must first and foremost be engaged with whatever it is you’re offering — be that a product, a team, or the game itself. To bring them up the tiers is essentially to ask them to increase their level of engagement with you. And if you want fans to engage deeply, you have to deeply understand what it is that they want.  

In other words, the better you can understand the crux of a fan’s engagement — how it is shaped, how it’s maintained, and how it grows (or stagnates…) — the better you can cultivate their inspiration to upgrade. Getting to this level of a fan identity requires an intimacy with their beliefs that goes beyond the details on an account subscription. 

A fan-centric view of sports

As mentioned, while there is clear value in analyzing subscription trends, it is inherently top-down and corporation-centric, placing fan behaviors primarily in relation to their monetary value for the company. If this is the key variable by which segments are sliced and diced, it can limit the organization’s ability to surface the most meaningful characteristics and variations that define their fan base. And, subsequently, limit the organization’s ability to serve such needs, and get the very upgrades they are after.

What many sports companies could use is a complementary bottom-up approach to segmenting and analyzing fans. This approach would start by understanding how and why a fan engages in a sport. Is it all about supporting a particular team? Is it a larger appreciation for the sport? Is it about the culture? Belonging? Nostalgia? Hometown pride? Is it about going to games because all their friends do? Starting on the ground to understand attitudinal and behavioral differences across fans can set organizations up to learn something deeper and more important about that fan than their subscribership status — things that ultimately do more to determine how they can serve each segment. 

Stories from the stadium 

In a previous project, a major sports league asked us to overhaul their mobile app. Their goal was to get fans to spend more time on the app so they could generate more ad revenue. When we started doing research on their fan base, we uncovered surprising trends that ended up influencing the league’s overall engagement strategies. For example, there was a significant portion of the fan base who were what we called “adopted fans.” Instead of inheriting a team from traditional family ties, they adopted a new team when they moved to a new state, or adopted one based on its underdog status. As newer fans, they looked to national news for sports intel. Diehard fans, on the other hand, primarily went straight to their local beat reporters for sports news. This stratification uncovered opportunities for the league to serve each group differently and personalize their experience on the app, increasing the engagement opportunity for each group. 

In another project with a major sports team, the avidity level of a fan turned out to be among the most important characteristics to analyze. We uncovered, for instance, a segment of the population we called “tag-alongs” — those who attended a sporting event because someone had invited them. Many of these tag-alongs didn’t know much about the sport to begin with, but loved the experience of going to a live game and rooting for the team. For this sub-group, the atmosphere and amenities at the stadium made a big impact on their likelihood to return. Once this group was uncovered, the team was able to do more to convert these tag-alongs into fans in their own right. 

Doing the “field” work: meeting fans where they are

Let’s assume your organization has bought into the value of uncovering the unique fan archetypes within their population. What comes next? 

One important way to research fan attitudes is, of course, going to games. Observing fans interacting with their sport or team, and also observing them in community with one another at games, is not to be overlooked. 

But fans are not only fans during sports games. They are also fans when they are reading the news, keeping up with players or stats or the league at large. They are fans when they’re out at a bar with friends and see their favorite player’s jersey on the wall. They are fans during off-season as well, even when there aren’t as many ways to show it. 

Understanding a fan means understanding the rhythm of their fandom, the ebbs and flows in addition to the moments of peak excitement and engagement. How they stay connected to their team or sport when games aren’t going on can be just as informative as how they behave during a game. There are cadences to the experiences of different sports fans, and understanding that richness of detail is key to understanding how their needs can best be met. We’ve found that understanding these harder-to-capture aspects of fandom require different research methodologies — for instance, perhaps you need diary studies to check in on fans during off-season or lulls in action. Perhaps you need to post up in a sports bar and catch people stretching out the emotion of a game by connecting over it. Perhaps you need data points from people as they read sports news throughout the week. 

Sports mean a lot to people. For some, their fandom is a key piece of how they see their own identities. Taking the time to understand these segments with multidimensional attributes with care can pay off greatly for fan satisfaction as well as overall engagement metrics.

Looking to better understand and serve your fans? We’d love to hear from you!

Great First Impressions: Leveraging UI for Critical Product Moments

Your user interface is your digital first impression. And as we all know, a good first impression can change everything. 

