Diana Deibel July 23, 2024

4 Things You Won’t BELIEVE Design Can Learn From Buzzfeed

July: a time for pools, slushies, bike-riding and hanging out with friends. What better way to celebrate mid-summer than to look for inspiration in one of the quintessential lighthearted media outlets?

Without further ado, here’s what design – at all levels – can learn from the Buzzfeed approach.

Bite-sized content works. People read listicles and short articles because they are brief snippets they can parse quickly and move on. Often in design, we try to pack too much in, and it gets lost in the process. Bullet points of quick takeaways, illustrative impact quotes or screens, and executive summaries work really well – with an offer to dive deeper for those who genuinely want more.

Nothing engages like gossip. Put another, more design-y way, stories anchor everything. We all want that tea spilled and frankly, when details are grounded in a narrative that starts with a bang and sets the stage, tension that builds, and an ending that wraps up that portion of the story (even if the overarching narrative will continue on), we’re listening the whole way through. Along those lines…

Juicy headlines draw people in. Is it clickbait or is it cutting through the noise to grab your audience’s attention? (Both?) We can do the same in design when communicating important research insights with leadership or naming design options with stakeholders managing busy schedules. Marketing exists for a reason and oftentimes Design doesn’t do a good job of utilizing it for ourselves. Juicy headlines or naming conventions can help our business stakeholders understand what problem is being solved, or what they or their users will get out of a particular solution from the get-go and bring them along in a productive, collaborative way.

Embrace the whimsy. Buzzfeed always has a silly quiz on things like “what your favorite sandwich says about your future” – and people love those. Sometimes design takes on the personality of business and the thing is, we really can’t take ourselves too seriously for two reasons:
1. We need to take the work seriously but take ourselves lightly in order to really enable creativity to flow. Putting on formal structured thinking and expression can feel quite confining to many designers. Which leads to…
2. We’re the “creatives.” (Yes, everyone is creative but we’re the people who are expected to bring the outside-the-box thinking and artifacts). We’re not only allowed but expected to bring some amount of rule-breaking and whimsy to the table.

Put another way, if not us then who? ESPECIALLY within your own teams. So have fun. Do a little something silly. Have a team-building activity that’s a little weird (we’ve done Secret Santa lunches sent to each other’s houses and at-home Nailed It challenges). Change your Teams photo to a raccoon meme. Use gifs in communication.

When you embrace the silly you make space for other people to relax, bring themselves and create a more creative and innovative space for work to take place. A place where they can take risks – at first with just themselves but then with the products and ways of working. And smart risk is how you get to great.

Want help figuring out how to set up and maintain a high-functioning and impactful design team? Drop us a line!

Diana Deibel May 20, 2024

Unsolicited Advice for Leveraging a GenAI LLM

At this point, you’re probably pretty familiar with the AI hype out there. You’ve likely read that GenAI (like DALL-E or ChatGPT) is great for generating both visual and text-based content, and AI overall can be good for identifying patterns, particularly in large data sets, and providing recommendations (to a certain degree).

But you may also be familiar with the myriad ways GenAI has gone sideways in recent months (ex: Intuit’s AI tax guidance debacle, New York City’s law-breaking chatbot, the Air Canada lawsuit, and so many more). That doesn’t mean you need to stop experimenting with it, of course. But it does mean that the folks warning about it not being ready quite yet have some valid points worth listening to.

Having built several AI solutions, including a recent GenAI LLM (large language model) solution, here’s some unsolicited advice to consider when leveraging a GenAI LLM.

Don’t use GenAI for situations where you need a defined answer.

As evidenced in all the examples above, GenAI chatbots will – and often do – make information up. (These are called hallucinations within the industry, and it’s a big obstacle facing LLM creators.) The thing is, this is a feature, not a bug. Creating unique, natural-sounding sentences is precisely what this technology is intended to do and fighting against it is – at least with the current technology – pointless.

There are some technical guardrails that can be set up (like pointing the system to first pull from specific piles of data, and crafting some back-end prompts to tell it not to make things up) yet still, eventually, our bot friends will find their way to inventing an answer that sounds reasonable but is not, in fact, accurate. That is what they are meant to do.

