Big Data Analysis - The 3 Most Important Concepts to Keep in Mind

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“What are the most important concepts HR professionals should always keep in mind as they embrace their utilization of Big Data into their portfolio of data tools?” The answer to that question is …

“What are the most important concepts HR professionals should always keep in mind as they embrace their utilization of Big Data into their portfolio of data tools?” The answer to that question is quite clear. “Don’t let the excitement about Big Data cloud your judgment.” Big or small, the same rules of data analysis still apply. And, being able to demonstrate your data intelligence is just as critical a skill as is knowing when and how to bring data into the decision making process. With this in mind, based on my years of experience, here are the 3 most important concepts to always keep in mind:

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  • 1. When it Comes to Big Data for HR, Don’t Forget - the Basic Concepts Still Apply The 3 most important concepts to keep in mindby David Bernstein on April 15, 2013Readers of my blogs and articles know that myfocus has often been on explaining Big Data. ThisBig Data phenomenon is quickly spreadingthroughout the business world. Those thatunderstand it well will be able to garner newinsights that will give them a competitiveadvantage in their business activities. This is why I’ve focused on demystifying it and talkingabout how HR can start adopting this new technology to drive business results. For this post,though, I want to change focus a bit. Instead, I want to focus on a related and equallyimportant idea about utilizing Big Data – developing and growing your role as a “Data Leader.”I’ve been asking myself, “What are the most important concepts HR professionals shouldalways keep in mind as they embrace their utilization of Big Data into their portfolio of datatools?” The answer to that question is quite clear. “Don’t let the excitement about Big Datacloud your judgment.” Big or small, the same rules of data analysis still apply. And, being ableto demonstrate your data intelligence is just as critical a skill as is knowing when and how tobring data into the decision making process. With this in mind, based on my years ofexperience, here are the 3 most important concepts to always keep in mind:1. Know the difference between “Story-telling” and “Story-selling”As both a producer and consumer of data analysis, it is paramount that HR professionals beable to differentiate between a neutral, unbiased interpretation of data and one that uses thedata to tell a desired story. Darryl Huff’s famous work, “How to Lie with Statistics” is full oftimeless cautions on this topic. He reminds us that despite its mathematical base, statistics isas much an art as it is a science.Today, the HR marketplace is replete with vendors and services all portraying themselves as theanswer to every business problem and need. With the ever increasing messaging on the needfor HR to be “evidence-based” in their decision making, it is now nearly impossible to find avendor or service provider who isn’t trying to use data to base their claim that their solution iswhat is needed. Let me offer a simple rule to keep in mind – “Even if you can’t see anydemonstrable bias in the data, always allow yourself a reasonable sense of skepticism;especially when the source of the data being provided is from someone who has a point toprove or a product to sell.2. Know the difference between “Correlation” and “Causation”Correlation does not imply causation. This is one of the most basic tenets of statistical
  • 2. analysis. The idea is straight-forward – “just because there is a connection between twovariables, does not necessarily mean that one causes the other.” This is very important in theworld of Human Resources. HR has long pursued being able to tie its activities to positivebusiness results. However, that pursuit will be fruitless until HR can understand which variableshave that type of impact and can then subsequently statistically demonstrate the causalconnection between HR activity and profitability.Interestingly enough, though, HR can also capitalize on simply knowing there is a correlationbetween data points. The trick is to know when correlation alone will suffice. Again, simplerules govern when correlation is sufficient. When the intended outcome is either:1) Preventive – i.e. reduce attrition by finding patterns in your voluntary terminationpopulationor2) Increases the likelihood of a positive event – i.e. increasing the completion rate of onlineapplications to your job postingsWhen it is not necessary to know why a relationship exists and you only need to be concernedwith the fact that a relationship does exist, then you can leverage that insight to drive desiredbusiness outcomes.3. Know when your sample size is sufficientThis one is actually embedded in the two previously outlined concepts. However, because of itscritical importance to this discussion, I am calling it out on its own. The right sample size is animportant feature when the goal is to use data to make decisions, evaluate results, or todetermine either correlation or causation. Sample size is critical, both in terms of the size of apopulation or data-set, as well as to how the sample size is determined or created. As noted,marketing collateral’s purpose is to story-sell. The data-savvy consumer of this type ofinformation should always be on the alert for data that is purposely cherry-picked to convincethe buyer of the vendor’s stated value proposition.Not coincidentally, HR and their data analytic teams must abide by this same concept. Whendata will be used to support decision making, to create policy, to make recommendations, or topurchase products, they must present an objective analysis that is based on a statisticallysignificant sample size.I felt compelled to write this article largely because I’m noticing an increase in the amount dataand analytics oriented marketing messages being presented to the HR community. I amconcerned about the HR professional who is not yet accustomed to examining the claims madeby others that are “supported” by their own reported data. It is important that HRprofessionals not blindly accept information at face-value simply because it is presented as factsupported by graphs and charts. With so many “Big Data” and analytic oriented solutions nowcoming to market, HR must know how to take a critical eye in evaluating these claims.
  • 3. This same critical eye is also what HR must bring to their own data analytic work. Objectivestorytelling based on adequate sample sizes, with appropriate conclusions as to correlation orcausation are the core traits of a seasoned data veteran.I remember back to the start of my career in Human Resources. There I was, a Generalist in anexplosive growth company called PeopleSoft. Back then, Dr. Lyle Spencer’s 1995 book onreengineering HR was like the bible to us. Dr. Spencer’s definition of a strategic HR functionwas one that was able to switch its focus from spending 60% of its time on Administration workto instead focusing 60% of its time on planning and the development of HR programs. Today,many HR departments have moved well past that milestone. The stature the HR profession hasachieved is clearly evidenced by the fact that 79% of CEO’s have their senior HR leaderreporting directly to them – primarily to play a key role in defining the direction and overseeingthe performance of the company. HR has graduated from its role as a “data steward” to that ofa business leader. HR now must regularly evaluate data and information as it guides and leadsthe businesses it operates in. And because of Big Data’s statistical analysis underpinnings, it iseven more critical that HR take its data-savviness to entirely new heights.Phil Simon, in his book, “too BIG to IGNORE – the business case for big data” talks about thepopular perception of HR folks tending to almost exclusively rely on gut instincts versus makingdecisions based on data. I’m convinced that as the profession continues to embrace the use ofdata and analytics into its practices, that it will also continue to solidify its role within the C-Suite.David BernsteinDavid Bernstein is the head of eQuests Big Data for HR/Predictive Analytics Division. This divisionstudies the performance and effectiveness of job postings on job boards and social media sites, enablingorganizations to make better-informed decisions about their recruiting and hiring strategy. Bernsteinsfocus is on yielding critical insights for HR departments to drive talent acquisition and workforceplanning strategies. Contact him at david.bernstein@equest.com.