UI design is often thought of as the creation of pleasing aesthetics. While this may be a part of what we focus on, the broader concern of the UI designer is to manage how someone feels while interacting with your content or page. Such feelings will translate, both consciously and subconsciously, into how people feel about you and your brand. Even minor confusion or frustration about what to click or how to input information can erode trust — who’s to say working with your business won’t be similar to using your website?

With ever-higher expectations for our digital world, and such high stakes, UI should not be an afterthought. Grand Studio’s UI team has compiled some tips for any teams taking on a new — or evolving — digital product. 

Tip 1: When everything calls out for attention, nothing calls out for attention

In an effort to get important components noticed, many designers try to crunch a lot of content above the fold (at the topmost part of a page, before needing to scroll down). Unfortunately, this most often ends up backfiring. Even if your user can see all the pieces in one glance, you risk overwhelming them, and generating confusion about what they should pay attention to.

We recommend placing one (or maybe two) areas of focus up top, sending the rest more into the background. Use color, contrast, size, and placement on the page to guide a user cleanly from primary to secondary focus. White space is your friend. 

Tip 2: Your top priority is helping your user know what to do when

It may sound obvious, but it’s far too easy to get caught up in components of the design and lose track of its primary purpose — helping the user take the action they need to take on the page. Consider the user’s paths through the page, and make sure they have everything they need to complete their journey. Never let your user wonder things like, “is this text interactive?” “what does this icon mean?” or “how do I fix the error I’m seeing?” 

At its most basic level, a visual interface is a means to communicate efficiently with your user so you can guide them through what they need as elegantly as possible. You want your UI to be a good communicator.

Tip 3: Everything that can be consistent should be consistent

If we think about a visual interface as a means of communicating with the user, it is critical that we are always using consistent language to do so. Though it may sound minor, using a color to mean one thing (e.g. red button = “remove”) at one point and another thing (e.g. red = “edit!”) at another point can be cognitively taxing on a user. As you establish your visual language, make sure there is always just one meaning attached to any given visual component, whether that’s an icon, a color, a word, or a button. 

These things not only save your user time, they help the user feel better on your page. Smooth sailing = trust generated. 

Tip 4: Consider your breakpoints, and don’t skip testing on the end device!

While of course there may be slight differences between different breakpoints or devices, there should always be visual and functional similarities across them. The idea here is to create an experience that is seamless and consistent for everyone, regardless of the device and its size. 

To create the type of layout that will be clear and usable no matter the size of the window, we recommend designing for breakpoints — points at which a design will “break” if you stretch your browser window wider — to ensure all of the page’s elements will nicely fit the available screen space, no matter the size. Considering breakpoints will naturally optimize content for viewing on different devices (even ones that haven’t been invented yet), ensuring everyone gets a clear and usable view.

That said, it’s still very important to view your design on the end device to be able to visualize it in a realistic way. You can do this by downloading your design and opening it up in your browser or device, like a mobile phone. Seeing your design in context with the device will ensure that elements or text are sized correctly and comfortably.

Tip 5: Accessible designs are better for everyone

Making sure your design can be used by as many types of people as possible not only increases the number of people who can interact with you, it can also help you find and resolve points of confusion that go on to help everyone. Accessibility isn’t icing on the cake; it is a critical component of good design. 

For example, take alt text for images, or text that describes what is happening in an image. Alt text’s primary function is to help those with visual impairments hear through text-to-speech what each image contains. But alt text can also be really helpful for Google searches, and helping people find content on your page. It’s invisible for those who don’t need it, but there for people who do. (For more on this, check out our blog post on accessibility.)

At Grand Studio, our UI team does way more than “pixel push.” Because we see UI as a critical part of a holistic design practice, UI is integrated into product strategy, UX, and even design research. We know that the best user interfaces come out of a deep understanding of not just UI best practices, but an understanding of the particular context and goals of each client we work with. When you’re making a first impression with your users, nothing could be more important. 

Got a user interface project? We’d love to hear from you?

Human-Centered AI: The Successful Business Approach to AI

If AI wasn’t already the belle of the tech ball, the advanced generative AI tools surfacing left and right have certainly secured its title. Organizations are understandably in a rush to get in on the action — not just for AI’s potential utility to their business, but also because, more and more, demonstrating use of AI feels like a marketing imperative for any business that wants to appear “cutting edge,” or even simply “with the times.”