In situations where you need defined, reliable pathways, you’re better off creating a hardcoded (read: not GenAI) conversation pathway that allows for more freeform conversation from the user while responding with precise information. (For the technically-minded, we took a hybrid format of GenAI + NLU for our latest automation and found it quite useful for ensuring that something like following a company-specific process for resetting a password was accurate and efficient – and importantly, in that use case, also more secure.)

Know thy data—and ensure it’s right.

I know it’s been said a million times over but a pile of inaccurate, poorly-written data will provide inaccurate, poorly-written responses. GenAI cannot magically update your data to be clean and accurate – it can, over time, generate new information based on existing information and its style (which should still be checked for accuracy) but asking it to provide correct information when it’s hunting for the answer through incorrect information is an impossible task. It cannot decipher what is “right” or “wrong” – only what it gets trained to understand is right and wrong.

It’s important then to know what the data that you’re starting with looks like and do your best to ensure it’s quality data – accurate, standardized, understandable, etc. Because barring time to properly train the data (which is a serious time commitment but well worth it for anyone wanting proprietary or custom answers), starting with a clean data set is your best bet.

Bring the experts in early.

When people have been experimenting with the technology and potential solution for a while, there is a pressure to “get it done already” by the time the experts roll in that doesn’t allow for the necessary exploration and guardrail-setting that needs to happen, particularly in an enterprise setting where there are plenty of Legal, Compliance, Security and even Marketing hurdles to clear.

From both personal and collected experience, it’s worth noting that often the initial in-house experimentation focuses on the technical aspects without user experience considerations, or even why GenAI might – or might not – be the right solution here. That’s going to take a little time. So it’s worth bringing in design and/or research experts, whether in-house or consultants, alongside the initial technical exploration to do some UX discovery and help the entire sussing-out process happen in tandem with the technical exploration. This can provide a clear picture of the business case for pursuing this particular solution.

To help out, the Grand Studio team created a free, human-centered AI framework for an ideal AI design & implementation process.

Interested in knowing how to start a GenAI project of your own? Drop us a line!

Diana Deibel December 5, 2023

The 2024 Design Forecast

We did it, everyone. We made it through another year. To be perfectly frank, this year was a bit of a weird one, mainly due to a few key elements:

A real will they, won’t they dance with a potential recession that constrained the budgets and resources of many organizations this year
Generative AI coming front and center and taking over everyone’s conversations and questions about the future in product and business
More layoffs across industries, impacting the design & product communities as well as what the remaining team members can accomplish

So let’s look ahead to next year, shake our magic 8 ball, and make our predictions about what trends we’ll see in 2024.

Generative AI Implementation Begins

2023 many folks spent learning and hiring for generative AI leadership in their organizations. Certainly both these things will continue into the new year, but orgs are starting to feel ready to “try something” in generative AI and set up their first initiatives and pilots to test out what AI can do for them.

One unsolicited piece of advice we’ll give from our previous experience: take your time to really define and scope the problem you’re solving, make sure AI is the right solution for your user group, and start small. It’s easy to skip past these steps but most everyone is in a test-and-learn moment right now, so if ever there was a time to understand before blasting a technology everywhere, this is the time.

The Return of Innovation

Businesses at large took a collective pause from innovating to focus on optimizing what already exists. Part of this is burnout from the last few years, part of it was budget slashing and belt-tightening. And to be honest, this will likely continue into the first half of 2024, especially given the geopolitical and economic tensions currently simmering.

However, our bet is that the second half of 2024 will begin to see a return to pushing innovation, particularly for incumbents who may have newcomers nipping at their heels. It’s always nerve-wracking to feel like you’re losing momentum in the market, and innovation is the way to stay ahead of the pack.

Consumer-Focused Mixed Reality Hits the Shelves

In a prediction that merges both innovation and emerging tech, we’re seeing a trend towards more mainstream utilization of mixed reality and spatial UI design (things like Vision Pro and Quest3), particularly in the enterprise side of things on tasks like training and digital twinning.

