2017 Design Salary Survey Tools, Trends, Titles, What Pays (and What Doesn’t) for Design Professionals John King & Roger Magoulas 2017 DESIGN SALARY SURVEY Take the Design Salary and Tools Survey INTERACTION DESIGN IS A YOUNG FIELD Anonymous and secure, next year’s survey will experiencing tremendous, fast-paced growth provide more extensive information and insights As a discipline, it’s still defining itself, keeping into the demographics, roles, compensation, work pace with rapidly evolving technologies Sorting environments, educational requirements, and tools out design titles, roles, responsibilities, tools, and of practitioners in the field high-value skills isn’t easy when everything Take the O’Reilly Design Salary Survey Today is changing so quickly (And don’t forget to ask your design colleagues to So we’re setting out to help make more sense of it take it, too The more data we collect, the more all by putting a stake in the ground with our annual information we’ll be able to share.) Design Salary Survey Our goal in producing the sur- oreilly.com/design/2018-design-salary-survey vey is to give you a helpful resource for your career, and to keep insights and understanding flowing But to provide you with the best possible information we need one thing: participation from you and other members of the design community I 2017 Design Salary Survey Tools, Trends, Titles, What Pays (and What Doesn’t) for Design Professionals John King & Roger Magoulas 2017 DESIGN SALARY SURVEY REVISION HISTORY FOR THE FIRST EDITION by John King and Roger Magoulas 2017-02-08: First Release Editor: Mary Treseler Designer: Ellie Volckhausen Production Editor: Shiny Kalapurakkel While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work Use of the information and instructions contained in this work is at your own risk If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights Copyright © 2017 O’Reilly Media, Inc All rights reserved Printed in Canada Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472 O’Reilly books may be purchased for educational, business, or sales promotional use Online editions are also available for most titles (http://safaribooksonline.com) For more information, contact our corporate/institutional sales department: 800-998-9938 or corporate@oreilly.com January 2017: First Edition 2017 DESIGN SALARY SURVEY Table of Contents The 2017 O’Reilly Design Salary Survey iii Executive Summary Introduction Salary Overview Geography Age Versus Years of Experience Gender 12 Industry, Company Size 13 Coding Time, Programming Languages 16 Tasks 19 Meetings 22 Working with Other People 23 Types of Products, Products or Services 26 Design Process 28 Tools 30 Tools: Wireframing and Prototyping 33 Tools: Information Organization / Architecture 38 Conclusion 43 Appendix A: Adjusted Median Salary 44 V 2017 DESIGN SALARY SURVEY OVER 1,000 RESPONDENTS FROM A VARIETY OF INDUSTRIES COMPLETED THE SURVEY YOU CAN PRESS ACTUAL BUTTONS (and earn our sincere gratitude) by taking the 2018 survey—it only takes about to 10 minutes, and is essential for us to continue to provide this kind of research oreilly.com/design/2018-design-salary-survey 2017 DESIGN SALARY SURVEY Executive Summary THE 2017 O’REILLY DESIGN SALARY SURVEY explores the landscape of modern design professionals, giving details about their roles and how much they earn The results are based on data from our online survey that collected 1,085 responses We pay special attention to variables that correlate with salary, but this report isn’t just about money—we present a range of information, including the popularity of design tools, tasks, and organizational processes In what is now our second salary survey, we find some consistency as to what matters in the field of design: that the better-paying design jobs tend to concentrate in tech centers; that experience matters more than age; that knowing more tools, working with more people in a wider variety of roles, and working for larger organizations all correlate with higher wages And, in a sign that some things in the design world resist change (in some cases, whether we like it or not), we still see women making Some key findings include: ■■ The West Coast (CA, WA, OR) has the highest salaries— salaries are high even relative to those states’ per capita GDP ■■ Healthcare, banking, and computers/hardware respondents report the highest salaries ■■ Respondents from large companies report higher salaries ■■ Agile is the most popular design process; however, those using LeanUX or a hybrid of different processes earn the most Designers reporting no process earn the least less than men and that most designers still use pen and paper as their primary design tool ■■ Designers reporting no process earn the least ■■ Higher earners use a wider selection of tools ■■ For prototyping and wireframing, salaries are highest among those that use Sketch We hope that you will find the information in this report useful If you can spare 5–10 minutes, please go ahead and take the survey yourself: oreilly.com/design/2018-design-salary-survey 2017 DESIGN SALARY SURVEY Introduction FOR THE SECOND YEAR RUNNING, we at O’Reilly Media have conducted a survey for designers, gathering information about their compensation and details about their work This year, 1,085 people from 48 countries took the survey Respondents are mostly UX, product, and graphic designers, but there are also a fair number of developers and other professionals involved in product design The survey was conducted online, collecting responses from December 2015 to December 2016 Throughout the report, we quote median salary statistics for various groups of people, such as those respondents who used a certain tool or came from a particular industry Since these figures can be misleading if the variable in question correlates with geography or experience, we also sometimes quote a median “adjusted” salary Technical details are in Appendix A 1,085 people from 48 countries took the survey While typical for online surveys, the methodology we used of a self-selecting, uncontrolled respondent pool can lead to less than ideal results However, the broad range of respondents’ geographies, industries, and company sizes helps mitigate the issues associated with a small, narrow sample In the horizontal bar charts throughout this report, we include the interquartile range (IQR) to show the middle 50% of respondents’ answers to questions such as salary One quarter of the respondents has a salary below the displayed range, and one quarter has a salary above the displayed range TASKS (MAJOR INVOLVEMENT ONLY) WIREFRAMING SHARE OF RESPONDENTS 17% INDESIGN 17% 22% BALSAMIQ CSS/HTML 40% 14% OMNIGRAFFLE 11% ILLUSTRATOR KEYNOTE 6% 40% AXURE SKETCH 4% UXPIN 57% PENCIL AND PAPER 34 TASKS (MAJOR INVOLVEMENT ONLY) WIREFRAMING SALARY MEDIAN AND IQR (US DOLLARS) Pencil and paper Sketch Illustrator CSS/HTML Tool Balsamiq InDesign Omnigraffle Keynote Axure UXPin 0K 30K 60K 90K 120K 150K Range/Median 35 TASKS (MAJOR INVOLVEMENT ONLY) PROTOTYPING SHARE OF RESPONDENTS 11% AFTER EFFECTS 6% 19% 26% MARVEL KEYNOTE AXURE 5% PROTO.IO 41% INVISION 5% PIXATE 44% HTML/CSS 4% PRINCIPLE 56% 4% PEN AND PAPER FRAMER 4% FLINTO 36 TASKS (MAJOR INVOLVEMENT ONLY) PROTOTYPING SALARY MEDIAN AND IQR (US DOLLARS) Pen and paper HTML/CSS Invision Axure Keynote Tool After Effects Marvel Proto.io Pixate Principle Framer Flinto 0K 30K 60K 90K 120K 150K Range/Median 37 2017 DESIGN SALARY SURVEY Tools: Information Organization / Architecture THE NEXT TOOL CATEGORY IS INFORMATION ORGANIZATION/ARCHITECTURE, including software for card sorting and mind mapping 45% of respondents use at least one tool in this category, but most that did use just one No single information organization/ architecture tool is used by more than 10% of the sample, in stark contrast with some of the other tool categories, such as wireframing or project management The most commonly used information organization/ architecture tools are Optimal 38 Sort, Google Drawings, Simple Card Sort, and XMind Users of each of these four tools have above-average salaries ( For XMind, median salary was only $70K, but median adjusted salary was $86K The shift is due to XMind being much more popular outside of the US than within the US.) More generally, respondents who Respondents who use any information organization/ architecture tool earn more than those that don’t: use any information organization /architecture tool earn more than those that don’t: the difference in median adjusted salary is $9K INFORMATION ORGANIZATION / ARCHITECTURE SHARE OF RESPONDENTS 4% 4% MIND NODE 4% GLIFFY DRAW.IO 5% SALARY MEDIAN AND IQR (US DOLLARS) MINDMEISTER Optimal Sort 5% Google Drawings XMIND Simple Card Sort 6% Tool XMind MindMeister SIMPLE CARD SORT Draw.io 6% Gliffy GOOGLE DRAWINGS Mind Node 0K 10% 30K 60K 90K 120K 150K Range/Median OPTIMAL SORT 39 2017 DESIGN SALARY SURVEY Tools: User Research and Testing The category of user research and testing tools is notable for its variety: 21 tools are used by at least 1% of the sample, far more than any other category About two-thirds of the sample use one or more of these tools, although only 30% of the sample use more than two The top tools in this category are SurveyMonkey, Skype, GotoMeeting, User Testing, Google Hangouts, and Webex Differences in salaries among users of various user research tools are not significant, although, as with information