Sometimes, rapid technology integrations can be a boon to the business. But other times, this kind of urgency can lead to poor, short-sighted decision-making around implementation. If the technology doesn’t actually solve a real problem — or sometimes even when it does — many don’t want to change their process and use it. All this to say: a bitter first taste of AI within an organization can also harm its chances of success the next time around, even if the strategy has improved. 

At Grand Studio, we’ve had the privilege of working alongside major organizations taking their first high-stakes steps into AI. We know the positive impact the right kind of AI strategy can have on a business. But we’ve also seen the ways in which pressure to adopt AI can lead to rushed decision-making that leaves organizations worse off. 

Our top-level advice to businesses looking to implement AI: don’t lose sight of human-centered design principles. AI may be among the most sophisticated tools we use, but it is still just that — a tool. As such, it must always operate in service of humans that use it. 

A human lens on artificial intelligence

When implementing AI, it is tempting to start with the technology itself — what can the technology do exceptionally well? Where might its merits be of service to your organization? While these may be helpful brainstorming questions, no AI strategy is complete until it closely analyzes how AI’s merits would operate in conjunction with the humans you rely on, whether it be your employees or your customers.


In our work supporting a major financial organization, we designed an AI-based tool for bond traders. Originally, they imagined using AI to tag particular bonds with certain characteristics, making them easier for the traders to pull up. It seemed like a great use of technology, and a service that would speed up and optimize the trader’s workflow. But once we got on the ground and started talking to traders, it turned out that pulling up bonds based on tags was not actually their biggest problem. AI may be a golden hammer, but the proposed project wasn’t a nail — it only looked like one from far away. 

As we got more clarity on the true needs of these traders, we realized that what they actually needed was background information to help them make decisions around pricing the bonds. And they wanted the information displayed in a particular way that gave them not just a suggestion, but the data that led them there. In this way, they’d be able to incorporate their own expertise into the AI’s output. 

If we had designed a product based on the original assumptions, it likely would have flopped. To be useful, the AI needed to be particularly configured to the humans at the center of the problem.

The linkage points between human and AI are crucial

We all know that bad blood among employees can spell doom for an organization. Mistrust and negative energy are surefire ways to sink a ship. In many ways, integrating AI can feel a lot like hiring on a slough of new employees. If your existing employees aren’t appropriately trained on what to expect and how to work with the new crowd, it can ruin even the best-laid plans. 

Once you’ve identified where AI fits into your organization, we recommend paying extremely close attention to the linkage points between human and AI. Where must these parties cooperate? What trust needs to be built? What suspicion needs to be mitigated? How can each benefit the other in the best way possible?


Recently, we worked with a financial services technology provider to develop AI that could spot fraud and inaccuracies in trading. We conducted in-depth research into the needs of the surveillance teams who’d be using the software to understand their role and also their expectations for how they’d use such a tool. This allowed us to thoughtfully build a visual interface on top of the AI that could maximally meet the surveillance team’s needs, including helping them with task management.

Taking the time to understand the precise nature of this potential human-AI collaboration helped us use resources wisely and prevent the mistrust and resistance that can cause even the best tools to fail. 

AI integrations require trust and understanding

Your AI also can’t be a “black box.” While not everyone at your organization needs to be an expert on its functionality, simply dropping an unfamiliar tool into a work environment and expecting people to trust whatever it spits out is very likely misguided. This is especially true when AI is helping experts do their jobs better. These roles are defined by the deep training that goes into them — how are they supposed to give an open-arms welcome to a new “employee” whose training they can’t see or understand?

For example, a doctor trained in reviewing mammograms may well benefit from AI software that can review 500 scans and whittle it down to only 20 that need human assessment. But you can imagine a physician’s resistance to simply taking those 20 images without understanding how and why the software weeded out the other 480. They rely on their expertise to save lives, and need to trust that whatever tools are helping them are supported by similar training and values. 

AI has the power to make big change. But if we don’t center humans in our implementations, the change we make may not be the good kind. 

Contemplating your early steps into AI? We’d love to work with you to help make your leap into the future a smart one. 

Designing Products for Healthcare: 5 Important Considerations

In the healthcare space, the design choices you make can quite literally have life-or-death stakes. Getting it right is important. 