This trend is still looking for its footing on the consumer side, which leaves 2024 wide open to folks looking to lead in that space. We foresee the emergence of tools involving B2C applications in this realm, though it won’t yet be a saturation of the market. Frankly, if the economy continues in an up and down pattern, it will likely remain a luxury novelty in the consumer space until people have the money – or a reason – to invest in it. Likely 2024 will be a learning year for all of us watching this space to see what plays out with consumers.

Research Execution Will Extend Beyond Researchers

While many design and product teams were hit hard with layoffs in late 2022 and throughout 2023, it’s worth noting that research teams seem to have taken the hardest hits. Because of this, needed research is going undone and we’re seeing product managers and UX designers taking up the mantle of executing research – in particular, evaluative research that is necessary for the optimization work that’s been on the forefront this year.

We see 2024 being a year where research continues to be a deficit and many organizations will look to contractors and agencies to fill the gap – but also to their internal folks with less of a background in how to execute. For this reason, we may also see an uptick in attendance for research conferences, books (we love Steve Portigal’s Interviewing Users and Caroline Jarrett’s Surveys That Work), online courses, and trainings to help support these additional asks on folks.

Want to talk about your design & research support needs for 2024? Reach out to us!

July 24, 2023

Using AI in Enterprise

AI is everywhere these days. There’s no escaping it whether it’s a board room conversation, a conference, or a meme on social media. And with good reason. As Bryan Goodman of Ford Motor Company said recently at the 2023 Reuters Momentum conference on AI, “I can’t imagine anyone being competitive without AI.” The resounding perspective across industries is in agreement with him.

The question amongst many people, particularly those in larger enterprise organizations with less scrappy flexibility and more risk, is how do we use AI in a way that is responsible to our business units, our shareholders, and humanity at large?

Download our whitepaper and read more about the best use cases and challenges to consider for enterprise AI usage.

GrandStudio_Using-AI-in-Enterprise.pdf Download

Anna Lathrop June 27, 2023

How to Innovate for Long-Term Vision

Many of us have been in a position where, amid our day-to-day tactical work, there surfaces a nagging suspicion that some long-term organizational vision is needed. You know something major needs to change, that some kind of high-level ethos-tinkering could push your team forward… but nobody quite knows what that thing is.

Even if you manage to set up a brainstorming session to get some fresh ideas out, what often happens is that a few wild ideas will be thrown out, then immediately nixed due to (very real) feasibility or viability concerns. How does anyone get past these blockers to arrive at exciting — yet grounded — innovation?

What does a successful visioning process look like?

This is a common problem we tackle frequently at Grand Studio. While every project will have constraints to take into account, successful visioning typically boils down to 3 main things:

Allow time to think expansively
Keep your ideation separate from your editing
Choose activities that match where your team is at

We’ll take you through each one of these in a little more detail.

Think expansively

The purpose of visioning is to let go of constraints and dream up potentially surprising solutions, knowing we can always come back to earth afterwards. The idea is to think big, to make the kinds of lateral, creative connections that generate game-changing ideas.

To do this, we recommend setting expectations and reminders with your team that constraints don’t matter right now. We also recommend helping your team practice expansive thinking with a warm-up. Very often, with our day-to-day jobs, our brains are trained to think pragmatically, and making the cognitive shift into a visioning session can be challenging.

Forced connections can be a great exercise for people new to expansive thinking. With this, you take 2 seemingly unrelated topics or items and force yourself to connect them in some way. You can do this with physical objects in the room you’re in, current events, items in people’s bags… anything at all.

For example, say your first pairing is an iPhone charger and an apple from someone’s lunch. How could they be related? Maybe there’s a novelty phone charger that uses the energy from an apple to charge an Apple device… kind of like the potato-powered lightbulb of kids’ science experiments. You might start with a few silly pairings to get people in the groove, then start adding in pairings related to your business or user needs.

Keep your ideation separate from your editing

Wild ideas can always be edited down. But applying too many constraints on imagination can end new ideas before they even begin. We recommend setting aside time for true ideation — even if it’s just a couple of hours — without letting feasibility concerns or fear of the unknown be the leading force in the room.

To do this, have the group mutually agree upon what the dream-big phase of your ideation session will look like, and put everyone’s mind at ease by also setting expectations for what the editing down phase will look like, complete with agreed-upon deliverables.

