Mid Market Cos. Embrace Big Data Projects

To Discover what drives midmarket adoption of big data projects, Dell Software commissioned Competitive Edge Research Reports to conduct a global surveyi of midmarket executives. Focused exclusively on midmarket organizations, the survey indicates that big data projects have made a significant shift from their enterprise roots, and have become a critical decision-making factor for midmarket companies across the globe. Survey findings also show midmarket organizations today overwhelmingly believe in the potential of big data projects to help them solve tangible business problems, and they are backing up that belief with action.


Survey results demonstrate agressive adoption of Big Data initiatives in the Midmarket


The survey's most significant finding is that 41 percent of respondents have one or more big data projects already in place, with another 55 percent planning to start one the foreseeable future. Further results show that more midmarket firms plan to use big data analysis to grow their businesses, rather than just find ways to cut costs. Additional findings include:


80 percent of survey respondents agree that they need to better analyze their rapidly expanding data collections. Among their top goals: Improve product quality, seize business opportunities and speed decision-making.

89 percent of respondents with a big data initiative in progress report significant improvements in company decision making.

Encouraged by early success, respondents expect big data budgets to rise from between $2 million and $5 million up to an average of $6 million in the next two years as companies invest more in hardware, software and trainingi.

The biggest drivers of big data project success are IT/business collaboration, proper skills, and performance management to gauge the effects of big data initiatives.

The most influential departments in big data projects are IT and sales/marketing.

The most valuable technologies for midmarket companies running big data initiatives are real-time data processing, predictive analytics and data visualization tools.

A host of key drivers are pushing midmarket companies to embrace and invest in big data initiatives. Survey respondents' report that their top three project goals are to provide better quality products and services, take advantage of new business opportunities, and improve the quality and speed of decision-making. Those goals are followed closely by gaining a better understanding of customer needs, having the ability to respond quickly to competitive threats, and improving the effectiveness of their marketing programs.


Early Results Show an Immediate Impact


Although many midmarket companies are just now getting started with big data projects, the early results show those projects have had an immediate and overwhelmingly positive impact on their organization's productivity and success. According to the survey, organizations with big data projects in flight report far greater levels of satisfaction with productivity and decision making than those still in the planning phase. For example:


50 percent of organizations with a big data initiative in flight are satisfied with the quality and speed of their decision making, compared to just 23 percent among those yet to kick off a big data project.

49 percent of organizations with a big data project in progress are satisfied with their ability to improve product quality, compared to just 32 percent of those organizations still in the planning phase.

47 percent of organizations in production with a big data initiative are satisfied with their ability to identify and take advantage of new business opportunities, compared to 24 percent of those organizations whose initial big data project is still in developmenti.

Key Success Factors


A well-known but often-ignored best practice for big data projects among enterprise organizations, collaboration between IT and business units is the most often cited prerequisite of midmarket project success documented in the Dell survey, with 41 percent of respondents indicating that strong cooperation between the two groups is needed in order for an initiative to succeed. Other commonly cited success factors include:


A strong connection between data analytics and performance management in the organization, cited by 37 percent of respondents.

The availability of required skills – such as those possessed by data scientists – within the organization, cited by 33 percent of respondents.

The documentation of complete and accurate business requirements, cited by 32 percent of respondents.



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