But healthcare environments are unique spaces, and what works in other industries might not always carry over. In addition to regulatory considerations like HIPAA, many healthcare organizations have distinct cultures and ways of doing things shaped by decades of caring for people, often in extreme circumstances. 

Grand Studio has had the privilege of working with several healthcare organizations over the years and has come away with some rules of the road when it comes to product design in these specialized spaces. Read on for five key things to keep in mind.

Tip #1: Involve Clinicians & Other Stakeholders from Day 1

For the best chance of success, bring in key stakeholders right from the outset — particularly clinicians. For one, their perspectives will be critical to developing whatever you’re creating. But also their involvement will also help build buy-in and trust. 

Too often, clinical teams get burned by the debut of some new technology that was clearly built without insight into their day-to-day experience and ends up causing more headaches than it eases. Looping these key stakeholders in immediately and keeping them up to date as the design process moves forward will have a two-pronged benefit: you’ll spot potential problems in the design, and you’ll also do a lot to socialize your effort. You build faith that you’re listening to them, working to understand their unique, high-pressure world. 

That said, keep in mind that they are busy literally saving lives. They may not be available for every collaboration you’d want from them, so as part of your Day 1 involvement, settle on a cadence that gets your team the input you need while respecting their often busy schedules.

Tip #2: Onboarding Must Be a Part of Your Design

Take the time up-front to consider the onboarding process. People working in healthcare environments, from doctors to nurses to administrators, almost always have a great deal on their plates, and what’s on their plates is extremely important. Changing a process or asking people to adopt a new product can feel extremely disruptive. Even something people may ultimately find helpful and time-saving might gather proverbial dust if the channels of a routine run too deep — especially if it’s not explicitly clear why or how people should switch things up.

The single most important thing you can do to help onboarding is getting an internal champion — someone who believes in what you are doing and can support you in socializing it from within. Clinicians tend to place a high degree of trust in insiders who know through experience what their day-to-day life is actually like. Finding the key leverage points in the culture of an organization and getting them on your side will be critical to any onboarding/socialization plan. (In our experience, the most powerful shifters of culture are doctors and nurses.)

And of course, onboarding is not a one-and-done thing. Just as the design requires iteration, so too does onboarding. It’s important to continually go back to the front lines and tweak how the value prop and plan are described, paying attention to what yields the best adoption.

Tip #3: Design for Rapid Action

Healthcare providers frequently need to do things quickly. While efficiency is valuable in any situation, there are particularly time-sensitive moments in healthcare — like responding to a patient with a critical condition exacerbation.

In a recent project with one of the largest private healthcare organizations in the US, our task was designing tools for nurses to remotely monitor patients with postpartum hypertension. In our design, we asked ourselves how we could enable nurses to quickly identify which patients required their attention most urgently — digital triage, in essence. If a patient in a life-threatening condition was identified, we also asked ourselves how we could best support the subsequent action that needed to be taken. For patients with dangerously high blood pressure, we worked with our client on a system by which nurses could immediately alert not just the attending physician but also the patient and their circle of care. Nurses could act rapidly on the situation and also keep everyone connected.

Tip #4: Allow for Personalization

In the clinical field, there is a vast diversity in job functions as well as people’s way of doing things. Instead of making a one-size-fits-all solution, you’re better off locating and enabling key points of personalization that allow people to do their jobs in ways that suit their needs. 

We recommend interviewing wide sets of end users and attuning yourself to the subtle differences in process that could inform how you allow for personalization of the product. Some clinicians, for example, only need to view a subset of the patient population in order to do their job, and anything beyond that will be visual clutter. Some clinicians need to filter down by a particular biometric or health status marker. Some clinicians need to respond to issues in different ways than others. Building in personalization helps you meet people where they are and let them practice medicine the way they know best.

Tip #5: Support the Patient-Provider Relationship

The job of technology in healthcare should always be one of making healthcare providers more efficient and effective — not impinging upon or trying to replace a clinician’s relationship with their patients. No matter how “intelligent,” technology is ill-suited to replace this powerful and healing relationship. 

Focus instead on getting technology to solve lower-level problems so that providers can spend time on patients in need of their skill set. Focus on designing tools that enable high-impact interactions and offload low-level ones. Figure out ways to optimize and clear a path for what care providers do best. 

