TRENDS
How the Gig Economy Is Reshaping Tech Careers and IT ItselfPlatforms That Offer Flexible Designer Careers to IT Talent Complement the CIO’s Need for More Dynamic and Effective Talent Sourcing
Dion HinchcliffeVice President and Principal AnalystCopy Editor: Jim DonahueLayout Editor: Elle Froze
Produced exclusively for Constellation Research clients
May 12, 2020
TABLE OF CONTENTS
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3
The Gig Economy for IT Brings a New Deal for Talent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
Gig Work Brings a Data-Based, Color-Blind Objective Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Performance Data on Gig Economy IT Projects Shows Significant Advantages . . . . . . . . . . . . . . . . . . . . 6
Professionals Largely Benefit from Gig Economy Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
IT Employers Gain Big Advantages from Gig Economy Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Analysis from Real-World Gig Economy IT Projects Shows Real Win-Win Opportunities . . . . . . . . . . . .8
Analysis Starts with a Baseline of Traditional Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Gig Staffing Is Not Just More Efficient but Also Lower Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Gig Economy Worker Happiness Brings Higher-Quality Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Large Projects Tell the Best Story of Gig Economy Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Constellation’s Research Advisory Board . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Analyst Bio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
About Constellation Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
© 2020 Constellation Research, Inc . All rights reserved .
© 2020 Constellation Research, Inc . All rights reserved . 3
EXECUTIVE SUMMARY
A close examination of gig economy platforms, such as Upwork and Gigster, which enable businesses to hire remote staff on demand via the Internet, and their potential effect on IT employers and IT staffers in particular shows that such solutions offer marked advantages that translate into better employment arrangements for both groups .
An independent analysis of the raw data from several hundred gig economy–staffed IT projects, both large and small, shows that such projects are approximately 30% more productive while also resulting in substantially higher combined tech staff and IT customer satisfaction .
The data analysis conducted by Constellation Research for this report signals that the traditional information technology (IT) industry should look to new multiproject delivery platforms and practices that are changing the face of development just as cloud computing methods changed the nature of IT operations .
Business Themes
New C-Suite Future of Work
© 2020 Constellation Research, Inc . All rights reserved . 4
THE GIG ECONOMY FOR IT BRINGS A NEW DEAL FOR TALENT
Today, most people still associate the gig economy with lower-paying work performed on demand . Among the most-cited pay-per-task examples are the Uber and Lyft ride-hailing services as well as DoorDash and Grubhub food delivery . Yet the positive aspects of gig work—flexible hours, regularly updated choices of what work to do, the ability to maintain control, and so on—are now shaking up careers in the white-collar world .
While still predominantly a trend in the United States, the gig economy for professional work is steadily growing and expanding around the world .
The current industry data paints a clear picture of the rapid shift taking place as gig economy work goes upmarket to include professionals and to penetrate information technology (IT) departments (see Figure 1) . Recent IT consulting data shows that 72% of all gig projects were in large enterprise and professional services firms in 2018–2019, compared with 52% just two years earlier .1 This rapid
Figure 1: The Rapid Growth and Shift in the Gig Economy to Professional Work
Some Rights Reserved, 2020 by Dion Hinchcliffe
Flexible talent via online platforms was first sought by startups. Now,professional services firms and large enterprises dominate gig demand.
2018–2019
45% of gig industry staffing 27% 19% 8% 1%
2016–2017
30% 22% 37% 9% 2%
Professional Services Large Enterprises Startups Dev Firms Other
Medium-Term ProjectsTwo-thirds of projects were less than 6 months long.
Flexibility ReignsRequirements drive the structure of gig hires.
Strategic Skills SoughtIncluding strategy, technology, marketing and account.
Source: FlexingIT
© 2020 Constellation Research, Inc . All rights reserved . 5
growth is spurred by workers’ interest in flexible careers as well as businesses’ interest in convenience and efficiency . There are signs that the gig economy is finding many adherents overseas as well .
