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Data blending, i.e., the ability to access, integrate, cleanse and enrich data from multiple data sources, is the linchpin of deeper, more impactful insights. Analysts across sales, marketing and operations cite the lack of data blending capabilities to be the primary reason for not using the right data to drive critical business decisions. The impact of not having data blending capabilities in the line of business is lost revenues, missed opportunities and lower profitability.
Source: Alteryx Data Blending Survey
Midsized organizations (defined by Aberdeen Research as organizations that reported between $50 million and $1 billion in revenue in the past year) win by outsmarting, rather than outspending, their larger competitors. They are more vulnerable due to their lack of a financial cushion, making it harder to withstand the impact of bad decisions. In their recent 2015 Business Analytics survey and 2014 Big Data survey, Aberdeen analyzed responses from mid-market organizations to identify the:
- key reasons why companies are investing in data blending tools
- primary capabilities impacting usage and adoption of data blending tools within the mid-market, and
- impact of data blending tools on an organization's use of data
Their latest Smart Brief, "The Impact of Data Blending Tools in the Mid-market," summarizes some of the significant differences that mid-market Leaders have over Followers when it comes to data blending. View their Smart Brief to see what mid-market companies value in their data blending tools, and how the companies with the right data blending tools differ from others in terms of speed of decision making, confidence in the quality of their data and insights, and adoption of data-driven decision making.
Do you agree with the findings? Let us know in the comments section below.
Stay tuned for more on the topic of data blending best practices for mid-market organizations, including a white paper with all of the findings from Aberdeen, plus a checklist that summarizes what midsized companies should look for in a data blending platform.
