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!

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.

CASE IN POINT 

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?

CASE IN POINT

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. 

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:

  1. Allow time to think expansively
  2. Keep your ideation separate from your editing
  3. 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.