This and other alternative workforce approaches find favor as more workers look for more flexible alternatives to working at one employer full-time . The ranks of contractors, outsourcing teams, freelancers and gig workers are expected to triple in the United States to 42 million workers in 2020, according to Deloitte .2
To be sure, the success of more transactional types of gig services, such as the global freelancing platform Upwork—which specializes in midlevel professional on-demand projects that can be delivered from anywhere—have proven the model . Platforms such as Upwork, Fiverr and others have been quite successful in recent years and have shown what’s possible in terms of building a sustainable career that spans hundreds of individual gigs .
The trend itself tends to be dominated by younger workers who are behind the movement in terms of changing career expectations, setting industry attitudes and defining core behavior changes in a public way . Meanwhile, older workers aren’t being left behind . Such workers stand to benefit because age-discrimination issues they may face in some IT projects are mitigated by gig platforms’ strict meritocracy . The new approaches continually revalidate a worker’s digital reputation within the platform, backed by two-way ratings data from all of that person’s previous gig engagements .
Gig Work Brings a Data-Based, Color-Blind Objective Reality
It’s this aspect of meritocracy within most of the gig economy, where everyone’s efforts—both client and gig worker—are rated and ranked, that makes it appealing . Gig workers can create proven portfolios of happy customers and successful projects that they can then show to future employers . Increasingly, this is a data-based performance and optimization story as well because the whole industry is driven by instrumented data . Because results (in terms of both satisfaction and business effectiveness) are instrumented and measured, they may be wielded as a competitive advantage .
© 2020 Constellation Research, Inc . All rights reserved . 6
While only 6% of workers choose at first to be part of the gig economy, according to the research cited above from Deloitte, more than 10 times that number say they would take on gig work to augment existing employment . The main reasons that workers are switching to the gig economy are simple: more money, more schedule flexibility and better balance between their personal and professional time .
Performance Data on Gig Economy IT Projects Shows Significant Advantages
But the data tells the most revealing story here . A detailed data analysis conducted by Constellation Research of fine-grained project data from on-demand IT staffing firm Gigster shows the dramatically higher benefits of using a gig economy approach for IT projects . Comparing this data from 190 Gigster projects with typical industry data, Constellation Research found the following:
• Gig economy IT projects were 30% more efficient on average in their staffing .
• These projects showed customer dissatisfaction reduce by half versus typical industry projects .
• Such projects showed over three times the gig worker satisfaction rate of traditional IT projects .
This data is significant because it shows a consistent and sustained improvement over traditional staffing models that put dedicated resources on a project, where their utilization is rarely an ideal 100% but is subject to the peaks and valleys of demand within the project . Furthermore, traditional staffing resources appear to become frustrated with such demand spikes, the poorer variety of work and less control over their situation .
Professionals Largely Benefit from Gig Economy Work
The rapidly expanding gig economy is not merely a response to changing economic conditions, especially now . There are numerous and substantial reasons that workers choose to work on a contingent basis . As companies are choosing to hire more contract workers in general, these
© 2020 Constellation Research, Inc . All rights reserved . 7
workers are finding a number of advantages in using a more contemporary model . Benefits include the following:
• Working on projects for multiple companies simultaneously can help to increase skill sets and expose workers to more opportunities .
• There is more independence and freedom to choose when and where to work .
• There is less risk of job and income loss with multiple employers .
• Gig workers can earn more while working less than full-time equivalent (FTE) counterparts .
• Workers get a safety cushion in uncertain times .
• There is higher job and career satisfaction and proven success .
Of course, there are certain downsides, such as less assurance of steady work engagements and work benefits . But for professional workers who aren’t used to managing the paperwork and process overhead of subcontract work, gig platforms help to handle much of the related effort, including collecting payments and providing benefits . In this way, gig economy services take the place of traditional employers .
IT Employers Gain Big Advantages from Gig Economy Work
Sourcing talent is one of the biggest challenges that IT departments face . Most of the popular skill categories are not available without expensive and time-consuming recruiting, obtaining worker visas, paying competitive salaries and going through lengthy onboarding processes .