Want to learn how Grand Studio can help with your next healthcare project and build clarity out of complexity?

Drop us a line! We’d love to hear from you. 

Best Practices for Qualitative UX Research

The better the research, the better your plan. Combining the hard-and-fast numbers-driven data points of quantitative research with the broader “why” and “how” questions of qualitative research sets you up to make well-informed decisions that truly speak to the problem at hand. 

That said, to some, qualitative research can feel squishy and daunting. Protocols as rigid as a survey will prevent truly illuminating findings from surfacing, but also, going in with too loose a plan can lead to time-wasting or significant gaps in findings. 

At Grand Studio, answering juicy qualitative research questions is among our favorite things to do. We start by working with clients to understand the decisions they’re trying to make, then co-craft a plan to help answer those questions. While every research plan is uniquely informed by the context and questions surrounding it, we have a few best practices to share. 

Best Practice #1: (Really, Really) Know Your Research Questions

We know this one sounds obvious, but this is a common problem we run into with clients. They’ll have a general sense of what they want to learn about but haven’t yet distilled these into concrete research questions that can keep teams on track in the field. 

Stakeholders who’ve been steeped in a problem for some time can probably rattle off the most critical research questions on the fly. But when they aren’t concretized into a clear list, things can get lost in translation when more people get involved. Researchers constantly encounter twists and turns out in the wild, and their clear understanding of the research goals can be the difference between a smart on-the-fly adjustment and a wasted day. 

We’ve also seen situations where the research goals are made clear at one point, but as folks get wrapped up in the work and adapt to surprises, the initial need can get lost in the mix. As pedantic as it may be, we recommend putting the research questions at the center of every research check-in and synthesis meeting. “How are we progressing along our goal of learning X, Y, and Z?” Impossibly simple, but the benefit cannot be overstated. 

Best Practice #2: Be Wary of Shortcuts

Life gets busy, and shortcuts can be tempting, especially when your research questions are so vast. Every day, there is slick new technology released, promising to enhance and streamline your qualitative research. We’ve looked at every piece of technology that’s come our way and tried out a lot of the new tools, Ray-Ban Stories and dScout’s diary study tools. While some are helpful augmentation tools, nothing we’ve found is a viable replacement for on-the-ground research. 

The bread and butter of qualitative research is talking to humans, and there’s a reason for that. No matter how crunched your timeline, be suspicious of things that try to steer you away from that. 

Best Practice #3: Choose Your Methodology Wisely

There is an art to choosing a research methodology that is nearly as critical as identifying your research questions. Once you’ve got a clear understanding of what you want to learn, you need to figure out the best way to learn it, and with whom. Say, for example, you’re doing a study on how people make decisions while grocery shopping. An interview may be able to tell you general things about how people shop. But when you’re on the ground, observing or doing shop-along, you’ll get so many details people would never have thought to tell you in an interview. Plus, the way people explain the why and how of what they did in the past can often be very different from what they say in the moment.

Perhaps the most tricky part of this is responding to inevitable restrictions that come up. Usually, there will be at least one or two feasibility or legal concerns that keep you from using your “dream” population. This requires you to get creative about how you can optimally answer your research questions using the tools you have. You don’t have to be in an exact real-life situation to get highly usable data.

One last point on methodology is to consider the reciprocity of the research. Sometimes, research questions may be sensitive, or catch people in a difficult moment in their lives. You don’t want to skip these perspectives, but you do want to be sensitive to them. For example, at one point, we collaborated with a client on a project to better serve the needs of cancer patients. With their support, we set up a table where patients could get free warm socks in exchange for their thoughts. 

Best Practice #4: Go Wide, Wider Than You Think

One of our favorite parts of qualitative research is the surprise involved in answering such large-scale questions. But it’s also the trickiest because, by nature, one cannot entirely plan for surprises.

Knowing that, at the beginning of the research, you don’t know what you don’t know, we recommend casting a wide net. Talk to more types of people and roles than you think you need, especially if these people are easy to access. You don’t need to go overboard — just one or two sessions with a new type of participant can do the trick. We’ve made critical discoveries by taking the time to talk to someone slightly adjacent to the primary field of research who ended up having a great deal of insight into it. Go small at first, just to see if there are new stones worth turning over. 

Best Practice #5: Always Stay Aware of Bias in Synthesis

There is no way around the fact that humans are biased, even researchers who try very hard to be objective. 