organization/architecture tools, respondents who use at least one of these tools tend to have higher salaries than those that don’t, again by a margin of $9K TASKS (MAJOR INVOLVEMENT ONLY) USER RESEARCH AND TESTING SHARE OF RESPONDENTS 8% TYPEFORM 17% 16% WEBEX GOOGLE HANGOUTS 19% 6% MORAE 6% SILVERBACK USER TESTING 5% 19% OPTIMAL GOTOMEETING 4% USER ZOOM 23% 4% SKYPE SURVEYGIZMO 25% SURVEYMONKEY 41 TASKS (MAJOR INVOLVEMENT ONLY) USER RESEARCH AND TESTING SALARY MEDIAN AND IQR (US DOLLARS) SurveyMonkey Skype GotoMeeting User Testing Google Hangouts Tool Webex TypeForm Morae Silverback Optimal User Zoom SurveyGizmo 0K 30K 60K 90K Range/Median 42 120K 150K 2017 DESIGN SALARY SURVEY Conclusion THE FIELD OF DESIGN HAS SEEN PROFOUND CHANGES IN THE LAST DECADE—new mediums, new tools, new frameworks for thinking about design and how and where design principles should be applied Keeping up with the evolving tool ecosystem can have an impact on one’s career development We see that those adopting particular tools and techniques, e.g., Sketch and Invision, Agile, information management, and testing, all correlating with higher salaries We also see that those who know more tools, work in larger organizations, interact with a wider variety of roles, and work on multiple platforms earn more—information that designers can use to help expand their career horizons As design principles and design thinking move beyond the world of designers, we see these findings as relevant well beyond the world of design Software developers, data scientists, or anyone who does design work or works closely with designers can benefit from understanding what designers use and how they work When we quote statistics about salary, for example, that users of this tool make this much more than users of that tool, it’s important to remember that learning the “high salary” tool is not guaranteed to give you a raise This survey data is observational, and we can’t assume cause and effect On the other hand, knowing that particularly well-paid designers frequently use some tool might be a potential sign that this tool is especially efficient or powerful, and that alone could be enough justification for trying out a new tool This research is an ongoing project, and it depends on your participation If you’ve found this report useful, please consider taking to 10 minutes to complete the 2018 survey yourself for next year’s report: oreilly.com/design/2018design-salary-survey Thank you! 43 2017 DESIGN SALARY SURVEY Appendix A: Adjusted Median Salary GEOGRAPHY AND EXPERIENCE CLEARLY MAKE A DIFFERENCE IN SALARY, and this is fully expected However, since geography and experience can correlate with other variables, unless we analyze all three variables together, it can be hard to tell whether variations in salary are due to these variables or to geography/experience For example, age correlates with experience and with salary, but if we consider groups of respondents with equal experience, then age no longer correlates with salary (at least, strongly or monotonically) This is what we mean when we say that age and salary don’t correlate when we “block” years of experience To give another example, this time with geography: the median salary of the 9% of respondents who say they code over 20 hours/week is $50K, while the rest of the sample (those who spend less time coding, if any at all) is $80K However, the difference is attributable to the fact that most of the people who code over 20 hours/week happen to come from places that have lower salaries in general For example, 36% of respondents from India, Russia, and Ukraine say that they code over 20 hours/week, while only 1% of California respondents This probably shouldn’t be taken to mean that CA design professionals don’t code: correlations like this will appear frequently on such surveys; namely, when there is little 44 control over the sampling This correlation is likely just noise that we should try to filter out The solution we use in this report is to provide, when appropriate, an additional metric, the adjusted mean salary The first step in computing this metric: is to create a simple model to predict salary using country/state and experience After trying a few economic metrics to quantify geography, we found that per capita GDP gave the best results.2 Using this survey’s data, no complicated modeling technique or transformation made a big improvement over a simple linear model, so we stuck with the latter The model is: predicted_salary = 1.95 x years_of_experience + 1.26 x per_capita_GDP – 1.29 where monetary values are in thousands of USD, and years of experience is capped at 20 (for someone with more than 20 years of experience, the value inserted