2015

The 2015 Report explained design’s rise in value to tech as due to mobile devices and the mass-consumerization of computing. We moved from “tech-led” to “experience-led” digital products as services on smartphones took over and gave access to everyone. Designing for mobile brought new experience constraints compared with the desktop, and made designers’ skills invaluable as the pathway to non-techy consumers.

• 27 startups co-founded by designers and 13 creative agencies were acquired by tech in the last 4 years.
• 5 startups co-founded by designers have raised more than $2.75 billion, and more are out there.
• 6 venture capital firms invited designers onto their teams—for the first time—in the last year.
• To achieve great design, you need great business thinking— to effectively invest in design — and you need great engineering — to achieve unflagging performance.
• Tech is no longer for Tech-ies, because mobile computing is for everybody now.
• The smartphone revolution brought design’s value into the foreground because usage of computers dramatically increased.
• User experience design matters so much because we are unlocking our phones every 5 minutes and will not tolerate bad experiences at such a high frequency.
• Over 90% of designers in the technology industry are in favor of learning coding.
• Seven of the top ten business schools in the world have student-led design clubs.
• 10% of the 2014 Fortune 125 companies have executive-level positions or CEO support for design.
• The first generation of computing was all about Tech-ies. The new generation of computing is for regular people and “the rest of us.”

2016

The 2016 Report showed peak growth in interest by venture capital firms in design, and highlight significant growth in the acquisition of design agencies by consulting firms like McKinsey & Co and Accenture. Google emerged as a new leader in design. There are 3 kinds of design: Classical Design, Design Thinking, and Computational Design. The most business value is being driven by the latter two kinds of design.

• Design isn’t just about beauty; it’s about market relevance and meaningful results.
• Design firm acquisitions continue: 42 design firms have been acquired since 2004, ~50% of which have been acquired in the last year alone.
• Designer co-founded companies exhibit funding success: 36% of top 25 funded startups are co-founded by designers, up from 20% in 2015.
• Designers in venture capital have increased: More designers entered VC in the last two years than the previous four years combined.
• Currently design education lags the technology industry’s needs for data- oriented, coding-enabled graduates with business acumen.
• Becoming a skilled self-learner is a critical skill for the new designer.
• Computational design has been around since the 70s and grew from collaborations between architects and computer graphics folks.
• The notion of making something perfect, as classical designers want to achieve, runs counter to how computational systems exist.
• Being literate in code is important, but being an expert is not necessarily in your favor.
• Design at the feature level is in isolation, and can be measured. Design at the system level is bolder and holistic, but harder to measure.
• Products are products of a company’s culture, and not just some magical switch where “design” gets turned on inside a company.
• This year 100% of the top business schools have student-led design organization.
• Google has risen in its perception for design quality due to a series of actions that have been ongoing over the last decade.
• Thinking critically about design means considering the broader human impact of a product and service that goes beyond profitability.
• The next generations of designers aspire to design a world that reimagines the status quo with empathy for their fellow human beings.
• Instead of seeing diversity as a problem that needs solving, designing for inclusion is both an economic opportunity and cultural responsibility.
• There are three kinds of design at play. We need to be specific.

2017

The 2017 Report framed computational design as a key driver of accelerated growth, with inclusive cultures @work as vital for tech businesses hoping to lead in design. We saw the emergence of new tools and creative communities as producing increased value, and inclusive design had just started to arrive in the zeitgeist of the product landscape. Adopting an inclusive design approach expands a tech product’s total addressable market. The tipping point for inclusive design begins to tip.

