Sunday, April 29, 2012

Social Enterprise ROI? You can get there from here!

Originally published on the Acquity Group Blog.

It’s been fascinating to observe the growing interest in justifying the ROI of Social Enterprise investments over the last three to six months. It’s right on schedule, of course; the Innovators and Early Adopters have been cleared off of the curve with generally positive results, and we’re now staring into the face of the Early Majority. The challenge is that the deeper you get into the adoption curve, the more evidence-driven the adopters become.

When sitting in a roomful of business stakeholders, everyone agrees on the importance of ROI. But just try getting to consensus on what ROI looks like for Social Enterprise initiatives. The fundamental issue with trying to define and calculate Social Enterprise ROI is that the ad hoc processes you're improving have never been identified nor measured by management. Armies of managers and consultants have spent over a half-century defining and analyzing ERM processes; a quarter-century figuring out CRM processes; and, less than five (5) years focused on the convergence of collaboration, innovation, communications and shadow processes / organizations out of which the Social Enterprise emerges.

The fundamental issue with trying to define and calculate Social Enterprise ROI is that the ad hoc processes you're improving have never been identified nor measured by management.

As we’ve done Social Enterprise research and work with our clients, we’ve identified two (2) workable responses to the ROI question:
  1. Your organization can spend the upfront time identifying ad hoc processes, defining and measuring them (this generally requires patience and the support of outside expertise).
  2. Alternatively, you can find favorable user clusters in which to introduce Social Enterprise initiatives, identify critical metrics for the group, and conduct pilots. In this scenario, stakeholders agree to treat the pilot as a “black box”—comparing the “going in” metrics to the post-pilot outcomes.
We’ve also come to understand that conservative (i.e., "risk-averse") organizations almost always want to map processes first. We regularly do this work for our clients, and have developed approaches that get to consistently useful results. However, given the limited cost of standing up Social Enterprise pilots (close to zero for a SaaS solution from a willing vendor), we’re much more interested in working with our clients to help design pilots that achieve results and deliver the “quick wins” needed to justify additional investment and deployment. As always, there are caveats: if there are legal / regulatory / compliance or cultural / organizational issues that would limit pilot effectiveness or create excessive unmanaged risk, then a process mapping approach is a worthwhile first step.

It's interesting to note that many of the leading solution vendors in the Social Enterprise space (e.g., Jive, Yammer, SocialText) have coalesced behind the "pilot and learn" approach, while enterprise platform vendors (e.g., Microsoft) still trend towards "learn then deploy".

So by all means, ask the ROI question. Just understand going in that there’s work to do to define it, but that you have options regarding how you get to the answer.

Tuesday, April 24, 2012

the future of knowledge work and the return of task specialization

“The means of production should be owned by the purrrletariat.” - Lenin Cat

If you’ve been tracking my Twitter feed (@CycleBot) recently, you’re aware that I’ve been using Amazon’s Mechanical Turk to investigate possible correlation of worker engagement and brand affinity. I’ll be sharing the results of this research, as well as my practical experiences using Mechanical Turk, over the coming weeks. As I’ve been working through this project, as well as observing the rapid growth and evolution of crowdsourcing and open innovation practices, I’ve started to get a personal sense for the emerging future of knowledge work.

I’m not ready to go out on a limb and speculate on the timing of wholesale adoption of new work models, especially as I think we’re still 2-3 years away from a clear inflection point. But when you look at crowdsourcing markets such as elance (who just surpassed the $500m mark in work facilitated(1)) and task facilitators such as Mechanical Turk (still in beta, but already averaging $15k+ in payouts per day(2)), it’s clear that the future of knowledge work is experiencing a dramatic shift towards task specialization. Compared to the Industrial Revolution, which created unhealthy co-dependencies between workers and the enterprise, the timing and nature of this current revolution is refashioning the market for work in ways that should ultimately be beneficial for workers, businesses, and society as a whole. It’s my opinion that knowledge workers will increasingly be free agents for hire in this new order, executing on pre-defined activities and moving on to the next opportunity.

The key trends I see driving this change are:
Drivers of Future Knowledge Work

Anywhere, anytime access to work

No surprise here: there’s already a ton of data demonstrating the ubiquity of devices and networks to connect us to our tasks and the resources required to complete them. And demand is moving in lockstep with supply: a recent Cisco global survey of 2,800 college students and young professionals showed that 40% of them would accept a lower-paying job in exchange for better access to social media, the ability to work from the location of their choice, and to select their own mobile device(3).

