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Enterprise Crowdsourcing:  Calculating the Cost Savings
editorial

Enterprise Crowdsourcing: Calculating the Cost Savings

Editor's Note: The following comes to us from Arnold Koh, Lionbridge Enterprise Crowdsourcing Solution Architect. Koh explains how Lionbridge is able to pay its crowdworkers competitive wages, and still help enterprises save money. To find out more about Lionbridge, check out our previous posts here, and visit the company's site here.

Disclosure: Lionbridge is a client of Massolution / Crowdsourcing.org. This is a sponsored guest post.

One unfortunate misconception about enterprise-level crowdsourcing is that the massive cost efficiencies the model enables are attained by simply sending the work overseas to be completed by lower-waged staff. The reality, at least within our pre-qualified 100,000+ member crowd of professionals utilized through Lionbridge’s Enterprise Crowdsourcing Practice (ECS), is vastly different.

Our crowd workers earn aggressive, competitive wages for the tasks and jobs that they complete. With the level of education, skill sets and expertise that our clients demand, it is imperative that we compete aggressively for top global talent and matching client projects to the available talent from within our crowd is a painstaking process. It is also critical that we get it right to keep the client satisfied and to ensure there will be follow on work.

Related:
- The Recipe for Quality Enterprise Crowdsourcing
- Enterprise Crowdsourcing: In-Depth with Lionbridge 

So, how is it that these cost savings are realized by our clients if wages are still so competitive? The answer comes in numerous smaller savings that only the crowdsourcing model allows.

Elimination of Infrastructure

Invite an efficiency expert into a corporate office and the first thing they’ll look to control is the overhead costs. The sheer volume of stuff required to maintain an office where staff has all the tools, space and other infrastructure necessary to do their jobs is mind boggling. Imagine if the desk, computer, parking fees, heating costs – every bit of the overhead associated with employees or an entire project team – was simply eliminated. Crowdsourcing models like ours essentially eliminate these infrastructure costs, while ensuring project managers have access to highly qualified teams of global professionals who are experts in their field or discipline and only an Internet connection away.

Output-Based Pricing

When companies pay only for the work completed by the crowd, they instantly eliminate employee downtime. The standard full-time employee (FTE) model (or role-based practice) carries numerous built-in costs that are often taken for granted. Employers must absorb numerous personnel costs ranging from vacation time to the thumb-twiddling hours that follow IT crashes. The bottom line is this: ECS eliminates non-productive and unbillable minutes, hours and days all while allowing project managers to lock in labor costs based on the particular skill set required for a specific task.

On-Demand Elasticity and Scalability

With virtually instant access to our 100,000 workers, our ECS model enables the project workforce to be scaled to meet changing task demands, and its size/scale can be revised quickly when necessary. When work slows during off-peak times, it is difficult, under the FTE model, to maximize each employee’s revenue potential. Once project tasks are created within our ECS practice’s cloud-based project management platform, the volume of tasks assigned is entirely up to the project manager and the client pays only for tasks or projects that are actually completed. The flexibility that such an elastic workforce provides is a major boon to the bottom line during slow periods.

Accuracy Increases Productivity

One more cost savings measure is actually a byproduct of a quality control mechanism. With each project sourced through our ECS practice, numerous layers of quality validations are established to ensure that our crowd delivers accurate results for a client. These checks and balances have routinely led to increased accuracy rates in data processing projects and those few percentage points on a survey of data quality often result in an immense amount of manpower savings.

The four areas identified above are the most commonly identified areas for increased productivity, greater efficiencies and significantly improved delivery of products and services. What are your experiences? We’d love to hear them.

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