Gig economy platforms for the enterprise can get around these hurdles and enable IT departments to tackle just about any situation—especially if they don’t have large pools of IT resources ready to spin up and ready to deliver, which most don’t .
© 2020 Constellation Research, Inc . All rights reserved . 8
The specific advantages of the gig economy for IT include the following:
• Faster access to talent and shorter time until productivity
• Ability to hire IT staff for services not needed on a regular basis
• Agility in scaling IT staff up and down quickly to meet business demand
• Reduced cost of providing healthcare and other benefits
• Lower workspace costs
Keep in mind there are still some less-then-desirable aspects of the gig economy for IT departments . One is a loss of the contributions that staff workers add to company culture . Another is institutional knowledge retention . But these, in Constellation’s view, are largely offset by the advantages presented above .
ANALYSIS FROM REAL-WORLD GIG ECONOMY IT PROJECTS SHOWS REAL WIN-WIN OPPORTUNITIES
The gig economy is a highly instrumented industry, where work is tracked in great detail, especially for work that has structured engagements, such as IT projects .
The performance and satisfaction data routinely captured at preset intervals in the Gigster IT project dataset provides germane evidence, allowing a pattern of typical performance to emerge . Because project activities are logged by role in detail, we can look at the peaks and valleys, the behavior, and the results of gig economy IT projects in both dedicated and blended projects . This is true for both small and large projects .
The results of such an examination are illuminating . Diving deep into the datasets, we see that Gigster projects were, on average, consistently 30% more efficient for the same type of project for the
© 2020 Constellation Research, Inc . All rights reserved . 9
same time, during each stage of the project—from inception, through the midpoint and then final delivery crunch .
Specifically, an IT project run through Gigster’s talent platform consumed about 30% fewer FTE staffers over time versus a similar project staffed the traditional way . Figure 2 shows that the benefits are clear over the entire life of the project .
Furthermore, research that applies Constellation’s data analysis to several hundred gig economy projects employing Gigster’s dynamic staffing model shows these new approaches are dramatically more efficient than traditional development IT project staffing .
More interestingly, the data mostly does not indicate what is traditionally described as “crunch mode” across IT projects . Crunch mode is a common feature of IT projects in which intangible risks finally arise and must be dealt with . But more-advanced models for delivery now allow projects to be structured around proven templates that are then monitored closely to detect deviance from healthy norms baselined across many prior projects . This prevents the emergence of off-project schedule
Traditional LOE
-30%
Some Rights Reserved, 2020 by Dion Hinchcliffe
Figure 2: Gigster Level of Effort (LOE) with On-Demand Staff vs. a Traditional IT Project
Source: Gigster data analysis by Constellation Research
© 2020 Constellation Research, Inc . All rights reserved . 10
liabilities that accumulate and then present themselves as unwanted surprises toward the end of a project . This ability to maintain a large and consistent dataset of project success factors and risk models allows platforms like Gigster to provide better project management .
This is compelling evidence that this model results in better-managed projects that can tap needed resources on demand . That’s because the vast majority of traditionally staffed projects still suffer a high failure rate currently (see data below) . One key reason that the gig platform model appears to be superior is that the data from past similar projects can be consulted to pinpoint project deviations from normal progress early on . As a result, Constellation’s analysis finds that the average level of risk in a platform-hosted, on-demand staffed IT project is a rather significant approximately 5 times less than a legacy IT project (see Figure 3, which actually shows 5 .7 times less risk using general industry average data), given that Gigster’s model uses in-flight project data to manage risk much more proactively as well as to step in proactively to help address risks . This appears to be due to Gigster’s superior perspective by virtue of a large historical project dataset that informs what needs to be done and what the top risk factors are likely to be .
Traditional IT projects still have a high failure rate due to poor data-driven quality loops and limited external reviews.
