by Matt Manning
For the information industry, the question of customers’ return on investment in data subscriptions and licenses is an existential one: without a clear ROI, renewal rates go down and information services wither away (see The Importance of Being Used). A corollary to being able to
prove the worth of a data set is that you can only charge top dollar if clients can import it into their existing CRM, BI or other systems. This also works if you’ve gone down the road of bundling software and content into apps or online services with robust functionality. Both approaches allow customers to make immediate use of the data. Companies with clear case studies highlighting the cost-effectiveness of their solution to clients’ problems are best positioned to succeed.
This success means an offering’s features have become progressively more important than the content itself. Users’ expectations on data integration, analysis, and visualization continue to creep upward as people interact with increasingly powerful tools with intuitive interfaces, from in-vehicle GPS to Nest thermostats. But have rising functionality expectations caused the execs managing data businesses to lose track of the importance of identifying and bundling unique or hard-to-find datasets? I think this may be true today, but perhaps the answer is right under managers’ noses in the form of unique user data gathered by their digital products.
Take start-up StreetContxt, a niche aggregator similar to MarketResearch.com. They bundle specialized content, in this case research reports from investment advisory firms, for their financial industry audience. What they do next is what makes them different: they sell information on users interested in particular industries to the folks flogging investment opportunities in those industries.
The act of blurring the line between content and user/usage data for an information service typically involves giving the content to the end-user outright so they’ll agree to surrender their metadata. This emerging paradigm has been evolving for years and it gets more interesting the more aggressively it is implemented. For example, the more data customers “consume” on a B2B buyer’s guide site under this type of model, the more revenues increase. This is because now there is more high-value data (that costs nothing extra to obtain) to be monetized.
It’s a tantalizing proposition and I expect to see more and more variations on this model.
posted by Shyamali Ghosh on February 1, 2016
by Matt Manning
One of the most underappreciated aspects of the rise of crowdsourcing is that it’s laying the groundwork for a fundamental change in the very nature of work. The construct of the M-F, 9am-5pm, on-site, day job is now only marginally workable. Employers find it more difficult to get demonstrable ROI on their investments in salary, overhead, and benefits, while employees have trouble fulfilling their personal and family obligations within rigid schedules. At the other end of the spectrum, the “gig economy” of Uber and TaskRabbit offers extreme flexibility to both employers and employees, but only for certain types of work and often for only modest compensation. It seems likely that in the near future, workplaces will blend the best parts of both old and new models, bringing vastly more flexibility to both sides of the employer-employee equation and better ROIs for everyone.
The imperatives driving more flexible work models are:
- lower overhead for businesses
- more profit
- more growth
- more innovation
- less commuting for employees
- reduced carbon in the atmosphere
- more time spent on productive activity
- more money in the employees’ pockets
That sounds like the telecommuting and paperless office paradigms predicted in the 1970s, but in 2015 we have even more technical advantages:
- Ubiquitous, reliable, cheap communications technology (mobile, WiFi, virtual PBX) means employees can be 100% available to the employer regardless of their location.
- The speed and power of laptop computers and peripherals (flash memory, the cloud, external drives) has gotten to the point where large, heterogeneous tasks don’t demand fixed-location PC workstations and have fewer storage constraints.
- Centralized work platforms like WorkFusion allow for secure, shared access to documents, a digital “paper trail” of tasks performed, and easy comparison of the productivity of peer groups. TribeHR and ClearCompany are two HR-related platforms leaning in this direction.
These technologies in combination could mean that before long, people will share the same physical space with co-workers only during important meetings and company holiday parties, BUT there is one underlying assumption that stands in the way. Crowdsourcing was built on a “pay for performance” model where the work has a measurable output and workers can be compensated for production output instead of hours spent at work. So, the question becomes: Can a platform based on a pay-for-performance model work for most office jobs where work is more varied and complex? Sales departments are the most obvious “yes,” but I believe it’s possible to manage most other work via platforms originally made for crowdsourcing.
Examples:
- Break an HR staffer’s activity down into
- doing annual worker salary reviews
- new hires onboarded
- job listings placed.
- Measure a marketer’s productivity by
- the number of social media efforts posted per day
- media mentions
- number of campaigns created and deployed
- An accounting executive’s work involves
- submitting government filings
- checking expenditures v. the budget
- reconciling invoices and payments.
Once the work and productivity metadata for an office worker is stored centrally, it’s simple to compare it to other workers in the same role within the company or across similar organizations. Managers can check the output easily, so a single manager can manage more staffers, reducing the need for costly managers.
This kind of centralized assignment and work review enabled by crowdsourcing platforms is something that I think more operations managers will soon appreciate for the transformative development that it is—a move towards better, faster, cheaper that can benefit everyone involved.
posted by Shyamali Ghosh on January 11, 2016