into the model is 20) For example, the predicted salary of someone with years of experience from Australia (where the per capita GDP is $51K) is $76.5K This model explains about half of salary variance in this sample Both country and state numbers were taken from Wikipedia Country figures are from the IMF column http://bit.ly/2iCUvcD 2017 DESIGN SALARY SURVEY We use this model to create the aforementioned “adjusted median salary” statistic This works by recalculating salaries as if the respondents who received them were from a single, fixed place and had the same amount of experience The actual fixed values are somewhat arbitrary, and we pick values close to the sample averages: seven years of experience and $51K for the per capita GDP, which is roughly the per capita GDP of Australia, Denmark, Singapore, Ohio, North Carolina, and Wisconsin To adjust someone’s salary, we simply subtract an amount that the model attributes to their experience and geography, and then add a fixed amount for seven years of experience and a per capita GDP of $51K we are really just including residuals, and the conversion from residual to adjusted salary (i.e., the operation of adding $76.7K) is performed to convert the number to something less abstract and so that we don’t have to introduce technical language (“residual”) into the text Perhaps a simpler way of understanding the calculation is to consider the residual, the difference between the observed (reported) salary and the predicted salary If someone earns much more than we would expect given their experience and location, their salary residual is high We calculate the residual and then add it to $76.7K, the predicted salary for someone with seven years of experience living in a place with a per capita GDP of $51K However, the simple linear model above performed just as well as a few others we tried that attempted to explain a more complicated relationship, and furthermore, the simplicity has the major advantage that it is easier for you, the reader, to plug in your own numbers Unlike the models in other O’Reilly salary surveys, including last year’s Design report, this model only takes two variables, so insofar as there are other relevant variables that affect salary, this model will miss them More fundamentally, the variance of salaries for any given experience and per capita GDP is quite high: the predicted salary that the model outputs is an average, and any particular salary may fall a ways from it For that reason, the real value of this model is not to predict someone’s salary, but to allow us to compare groups of salaries in a way that the comparison is minimally impacted by significant differences in experience and geography For example, suppose someone from New York with five years of experience earns $120K According to the model, this person is expected to earn $100.3K, so they “outperform” the expectation by $19.7K (this is the residual) If we add this $19.7K to the fixed $76.7K, we arrive at the adjusted salary, $96.4K It is worth noting that a single adjusted value in isolation doesn’t have much relevance; the real purpose of presenting these adjusted values is comparison In a sense, It is likely that with more data, a more complicated model (i.e., one that still just takes in experience and GDP, but is not a simple linear model) would provide better results For example, it seems likely that not every incremental year of experience is the same (e.g., to years versus 13 to 14 years) or that experience has the same relation with salary in every place (e.g., one year of experience adds as much in Switzerland as it does in Poland) 45 We need your data To stay up to date on this research, your participation is critical The survey is now open for the 2018 report, and if you can spare just 10 minutes of your time, we encourage you to take the survey http://www.oreilly.com/design/2018-design-salary-survey 47 Wait. There’s more easy ways to stay ahead of the game Design doesn’t stand still—neither should you Sharpen your skills and advance your career 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O’Reilly Media, Inc D1428 ... salary However, it does appear that interacting with a wider variety of roles correlates positively with higher incomes: the adjusted median salaries of respondents who interact with one, two,... more designers and employees The minority of respondents (7%) who work with industrial designers earn high salaries The minority of respondents (7%) who work with industrial designers earn high... management) Task Information architecture Leading design critiques Requirements gathering Storytelling User research Pitching (to clients or management) Usability testing Project management Managing