This rapid shift is driving behavioral change towards work. As I write this, I’m sitting in my favorite overstuffed chair with a view of the local deer mowing down my tulips (a friend once referred to my tulips as “deer nachos”). Today, I’ve spent time with my wife and son during the “business day”, chatted with the neighbors over lunch, and strolled to the library for a change of scenery and some inspiration. It’s been over a decade since Faith Popcorn put labels to the trends of “cocooning” and “cashing out”(4), but the availability of anytime, anyplace access is putting the exclamation point on the trends. A consequence of this shift is that worker identity is increasingly less affiliated with the employer and more focused on the task.

By extension, this trend also expands the marketplace of potential knowledge workers. For many midmarket companies (MMCs) and smaller firms, solutions such as Amazon’s Mechanical Turk create low-barrier opportunities to quickly and easily outsource and offshore work. The population of workers on AMT is globally diverse (current participation from at least 66 countries identified(5)) and continues to expand in numbers and nationalities. MMCs and smaller companies can plug into a global workforce without the concerns of infrastructure investment, currency exchange or political risk. As the opportunity space grows for businesses, so also does the competitive space for knowledge workers. The end result is an emerging global market for knowledge work.

Increasing atomization of work

When I first started thinking through this topic, the analogy that came to mind was analog vs. digital. Historically, knowledge work within the enterprise was experienced as a series of peaks and valleys—periods of high activity moderated by time for planning, development and socialization—akin to an FM radio signal. As we’ve moved into the digital age, the nature of our work has evolved to be much more packet based—either you’re executing on a task (“on”) or looking for the next task (“off”). Opportunities for career growth and forward thinking occur outside the digital workstream, if they occur at all.

Then the obvious analogy struck me: mass production. What’s changing about the nature of knowledge work is the increasing encapsulation of the basic unit of work (i.e., a task). As a result of advances in business process design, information management, and technology, knowledge workers are better equipped than ever with the contextual information required to complete a task without external intervention. Consider: a common use case for Amazon’s Mechanical Turk is content categorization. Workers on Mechanical Turk develop skills and achieve qualification levels in content categorization, and businesses create self-contained tasks for these workers that provide them with all of the context required to complete the category assignment activity(6). This echoes the mass production innovations of the Industrial Revolution, where assembly activities were bundled into self-contained work units. As long as the upstream workers on the assembly were all doing their jobs correctly, the individual worker could accomplish her work unit without additional input or interruption. We have already achieved this level of segregation for many types of knowledge work, and the list will continue to expand.

Increasing importance of knowledge specialization

Hand in hand with the atomization of work is the increasingly specialized knowledge required to accomplish a given business task. As recently as 15-20 years ago, a marketing professional could have a successful career as a generalist. Today, specialization is the name of the game: interactive marketing, analytics, campaign management, lead management, etc. Similar drives towards specialization are occurring throughout the professional knowledge domain.

The two (2) primary catalysts of this trend are: the increasing capabilities of automation solutions; and, the exponential growth of the knowledge corpus. Regarding automation, Business Insider recently published a post asking whether developers—the footsoldiers of the automation revolution—would become obsolete(7). The article profiles a startup company in the process of building a platform that would eliminate much of the front-end development and optimization required to launch a new multi-channel web presence, turning the complexities of site creation into layman’s activity. Of course, companies have been chasing this capability for as long as there have been websites. The difference is now is that we’re nearing solution maturity.

Talent doesn’t become obsolete; the definition of talent changes, and talented people equip themselves to fit. Just like COBOL and FORTRAN developers learned C+ and Java (or retired), generalists of today whose work is being replaced by automation will move to areas of deeper specialization. Developers who once wrote exception handlers for webforms will learn to optimize Latent Class Analysis algorithms for large datasets (or retire).

Which brings us to the continuing expansion of the knowledge universe. Certain domains started early down the path of specialization as a practical response to the amount of knowledge required by a person to be minimally effective and keep pace with the introduction of new knowledge (medicine is the easy example, engineering and law are others). Until recently, the business world has held on to the belief that talented generalists make the world go round—a perspective no longer sustainable as the pace of innovation and the brutal efficiency of the market continues to ratchet upwards. Instead of getting caught in a squeeze play (between the need for access to specialized resources and the expense of maintaining dedicated specialized resources) more and more companies (especially at MMC and smaller scales) will opt to farm out specialized activities instead of hire.