Reasons for IT Project Failure
Underperformance (on cost, schedule or quality) 53%
Cancellation 31%
Successful 16%
Successful 91%
Gig Economy IT Projects in a Data-Driven Delivery Platform
Some Rights Reserved, 2020 by Dion Hinchcliffe
Figure 3. Failure Rates of Bespoke Traditional vs. Gig Economy Projects
Source: Standish Group survey of 2,500 IT projects and Constellation Research analysis of Gigster project data
© 2020 Constellation Research, Inc . All rights reserved . 11
Analysis Starts with a Baseline of Traditional Projects
To benchmark Gigster data, Constellation used a variety of IT project datasets from organizations such as IBM . Constellation confirmed that staffing is essentially static across the lifetime of traditional projects . Activity shifts among project team members over time, resulting in a relatively inefficient model because underutilized people continue to add to the project budget and overhead, as they are kept on to contribute occasionally and buy down risk but at fully loaded rates .
This leaves various staff members either too busy or insufficiently utilized at different times on the project, resulting in both overspending and underengaged staff members . Typically, business analysts and architects are occupied toward the beginning of a project . Then, in turn, developers, testers and operations and deployment staff come into play over the duration of the IT project .
The analysis then looked at the staff ramp-up curve at the typical IT project, as well as the crunch mode toward the end, and at posting staff from adjacent projects and contract labor to make up for unanticipated issues that affect project delivery . Constellation then created legacy versions of the staffing models for each type of project that Gigster engages in, and next used data on typical staff levels required for level of effort on each type of project .
The result was a matching set of staffing and project models that Constellation could use to reason about the Gigster data and compare it with norms . The findings are reported above .
Gig Staffing Is Not Just More Efficient but Also Lower Risk
One of the most interesting aspects of the data is evidence that an IT project using a digital work platform substantially reduces the risk of delivery . With between 70% and 81% of projects failing on some significant metric according to virtually every industry data source, Gigster stands out for a much lower failure rate, at only 9% of projects . This is a striking difference worthy of note and more detailed analysis .
Constellation’s analysis of the data indicates that greater process repeatability is inherent in gig platform implementations that provide continuous independent checkpoints to ensure that risks are
© 2020 Constellation Research, Inc . All rights reserved . 12
being managed proactively . This seems to be a key ability that is inherent in structuring IT project work so it can be delivered via a gig platform: lower risk not only through greater transparency in the work data but in being able to use it for regular independent risk checkpoints to ensure customer success .
Gig Economy Worker Happiness Brings Higher-Quality Outcomes
Another useful insight came from Constellation Research’s analysis of the gig project data . It became clear that developers enjoy working in this manner . Probably because developers are so data-driven in the way they work, having a gig economy platform help them create a “designer career”—that is, working in the kinds of interesting projects that they’re looking for—results in happier developers .
In the analysis of the project data and developer satisfaction scores, the conclusion is unavoidable: Developers in gig economy projects are substantially happier than traditional IT staff—a very significant 3 .6 times more satisfied on average .
There is also now a proven correlation between one’s IT staff and happier independent rankings in the final outcome: the IT project or technology product in question . Using a recent Appealie study of Glassdoor software-as-a-service company rankings against G2 (a popular crowd-based product ranking service), there is clear evidence that happier employees result in better products (see Figure 4) .
By projecting the average traditional staff level of happiness against Gigster’s project staff satisfaction measures onto this data, one can see that Gigster delivers projects in the top quintile of customer satisfaction when it comes to its end-customer rankings . This is a compelling finding and shows that gig economy workers (at least, white-collar workers), are not only much happier than their counterparts in the traditional IT world but that final project outcomes are likely to be substantially better as measured by end-customer satisfaction . The industry data also shows that workers who are substantially happier (significantly, in the case of this data) are up to 72% less likely to leave .3
© 2020 Constellation Research, Inc . All rights reserved . 13
Large Projects Tell the Best Story of Gig Economy Advantages
The bigger the project, the higher the risk . That is the classic story of IT projects . But what is interesting in the economy project data is that not only is risk lower but the efficiency is substantially greater .
Constellation Research finds that Gigster projects experienced early spikes in staff activity during the development process for the most important and expensive engineers (mobile and full-stack developers; see Figure 5) . On a project staffed with FTEs, this would push up the long-term cost ceiling for the duration of the project and/or delay the project until the FTEs are available . Neither happens in the Gigster mode . Insight: A traditional project would use two additional FTEs who were greatly underutilized, driving up costs . The gig approach results in an additional 30% in average savings .