We’ve found that the best way to introduce objectivity is not to push individual brains into objectivity, but to stack many ideas on top of one another. Try to use at least a few researchers, and gather their own unique perspectives on what they are seeing. Ideally, people from your organization should also review their findings and point out their own conclusions. Individually, no one’s perspective is objective. But when we see which trends emerge collectively, it’s more likely that they’ll be rooted in the actual research.

As is often the case with hard things, they frequently turn out to be the most worthwhile. Don’t be tempted to skip qualitative research if it sounds time-consuming, just make sure the research plan is well-matched to your timeline and budget. And, of course, we’re always here to help.

Got a qualitative research project you’d like to work together on? We’d love to hear from you.

When Technology Meets Healthcare: Practical Considerations From the Field

While every environment is unique in its own way, healthcare might take the cake when it comes to a need for specialized design considerations. 

There’s a trifecta of challenges: legal requirements to contend with, complex funding pathways, and the fact that what’s at stake might be life or death. How do you build technology poised to make a meaningful difference without endangering what’s already working? 

Grand Studio had the privilege of working alongside several clients on the front lines of healthcare and learned a few lessons.

Find a sustainable funding source, and check the CPT codes

With the interplay of public payers, private payers, and providers, the flow of funding in healthcare can be complicated. Whenever possible, aligning your intervention with a CPT billing code can be a smart way to position your technology of sustainable financing.

In the past several years, there have been more and more codes released that allow providers to bill insurance companies for digital health interventions like remote patient monitoring and patient engagement, and still, more are on the way. It’s a win-win-win for all involved: providers get reimbursed for investing in technology that improves health outcomes, patients get more tools that help them get and stay well, and the insurance companies spend less on patients who need less care.

Once you’ve found CPT codes that may be applicable, dig into the specific requirements to ensure your technology can meet them, and — critically — make sure your technology is designed to facilitate easy billing. 

While recently working with one of the largest US private healthcare systems, we co-designed an intervention for pregnant people with pre-eclampsia. We created a digital triage system to catch early signs of a problem, improving patient safety and staving off costly ED visits. While the avoidance of an ED visit was a saving unto itself for the healthcare system (and for the patient), we also designed the program to align with the CPT code’s billing requirement, which stated that providers could only bill for the remote monitoring if they saw the data and acted on it. As designers, this kind of requirement is frustrating in how much it limits the service experience. We saw enormous opportunities for automated alerts and interventions. Still, it was critical for us to remember that the service could not be funded and, therefore, couldn’t exist if it did not live within the payer requirements defined by CMS. Understanding our real-world limitations allowed us to build something viable and desirable.  

When patients are involved, study their mindsets carefully

We are perpetually in favor of doing robust research on end users, and healthcare is no exception. 

Whether leaving the hospital, adjusting to a new diagnosis, or even coming in for a check-up, people’s experiences in and around a doctor’s office can be highly emotionally charged. You may be dealing with people who are exhausted, people who are sick, people who are nervous about their loved ones, people who are confused but afraid to tell their doctor or people who can’t process any information at all because they are still in shock. Standard “design conventions” that may work in other environments could crumble in healthcare if they don’t address the specific emotional valence of the patient experience.

For instance, we once worked with a nonprofit health system to redesign how cancer patients checked into the hospital. In most contexts, efficiency is priority number one — the fastest solution is the best solution. In this setting, however, it was also essential to prioritize the slower face-to-face interactions that let these patients feel like humans, not numbers being churned through a system. Moments of warmth and connection were precious for people dealing with the magnitude of doctor’s appointments that come with a cancer diagnosis. (It’s worth mentioning that helping people feel more connected to their healthcare providers doesn’t just make them feel better — it can improve health.)

Understanding the patient’s mindset is also crucial when your goal is health behavior change. As healthcare providers know all too well, simply having the solution to a healthcare problem doesn’t mean it will be solved. Patients often do not follow their provider’s recommendations to take their medications or implement a lifestyle change. It usually isn’t because they don’t want to — it’s simply because there are too many barriers. Often, these barriers are emotional. It requires thorough research to stand a chance at cracking the code on what actually moves the needle on patient behavior. 

Despite the challenges of healthcare, it’s a gratifying field to work in, and we’re eager to collaborate with more clients trying to support people where it matters most.

