This is a continuation of Crowdsourcing.org founder Carl Esposti’s discussion on enterprise cases of crowdsourcing from CrowdConf2011. Part 1 of the discussion covers how the Indian outsourcing paves the way for enterprise crowdsourcing.

Many of you will recognize Crowdsourcing.org’s “Crowdsourcing Industry Landscape” infographic — we published our updated November 2011 release a couple of days ago. This is the third generation of our taxonomy, which we first launched at CrowdConf2010. (More details on our revised industry taxonomy are available here.)

This taxonomy is broad, covering the primary categories where crowdsourcing can be applied from a high, distant perspective. For the last six months, however, we have undertaken detailed research initiatives with a number of leading crowdsourcing providers as well performing our own research where we looked at over 2,500 crowdsourcing use cases. This has resulted in the development of our Enterprise Use Case Framework.

Four Use Type Groups  / 19 Use Case Types / 68 Use Cases

Ideation-based tasks are completed by online workers engaged in the creative process of generating, developing, and communicating new ideas, where an idea is understood as a basic element of thought that can be visual, concrete, or abstract. Ideation is all stages of a thought cycle, from innovation to development to actualization.

Knowledge-based tasks are completed by online workers that possess knowledge based on a familiarity of someone or something, which can include philosophy, facts, descriptions, information, and/or skills acquired through experience or education. It can refer to both the theoretical or practical understanding of a subject. It can be implicit (as with practical skill or expertise) or explicit (as with the theoretical understanding of a subject), and it can be more or less formal or systematic.

Expertise-based tasks are completed by online workers that are widely recognized as a reliable source of technique or skill, and whose faculty for judging or deciding rightly, justly, or wisely is accorded authority and status by their peers or the public in a specific, well-distinguished domain.

Micro-tasks are short duration tasks completed by online workers. Micro-tasks require no specialized knowledge or expertise other than a basic level of comprehension and cognitive judgment.

SIZE AND MATURITY — Large/mature vs. small/growing — Large segments with high volumes (e.g. vertical processes) are more likely to be interested in additional value levers; maturity indicates deeper level of process understanding and ability to disaggregate

PROCESS NATURE — Transactional vs. Judgment-Based — Repetitive processes (e.g. insurance claims processing) are better candidates for crowdsourcing then customized judgment-based ones (e.g. company financials analysis)

PROCESS COMPOSITION — End-to-end vs. disaggregated — Processes that can be naturally disaggregated into tasks (e.g. check processing) are better candidates then predominantly end-to-end processes (e.g. customer support)

VALUE DRIVERS — Efficiency vs. effectiveness — Cost efficiency-driven segments (e.g. transaction cost in Finance & Accounting) are more amenable to crowdsourcing than effectiveness-driven (e.g. spend reduction in Procurement)

SECURITY AND PRIVACY — High vs. moderate — Processes that are subject to regulations or have heightened privacy concerns (e.g. HIPAA regulations in Pharmaceuticals) are much less likely to take advantage of Crowdsourcing, unless anonymity can be absolutely ensured

ROLE OF TECHNOLOGY — Platform-based vs. custom technology — Platform-based processes with high degree of standardization (e.g. ERP-driven Accounts Payables/Receivables) are easier to integrate than processes with custom technology (e.g. employee benefits administration)

OUTSOURCING PENERTRATION — Outsourced vs. in-house — While outsourcing can be looked at as an alternative to crowdsourcing, it indicates openness to consider alternative sourcing options and tolerance to privacy and security concerns

LEVEL OF AUTOMATION — Automated vs. Manual — Processes with high degree of automation, resulting in low use of labor are less likely to benefit from crowdsourcing than highly manual processes