Activity / workflow management solutions

While still maturing as a foundational, business-managed capability, the future value of business process management (BPM) is already apparent. Business processes have evolved from whiteboards and guesstimation to rapidly configurable and measurable system-managed workflows. The task encapsulation required to enable robust knowledge work markets (e.g., providing effective context and intuitive activity design) will require further evolution of BPM solutions, standardization of common task inputs / outputs, and new insights and approaches to user experience design; but, significant efforts to address these issues are already underway(8). In addition, enterprises will need time to evolve their structures and define effective practices to effectively integrate the crowdsourcing of knowledge work.

Adeptly applied, BPM will be a game-changer for the transformation of knowledge work. As BPM solutions mature and move up the knowledge value chain, the economic focus will shift from the worker to the task. To see what the future looks like, sign up as a worker and spend some time performing tasks on Amazon’s Mechanical Turk (lower on the value chain, standardized inputs / outputs) or get your own personal logo created at 99designs.com (a bit higher on the value chain, but also based on standardized inputs / outputs).

Activity scoring metrics / gamification models

A key component of the evolving BPM solution set is the visibility and use of performance metrics in the worker experience. Worker metrics have expanded beyond their early successes in customer service and industrial processes to become a management tool across the diversity of enterprise processes (as evidenced by the growing interest in workforce analytics(9)). In a crowdsourced knowledge market, metrics and gamification drive pursuit of performance on both the buyer and seller sides of the transaction. Buyers (businesses) have objective, quantitative data on which to allocate tasks and compensate for output. Sellers (knowledge workers) have an unambiguous understanding of the relationship between performance and compensation, and can make informed cost / benefit decisions regarding additional investments in skills and expertise development.

Disillusionment with the corporate model

For many, the ongoing parade of corporate scandals and fraudulent activity (beginning in the last decades of the 20th century and culminating with the Enron / Andersen and mortgage crises in the first decade of the 21st) has stripped away the veneer of the corporation as “citizen”. While government and businesses have reacted with an array of corrective measures—Sarbanes-Oxley, the Consumer Financial Protection Bureau, Corporate Social Responsibility, enhanced internal control frameworks)—public confidence will be slow to return. In a recent Gallup survey of honesty and ethics among professions, “business executives” were ranked 14th out of 21 professions evaluated. The only professions ranking lower were: labor union leaders, stockbrokers, advertisers, telemarketers, lobbyists, members of Congress and car salespeople(10).

Viewed through a pragmatist’s eyes, the singular purpose of the corporate structure is the effective and efficient aggregation and allocation of capital. However, the role of the corporation expanded broadly during the 20th century, eventually taking over many responsibilities previously held by the individual or community (e.g., social hub, healthcare and retirement provider, personal development resource). Commensurate with this growth, the Western world increasingly romanticized the corporate structure, positioning it and it’s practitioners as the ultimate realization of the capitalist ideal. All for a business structure originally conceived to make it easier for people to pool and invest their money.

Ultimately, society is healthier if the responsibilities that have been transferred to the corporation are returned to the community and the individual. Not only is personal freedom increased, but the influence of corporations in community and government affairs is diminished. The transition of the knowledge work market from a focus on the worker to the task should accelerate this transfer, and allow the corporation to return to its intended role as manager of capital flows. While presently not a significant factor, continuing ethical lapses in the management of corporate structures will likely result in accelerating the migration of knowledge workers to independent status.

Generational shift in values

A substantial body of academic research identifies the clear differences in the work values of younger generations, especially in the developed world(11). Compared to older workers, young people entering the workforce today are more driven by leisure and extrinsic values, and less motivated by the intrinsic, social and altruistic values of work. This dynamic has significant implications for the design of future work. As the importance of the workplace for providing meaning, community and opportunities to help others diminishes, the value and relevance of the ancillary roles adopted by the enterprise (i.e., activities other than capital acquisition and allocation) also decreases. Further, the task-driven nature of future knowledge markets is directly aligned with the younger generation’s focus on leisure and extrinsic rewards. In a task-based market model, knowledge workers have the freedom to choose when and where they work; and, there is a direct and unmistakable relationship between task performance and compensation. Recent difficulties in the economic environment will also increase the likelihood that younger workers will be more receptive to alternative forms of work vs. the long-term employment models available to older generations.

Conclusion: it’s a free agent future

Where does all this lead us? Obviously, any number of factors could impact the nature of future knowledge work: regulatory action, geopolitical upheaval, pace of technological change, economic events, cultural resistance, the coming zombie apocalypse. However, by observing the changes already underway and projecting the identified trends into the future, it’s clear to this author that the current model of knowledge work is in for a significant change. From the perspective of the individual, this transformation unlocks the organizational structures established and evolved since the Industrial Revolution, and makes available the pre-industrial “independent craftsperson” model as a viable option for earning a living.