Got a healthcare technology project you’d like to work together on? We’d love to hear from you.

Operational Efficiencies Through Service Design

Reworking a process that’s been around for a while can feel like opening Pandora’s box. 

Especially at large organizations, the prospect of reworking something that involves so many people is intimidating. And it’s not just the price tag — the prospect of making a significant change at an established organization usually requires near-herculean efforts of diplomacy and buy-in. 

With all that stacked against leadership, it’s no wonder any process working at least well enough stays in place as long as it does.

You may wonder how you got by when you finally cross the bridge to the other side. If done right, a service redesign has the power to revolutionize your organization, allowing the breathing room that lets people work and imagine to the best of their capacity. Job satisfaction goes up, and the bottom line does, too. 

If the light convinces you at the end of the tunnel, but you need help figuring out where to start, read on for our take on three common barriers to starting. 

Barrier 1: Too many politics involved in implementing a change

With more prominent organizations especially, decision-making is often dispersed across a number of groups, only some of which may talk to one another. The urgent problems of one faction of the company may not even cross the radar of another. The prospect of making a change with all those moving cogs can feel daunting to the point of impossible. 

Our best tip here is to get “in the room” with folks (even if it’s a remote room). It isn’t about turning on the charm to win someone over. It’s about demonstrating a genuine commitment to understanding their work and what’s important to them and creating improvements in a way that respects their lives and expertise. The sheer fact of feeling seen can do wonders. What shows up as stubbornness often belies a strong emotional connection and care about their work, which is grounds to connect. Plus, you may learn something that helps inform your approach to the redesign.

Tip: While this will seem biased, hiring consultants for some of this early diplomacy can be a game-changer if you have the budget. In addition to approaching the problems with fresh eyes, outsiders can often leverage an apolitical status and sense of urgency (due to budgets and timelines) to cut through entrenched political issues that can be very difficult to resolve from the inside

Barrier 2: Something feels wrong, but you’re not sure what the problem is

This is another common problem — our clients may have a general sense that something is inefficient but not know how and why it originates. 

We also sometimes see the flip side of this — clients who can pinpoint the issue precisely, but once solved, they realize it’s a symptom of the problem and not the core cause. 

For this, the best first step is to simply get out into the field. Watch people work, ask them questions about why they do what they do, and understand what motivates the different actions you’re seeing. While it may sometimes be daunting getting the logistics and approvals to go on-site, there is usually no faster way to diagnose the “real” problem than by getting into the thick of it.

Case study: With a recent healthcare client, we went out into the field expecting to streamline a patient registration process through digital tools. But after being on-site, we realized that solving the registration problem would actually create a new problem: when patients got to interact with an employee, even in an inefficient way, it let them feel known, cared about, and human. The problem to solve wasn’t digitizing clunky in-person processes. It was about optimizing moments of human contact.

Bonus: Having tangible examples to share with other groups can help lead to better communication and common ground for moving forward.

Barrier 3: The problem feels so overwhelming, you don’t know where to start

Start paralysis is one of the biggest barriers we’ve seen clients run into. Particularly when you are embedded into the organization you’re trying to change, with an up-close view of all the interconnections, interdependencies, moving parts, and potential obstacles, the prospect of getting started can feel like setting off a domino chain of chaos. There’s fear that change may actually make things worse.

In a perfect world, maybe it’d be possible to step back and assess your organization thoroughly and objectively, making a perfect step-by-step map of the best order of operations in which to tackle the overhaul. But in reality, it simply doesn’t work that way. 

One of the most significant steps toward success is letting go of the idea of starting in the perfect place and simply starting somewhere. After all, there’s nothing like getting into it to help you refine your map for the next journey phase. Indeed, the time will come when you need to coordinate efforts across the board, but having everything mapped out before the first step begins is an impractical goal that can stop efforts in their tracks. 

Tip: Experience and intimate knowledge of an operation are invaluable, but when it comes to getting started, it can also be a burden. Often, our clients know too much about what’s going wrong and can get into paralysis in figuring out an excellent place to start. Here is where outside eyes can be beneficial in helping you find a suitable starting place.

In sum, there’s a light at the end of the tunnel, and we hope to see you there.

Got a service design project you’d like to work together on? We’d love to hear from you.