Backcasting is a good technique for nailing down specifics that will eventually lead towards your collective vision. Keeping your future vision in mind, start working backwards and identifying the technologies, processes, people, and key milestones that would need to be in place to reach that goal. Keep working backwards in increments until you reach the current day. Now you can use these milestones when developing your roadmap or theory of change.

Choose your ideation activities wisely

Jumping into the deep end with complex visioning exercises may be a lot for people who’ve never been involved with this kind of work before. We recommend that organizations newer to visioning exercises start off keeping it simple.

For organizations newer to visioning, try some exercises like:

Crazy eights: This is a quick sketching exercise that asks people to come up with eight ideas in eight minutes. The speed of this exercise forces people to let go of coming up with a perfect, edited idea, and instead dream up as many possible paths as they can. Looking back at what people shared, you’ll usually see patterns across participants that can illuminate new directions.
Exquisite corpse: You may have done this in school. Exquisite corpsing starts with each person creating an idea. You then pass each idea off to another person in the group, who adds on, or ideates a different part of the idea. This can encourage collaborative thinking and riffing off of others’ inspiration, as well as letting go of the impulse to step back and critically evaluate the whole picture.

For organizations more comfortable with visioning and imagination activation, try:

Desired state storyboarding: If you had a magic wand, what would the ideal state of your service or product look like? How might people use it? What’s the ideal impact? How has society changed for the better? Create a narrative telling the story of your ideal state. This can be a drawing, a newspaper headline, or a storyboard. This can help everyone align on what the long-term dream would be, and set the stage to figure out the small steps you can take towards that vision.
Four Futures Scenarios: Making scenarios is similar to our desired states exercise above, but more in-depth. You can use these scenarios to think through multiple strategies, product ideas, and services to give your organization a wide range of action plans in order to proactively make your own future, instead of operating from a reactive place. Jim Dator at the University of Hawaii was one of the first to develop and popularize 4 key future scenarios that we can use when imagining alternative futures:
- 1. Continuous Growth: the company grows infinitely and expands market share. (Tip: Stay critical! Think about when growth can be a negative thing for companies.)
- 2. Discipline: the company faces significant limitations, either imposed internally or from other forces like government regulations.
- 3. Collapse: the company struggles to survive due to things like market disruptions, economic recession, or other extreme factors. This future can be useful to think through disaster scenarios and work on “risk-proofing.”
- 4. Transformation: the company changes something fundamental, such as its mission or ownership. This scenario is most exciting when thinking about ways to innovate and find something new. You can use Transformation scenarios to think about radical new directions your company can pursue in order to stay one step ahead of market trends.

Now take a step back and look at all your futures. See any common themes or patterns? New product lines or directions your company could go that are exciting and generative? Pick one, or a couple, and try backcasting from it to see what steps you would need to take.

Of course, there are plenty of ways to expand beyond these ideas into some really creative and out-there visioning exercises, but our advice is to start small to get your organization acquainted with what visioning can yield, and also build their faith that creativity doesn’t mean letting go of practicality. Once there is more of a culture around visioning and imagination, you can try exploring larger, more “out there” techniques.

Bonus: Get an outside perspective

Sometimes, working with an outside organization can help with visioning. While no one will understand your organization better than you, outside eyes can help push past some preconceived notions and generate new ideas. They can also help set the tone for what visioning can look like, shepherding unfamiliar or suspicious parties towards the light of imagination.

Got a visioning project you’d like to collaborate on? We’d love to hear from you.

Josh Lucas-Falk June 12, 2023

What My Cancer Treatment Taught Me About Healthcare Design

Three years ago, I was diagnosed with an aggressive bladder cancer. This type of cancer is very unusual in otherwise healthy 42-year old people, but I caught it early enough that I was able to complete a full course of treatment, and my doctor has put me in the class of patients with the highest likelihood of long-term success.

For my type of cancer, treatment has meant 2 surgeries to remove the cancer and then 17 rounds of immunotherapy over the last three years. I think this immunotherapy is “better” than chemotherapy in terms of side effects, but it is still pretty unpleasant – it involved instilling live botulism bacteria into my bladder to stimulate a local immune response. No fun. I’ve also had an enormous number of tests – CT scans, scopes, a surprise biopsy (cancer-free, thankfully), fluid analysis, etc.