Ove
rall
Empl
oyee
Rat
ing
Correlating Tech Employee Satisfaction with SaaS Product Ratings
Overall Public Product Rating3
5
Key Insight: Happier tech employees make customers happier with products.
Traditional IT Projects
3 5
Gig Economy IT Projects
Some Rights Reserved, 2020 by Dion Hinchcliffe
Figure 4. Happier Developers Mean Higher-Quality Outcomes
Source: Appealie and Constellation Research analysis of Gigster IT project data
© 2020 Constellation Research, Inc . All rights reserved . 14
CONCLUSION
To understand the difference and advantages of staffing IT projects using gig economy workers, Constellation Research used a recent historical project dataset with breadth, variety and depth from this nascent industry and compared it in detail against a set of typical IT project staffing profiles .
The findings are clear and unequivocal: Gig economy staffing not only results in nearly one-third more efficiency in terms of staffing effectiveness (less staff required for the same outcome), but it also lowers risk substantially by boosting IT success rates dramatically (70% to 81% IT industry average with 9% average in the gig economy dataset) .
Furthermore, on an objective basis, both the gig economy workers on IT projects and their customers are substantially more satisfied based on satisfaction scores reported by relevant stakeholders (gig workers and their clients) . The higher satisfaction scores, 3 .6 times a traditional IT project, will lead
Staffing Levels Over Time on a Larger Gig-Staffed IT Project
Some Rights Reserved, 2020 by Dion Hinchcliffe
Figure 5. Analysis of the Highly Dynamic Staff Profile of Large Gigster IT Projects
Source: Constellation Research analysis of Gigster IT project data
© 2020 Constellation Research, Inc . All rights reserved . 15
(in Constellation Research’s estimation) directly to higher-quality development outcomes that improve end-user satisfaction with the resulting IT solutions .
The data analysis for this report presents a sobering picture for the traditional IT industry, which uses a more parochial and bespoke staffing process that is not subject to multiproject feedback that informs the ongoing usage and evolution of a consistent delivery platform and practice across hundreds of projects . In other words, Gigster’s substantially more holistic approach to IT projects within a gig economy platform allows it to create a more dynamic and efficient staffing model, a more consistent and efficient work experience for gig workers, a data-driven performance management model and a more rigorous risk management approach .
Constellation also finds that when data from projects is more transparent, it results in more proactive measures to ensure on-time delivery, correct risks as soon as they emerge, and better track and reward high performers as well as weed out those who aren’t able to deliver efficiently .
In short, the gig economy for professional work—at least in the IT space—is akin to the cloud computing revolution happening in the operational part of the IT world: It creates an elastic, on-demand model that is more productive, leaner, more dynamic (ability to ramp work up and down with little penalty), more data-driven, and easier to manage and govern . Based on this data, Constellation recommends that IT departments proactively augment staff where appropriate (where long-term institutional knowledge isn’t as important, for example), including and up to a majority of IT project resources .
What’s more, this model even works with existing IT employees—hybrid IT projects performed about as well as all-gig-staffed ones .
This data, as summarized in Figure 6, not only underscores the superiority of professional gig economy platforms for the delivery of IT projects but the likelihood that it’s a superior employment model overall for professional work of most kinds that can be systematized to a similar degree as IT work can be .
© 2020 Constellation Research, Inc . All rights reserved . 16
A Note on the Analysis Methodology Used in This Report
Gigster certified and provided to Constellation Research a full set of 190 IT projects staffed by some or all gig workers . The data included task breakdown structures, resourcing loadings, hourly utilization and the resulting staff/client satisfaction and risk scores for each project . Subsequently, Constellation Research then built and validated its own traditional IT project staffing profile model, with an emphasis on large projects, which are the hardest and riskiest on which to deliver . Constellation used both data analysis and a statistical correlation approach to compare the two approaches . The data that was uncovered is presented in this independent analysis and report .