• According to LinkedIn, the highest echelon of the technology industry is vying for more design talent at a rate of +65% annually.
• 100% of the top business schools have student-led design clubs, which are pushing the curriculum in b-schools to shift as well.
• 80% of designers surveyed would start a company if they had access to venture capital / other funding.
• Three designer co-founded Chinese companies have combined market cap of over $300B: Alibaba, Visual China, and Xiaomi.
• There are 17 million designers in China with 0.5 million design graduates every year.
• In 2016, the largest US-based national designer association AIGA issued a study in collaboration with Google to reveal a sentiment shift for its future towards digital and interactive forms of design.
• The least satisfied designers: Publishing (74%), Print Design (74%), Architecture (71%). The most satisfied designers: Industrial/Product Design (83%), Brand Strategy (82%), Digital Design (82%)
• 86% of students surveyed say they learned their digital skills from resources outside their coursework.
• The top 3 skills needed by designers in practice are not available to them as basic coursework: business and finances, research and analytics, leadership and teamwork.
• 50% of companies have a single holistic design team. The other half splits designers across marketing and product.
• 8 of 10 smartphone apps in the US are owned by Google or Facebook, and when mobile devices are used there is 20% chance the person is engaging the Facebook app.
• Coding is not the only unicorn skill: writing and a content-centric skillset is needed in modern user experience design as a means to shape productive realities.
• Chat-based interfaces are grounded in mental models that don’t require a complex graphical representation and navigation system.
• Today’s connected technology products and services make us more vulnerable than ever before – it’s incumbent upon designers to build product features and UX that call out and protect against those vulnerabilities for end users.
• $150K—200K/year is the cost for protection against a sophisticated DDoS attack. For an individual journalist, it’s a prohibitive one that threatens the future of the Open Web.
• Historically speaking, technology products weren’t designed with inclusivity in mind because the users of the products were generally the makers of the products.
• As products and services in our lives become more personalized, there is a growing need for the teams that build products to look and feel like the users on the other side. To design for everyone, we need to now think and work more inclusively than ever before.
• 90% of designers surveyed in tech say that having a more diverse design team is important to them personally.

2018

The 2018 Report saw the growth of inclusive design expand from the edges into the center of conversations in the technology industry. Microsoft’s pioneering work in inclusive design as led by Kat Holmes started to be picked up by non-designers and business leaders. At the same time, Artificial Intelligence’s implications to design became evident with new advancements in machine learning that were both exciting and frightening.

• When people in the tech industry talk about “design,” they often make the mistake of not differentiating between classical designers and computational designers.
• A classical designer might craft a wooden chair for a home which is used by a few people; a computational designer might craft an app for a smartphone which is used by hundreds of millions of people.

• Medical schools in the US like the Mayo Clinic and the University of Michigan Medical School are using design thinking in their curricula.
• Consulting companies are going beyond just design thinking — they’re changing how business is done with rapid prototyping and new analytical frameworks.
• China continues to lead in designing experiences in the apps and automotive industriers at a scale and level of sophistication that astounds.
• The older generation “Gen B(older)” is becoming a market opportunity for new products and services that can’t be ignored — expected to reach $15 trillion by 2020.
• Data scientist and user researcher skills are bringing both quantitative and qualitative as needed skillsets for designers in the tech industry. The later stage the company, the more that such approaches are used — and often too late.

• Custom fabrication technology that leverages computation while using less tech, traditional manufacturing ideas is becoming more accessible.
• Speech recognition has advanced to the point where the experiences provided by this technology are becoming just as important as how computer graphics technology brought GUIs to the screen.
• Augmented reality (and VR) experiments and ideas abound as the technology becomes more accessible via smartphones and inexpensive peripherals.
• Speed is a key design attribute of a mobile experience with sessions averaging on the order of 30 seconds and over half of site visitors abandoning a site visit if takes longer than 3 seconds to load.
• 88% of designers surveyed believe that it will be at least 5 years or more until visual designers are replaced by AI. AI can already do a lot right now.
• The history of AI and generative visual art goes back to the 1960s with A. Michael Noll and other artists at Bell Labs, and stretches back to Marcel Duchamp.
• AI is extremely proficient at tedious tasks that no human should really have to do, like: adjust image contrast, correct messy lines, and re-style images.
• AI is showing us the unintended consequences of running what appear to be “fair” algorithms that feed off of past activity and practices that are converted into training data. But embedded in that training data is our long history of exclusion.