Big Data Blunders: Not All Analytics are Created Equal

You’re hard pressed to go through a day and not see or hear a mention of big data. Let’s start with the definition. According to an Inc. magazine article, “Simply put, big data refers to a collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.” The article also states that “Although estimates vary widely, research conducted by CSC estimates a 4,300 percent increase in annual data generation by 2020.” There certainly isn’t a lack of data, or a question of its utility. The question is – are companies leveraging it properly?

A top big data trend for 2015, according to an article in VentureBeat, is “faking it with big data will no longer cut it.” We couldn’t agree more. Companies have confused the marketplace by purporting to show results and demonstrate ROI with their tools and technologies. Problem is, not all analytics are created equal. Not all technologies can measure the specific ROI of your HR investments—or make the results actionable for front-line leaders.  Our goal is to help you move the business needle so we’ve pulled together some thoughts for you to consider before enlisting an assessment/analytics vendor or conducting analysis in-house.

Real Analytics for HR:

  • Analytics CANNOT be limited to slicing-and-dicing HR data (data visualization tools add little value)
  • Analytics must be true cause-effect and predictive of real business outcomes (not Engagement!)
  • Analytics must be reported and actionable to all front-line leaders (not just for pretty corporate PowerPoint presentations)
  • Actual business impact must be shown

Guiding principles for business-focused metrics:

  • There are no magic metrics that work for everyone
  • Every element on the scorecard must be directly linked to business outcomes
  • HR Efficiency Metrics are fine for Internal HR tracking but not for senior business leaders
  • HR Metrics must be predictive
  • For every metric you should be able to answer yes to these questions:
    • Can I articulate why this really matters to the business?
    • Do I know what a good number should be?
    • Can I articulate the business value of moving this number up or down?
    • Why would senior and front-line leaders
      care about this metric?

We’ll be speaking and exhibiting at the Predictive Analytics World Workforce Conference March 31-April 1. If you’d like to meet with us to discuss more on this topic while at the conference, or to schedule a demo of SMD link, please email us at

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