30%More-Efficient
Staffing
60+%Lower Risk
3.6xHigher Project
Satisfaction
Some Rights Reserved, 2020 by Dion Hinchcliffe
Figure 6. Summary of the Findings of Gig Economy IT Projects on a Platform vs. Traditional IT Projects
Source: Constellation Research analysis of Gigster IT project data
© 2020 Constellation Research, Inc . All rights reserved . 17
CONSTELL ATION’S RESEARCH ADVISORY BOARD
External reviews and contributions to this report were provided by vendor and end-user members of Constellation’s Research Advisory Board, who in this case were:
• Ian Gertler, well-known expert on the future of work
• Ben Haines, CIO, Verizon Media
• Jane McConnell, leading gig economy researcher
• Tony Scott, ex-U .S . federal government CIO
ENDNOTES
1 “Professional Gig Economy Report Card 2018-2019,” FlexingIT. https://www.flexingit.com/media/eoc_resume/professional-gig-economy-2018-19-report-card.pdf
2 Erica Volini, Jeff Schwartz, and Indranil Roy, “The Alternative Workforce: It’s Now Mainstream,” Deloitte Inc., 2019. https://www2.deloitte.com/us/en/insights/focus/human-capital-trends/2019/alternative-workforce-gig-economy.html
3 Ahu Yildirmaz, Christopher Ryan, and Jeff Neza, “2019 State of the Workforce Report: Pay, Promotions and Retention,” ADP Research Institute. https://www.adp.com/resources/articles-and-insights/adp-research-institute/research-topics/-/media/62FB03253C3B4B80A2EE73EB8EC29B82.ashx
© 2020 Constellation Research, Inc . All rights reserved . 18
© 2020 Constellation Research, Inc . All rights reserved . 19
ANALYST BIO
Dion HinchcliffeVice President and Principal Analyst
Dion Hinchcliffe is an internationally recognized digital thought leader, industry analyst, business strategist, enterprise architect, transformation consultant and keynote speaker . He is widely regarded as one of the most influential figures in enterprise IT .
Currently the VP and Principal Analyst of Constellation Research, Dion is an well-known industry expert on the topics of digital transformation, CIO issues, digital workplace, ecosystem strategy, digital business and next-generation enterprises . His thought leadership can be found on ZDNet, ebizQ, On Digital Strategy and the Enterprise Irregulars . He is co-author of the bestselling Social Business by Design (John Wiley & Sons) .
Dion is an Executive Fellow at the Tuck Center for Digital Strategies and was recently identified as one of the top 3 people most mentioned by IT leaders . Industry analytics firm Onalytica ranks Dion as the #2 influencer globally on the subject of digital transformation . He has keynoted or spoken at hundreds of leading industry conferences including CeBIT, KMWorld, IT Roadmap, Dreamforce, CIO Perspectives, AIIM Conference, IBM Connect and other industry events .
@DHinchcliffe constellationr.com/users/dion-hinchcliffe linkedin.com/in/dhinchcliffe
© 2020 Constellation Research, Inc . All rights reserved . 20
ABOUT CONSTELL ATION RESEARCHConstellation Research is an award-winning, Silicon Valley-based research and advisory firm that helps organizations navigate the challenges of digital disruption through business models transformation and the judicious application of disruptive technologies . Unlike the legacy analyst firms, Constellation Research is disrupting how research is accessed, what topics are covered and how clients can partner with a research firm to achieve success . Over 350 clients have joined from an ecosystem of buyers, partners, solution providers, C-suite, boards of directors and vendor clients . Our mission is to identify, validate and share insights with our clients .
Organizational Highlights
· Named Institute of Industry Analyst Relations (IIAR) New Analyst Firm of the Year in 2011 and #1 Independent Analyst Firm for 2014 and 2015 .
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· Organizers of the Constellation Connected Enterprise—an innovation summit and best practices knowledge-sharing retreat for business leaders .
· Founders of Constellation Executive Network, a membership organization for digital leaders seeking to learn from market leaders and fast followers .
www.ConstellationR.com @ConstellationR
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