By now if you haven’t heard of Klout and in a moment of vanity checked your own Klout score, you’re in the online minority. Klout engenders a lot of debate about its algorithms and relevance, but regardless of opinion, the undercurrent of the conversation is that we’re heading into a world of Klout whether we like it or not.
More broadly, we’re heading into a world of unprecedented measurability. Historically, great advances in society have been directly correlated to progress in two things: computational capability and measurement. Take for example the early age of American discovery. Until the invention of the astrolabe (a rough but effective instrument to calculate latitude and longitude) – and thus the increased accuracy of maps — marine exploration was limited to a few hundred miles off any coastline. With the ability to quickly measure location, explorers ventured progressively further away from the coast. Eventually, they ran into the Caribbean (which they first thought was China – we’ll give them a pass on that). The science of exploration and the ensuing discovery of the new world accelerated at an exponential pace after that.
As more of our daily activities move online, our ability to measure these activities is increasing. Klout is a leading indicator of this capability; a first glimpse into the ability to measure someone’s online influence. Once we have measurement, we can determine score, and then we can rank. Foursquare is a similar form of measurement – how loyal are you to a business. It simply measures your visits, scores your participation and ranks you against other customers.
Crowdsourcing marketplaces are taking measurability to the next frontier: work activity. In the same way that Klout has quantified Influence, crowdsourcing markets are quantifying expertise. Crowdsourcing companies are now quantifying the quality of software testing, paid search expertise and graphic design. No longer does the subjective and anecdotal reign; we actually have the data.
Much like Klout, the algorithms, complexity and understanding required to move from qualitative to quantitative assessment are in their infancy. There will be many permutations for both technical and emotional reasons. Expertise is a complex subject and in many cases it’s contextual. Who is more influential on Twitter: Robert Scoble or Ashton Kutcher? The answer is it depends on the context. The same applies to work expertise. A phenomenal back-end software tester might not be as good at UI testing.
What we do know is that once a solid foundation is laid, a wellspring of activity emerges around measurement. Take a common consumer example – getting a $ 5,000 line of credit on a credit card from a bank you’ve never done business with before. This is only possible now because of the standardization of credit-worthiness that came from the invention of the FICO score. This measurement allows you to receive credit card offers without having to engage directly with the bank. Once we derive benefits from such measurement, we then care to learn how to positively affect our scores (we’re all much more aware of our credit score activity now than we were 20 years ago). Systematic ratings drive an ecosystem of value.
As crowdsourcing models emerge for any form of expert labor that can be discretized and paid for based on performance and unit pricing, reputation scores will necessarily emerge with them. If you’re not participating with these scoring systems now, you’ll likely be left behind when they become critical to getting a job. During the hiring process, many social media managers now look at applicants’ Klout scores as a proxy for their true social media skills. Many engineering managers are starting to ask for TopCoder ratings or StackOverflow scores as well. In 5 years, the same will be true for most expert-based work.
Another change indicator is LinkedIn’s move to add skill-assessments to their profile pages. While still a first version and surely something they will evolve, freelancer markets such as eLance have been doing this for numerous years. Not to mention the ubiquitous eBay seller rating which is basically a customer service reputation system. The problem until now has been that these system have been based primarily on subjective human-based rankings. With crowdsourcing markets, there is an underpinning of data that drives these reputation and expertise scores. Just like Klout sees your social presence, crowdsourcing markets see the results of your work. As LinkedIn’s features progress, they will likely start to integrate these scores into your resume and profile. No longer will your resume be your own version of your work history; it will also include a data-driven third party’s assessment.
To go even further, these metrics of expert reputation are creeping into traditional businesses as well. Marc Benioff of Salesforce has all but publicly declared the company’s Chatter product is taking them in this direction. Through Chatter, Salesforce will start to derive both a reputation system and a compensation system for participants. The good news is that work-based game mechanics are emerging at the same time. Game mechanics will help us keep on the rails and remind us what’s important (to our employer or labor market). If designed correctly, they won’t be as much about the game as a reminder of behaviors that drive success. Even Klout employs game mechanics now with its badge system.
The next 20 years of work activity will see an incredible change in how we are measured. If you’re not thinking about your expert reputation and how to build it, it’s probably time to do so. The next time you look for a job, don’t be surprised if someone asks you for your score.
Niel Robertson is a three-time entrepreneur and CEO of Trada Paid Search, a crowdsourced paid search marketplace. In October of 2010, Niel introduced The Crowdsortium, a crowdsourcing industry group. You can find Niel on Twitter at @nielr1.
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