When I’m not dealing with cancer, I run a design studio that does significant work in the healthcare space. When I had my first surgeries, we were literally working on a product that helps improve scheduling of elective surgeries for a major healthcare provider. Last year, we helped another large provider redesign the service experience for patients undergoing cancer care at one of its facilities. It’s been an interesting exercise, and occasionally a useful distraction, to observe my care journey from the perspective of someone who has been responsible for designing care journeys for others. Kind of the ultimate empathy-building exercise (though I don’t recommend it).

A few things I’ve noticed along the way:

Existing online resources for people with cancer were really bad (for me).

When I first got diagnosed, I went to authoritative sites like the Mayo Clinic to learn about my type of cancer. This was a mistake. The best of these sites take the highly appropriate and responsible approach of writing about the disease with a near-clinical tone. They know that people are coming to their material to answer the big question: “Will I die from this disease?” The correct answer from a scientific perspective is to talk about morbidity over timelines across a broad population. This was actively harmful to me – it wasn’t helpful for me to see that an average person with my type of cancer has a significant chance of dying within 5 years. Intellectually, I knew that those populations included people with many comorbidities I do not have, and I knew that I was a couple decades younger than the average patient, but it still was data without comfort.

Balancing medication side effects is hard.

I came into this knowing this to be true – we literally had designed a cancer care app several years back that included medication tracking. Turns out living it gave me a much more nuanced perspective. Over the course of the last three years, I’ve very actively tried medications, observed their side effects, talked to my doctor, and rebalanced. I have the privilege of being a wealthy, educated, cis, white man, and communicating with my doctor was pretty easy for me. However, 80% of patients don’t complete the treatment I received, so I imagine that the same can’t be said for everyone. Without the tools, support or access needed to understand the side effects any one medicine has and to make changes, this process must be incredibly intimidating and discouraging for most people. It was really hard for me, and I was a best-case scenario.

I’ve never felt more like an object than when I was on a hospital bed.

When my car has an issue, I drive over to my mechanic, pull into the garage, and a couple of people descend on the car to poke at it. When I had my surgeries, I was the car. Someone literally wheeled me into an OR where there was a team of people quietly prepping surgical instruments that were about to be put into my body. I didn’t know these people, and these people only knew me as a diagnosis to resolve. It was a miraculous process – I was awake, then I fell asleep, and I woke up without cancer. It was also incredibly alienating. Because of my past work, I’m very aware that the hospital is going to want to do 5 – 7 cases in that OR on the day I had my surgery, and I sure did feel like a broken machine going in for service in a facility run as efficiently as possible.

I come away from this experience with a clearer sense of the design opportunity across this system: healthcare is dispassionate by design, and yet we humans get caught up in it and have human reactions like pain, confusion and fear. Despite my very positive experience with my providers, I didn’t get any support at all for those human reactions. And I’m just one person out of the ~2,000,000 that will have a cancer diagnosis in the US this year, which is a small fraction of the population that will interact with the entire healthcare system. That’s a whole universe of human need. I think it would take a lot of hubris to say that design has a significant role to play in mitigating all of that need, but there are certainly meaningful interventions that digital products and services could make.

Coincidentally, Insider just published this article on a JAMA paper comparing AI-driven responses to questions on Reddit to responses from doctors. It’s worth looking at – responses from the AI were rated by medical professionals as having higher quality and being more empathetic. The empathy piece is particularly relevant to me. I sought that out several times in the course of my treatment, and found it to be in really short supply.

I think what’s also clearer to me is that the scale of our healthcare situation, and its associated service problems, is so large that it’s impossible to imagine we will have enough humans to truly care for all the patients. There’s an enormous gap waiting to be filled by innovative products and design in allowing patients to better serve themselves. That Insider article above discusses the value of self-service in terms of diagnosis and triage. There’s also a huge need in supporting people with chronic conditions who may only see their doctor four times per year, but are dealing with their disease conditions every day.

I, for one, am looking forward to getting started working on these tools that will provide meaningful support between the doctor visits. Especially now that I’m done with my fucking cancer treatments.