From an enterprise perspective, a wide range of new opportunities open up. Freed from the requirement to allocate capital towards the maintenance of a permanent knowledge workforce, leaner organizational structures should emerge. To be certain, the enterprise will always need to maintain a core of strategic resources with a clear understanding of its purpose and goals to sustain its competitive advantages (primarily via the effective allocation of capital). However, the ability to manage capital for knowledge work more dynamically and with greater precision creates the potential for greater innovation. Ideas that couldn’t get to target ROI using existing structures can be explored and given the opportunity to evolve into meaningful lines of business. Capital allocation is freed from tradition and organizational culture(12), and the enterprise core team adopts a role similar to that of a venture capitalist.

Sunday, April 22, 2012

What does Turker Nation think of your brand?

I’ve completed the information gathering phase of my current research effort—exploring the relationship between brand opinion and crowdworker engagement. While I’m still churning through the data analysis, I thought I’d share some descriptive statistics with you to give you a sense of what’s coming. For an overview of how I produced these numbers, see the Methodology Overview (below).

Turker opinions on US consumer brands

As part of the survey methodology, each participating “turker” (a worker on Amazon Mechanical Turk, a crowdworker platform) was asked their opinion of two (2) well-known US consumer brands. They were asked to rank their opinion on a scale from “1 – Poor” to “5 – Excellent”. While the average score of each brand is not specifically relevant to the research question, the results do paint an interesting picture, as indicated by the following graphic.
Brand Ratings by AMT Workers
What’s interesting is the manner in which some of the ratings skew when compared to other measures of brand performance. Consider Volkswagen, which respondees scored third highest out of the 35 brands evaluated: or Nintendo, which scored fifth highest. In the 2011 Interbrand Global Top 100 Brand Rankings(1), these two brands placed 47th and 48th, respectively. This is well back in the pack from Google (Interbrand #4), Nike (#25) and Coca-Cola (#1). The survey did include an open response question, asking for a rationale of their opinion. I hope that an analysis of this information will provide additional insight and testable hypotheses.

Knowing the identity of the task provider

While some companies are attempting to maintain anonymity within Amazon Mechanical Turk (“AMT”), this is likely to be counterproductive. As the following chart indicates, a third of Turkers think it’s “very important” to know for whom they’re working, and another two-fifths are at least interested.
Brand Ratings by AMT Workers
There are a variety of reasons for wanting to know, and the subject deserves further analysis. An obvious reason, identified by reviewing discussions on the Turker Nation discussion site (http://turkernation.com/) is that there have been issues with payment from certain requestors. Also, new requestors are viewed with suspicion until they’ve demonstrated their consistency and reliability. Other Turkers are selective about the organizations for whom their willing to work—this is the focus of my research, and will be covered in a future post.

Methodology Overview

Over the period from April 5th to April 19th, 2012, I published a worker task for completion on Amazon Mechanical Turk (“AMT” - http://mturk.com). The task was a survey comprised of five (5) questions to gather information on brand / company opinion and task selection drivers. The task was published to AMT workers (“Turkers”) located in the United States (to provide for consistency of brand awareness) who have completed more than 500 tasks with a 90%+ approval rate on their completed tasks. These filters were implemented per suggested best practices to avoid potential bots and spammers.

Regarding the representativeness of AMT workers, there have been numerous studies performed that indicate that “Mechanical Turk workers are at least as representative of the U.S. population as traditional subject pools, with gender, race, age and education of Internet samples all matching the population more closely than college undergraduate samples and internet samples in general.”(2) As result, this initial study chose not to collect additional demographic data, although future research may extend into this area.

Out of a pool of 1,200 potential responses, I received 1,002 task submissions. After eliminating incomplete responses and multiple responses from the same worker (to reduce sample bias) I was left with 728 valid responses on which to base analysis. On average, a worker spent 1 minute and 48 seconds completing the survey.

Notes

(1) "Best Global Brands 2011." Interbrand. 2011. Web. 22 Apr. 2012.

(2) Paolacci, Gabriele, Jesse Chandler, and Panagiotis Ipeirotis. "Running Experiments on Amazon Mechanical Turk." Judgment and Decision Making. Society for Judgement and Decision Making, Aug. 2010. Web. 22 Apr. 2012.

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What does Turker Nation think of your brand? by Steven Beauchem is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.