Workload configuration and client strategy discovery using crowdsourcing

Abstract

Using enterprise crowdsourcing service we have engaged multiple teams that interact with 300 clients to obtain insights into workload configurations on client infrastructure, identifying over 400 new project/revenue opportunities. The derived insights had a number of purposes: • identify shortcomings of the platforms hosting key business functions • identify most common workloads and application topology • create new project and revenue opportunities with clients Client teams from different geographies participated, and we discuss what factors affected relatively slow response rates, in comparison to our prior deployments Immediate follow up includes a survey of system users to obtain the feedback on the tool, as well as the questionnaire content. As future work we plan to cross verify collected data with existing systems of record, apply predictive analytics on workloads and improve data collection process by augmenting decision theory to identify when (not) to use crowdsourcing. © 2014 IEEE.