HR Insights, HR Management

How HR Can Implement Big Data — in Six Baby Steps

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While some companies are leaping into Big Data with a vengeance, others are shying away from Big Data altogether.

The term “Big Data” alone scares off the weak-hearted HR executive who already has enough on their plate. I often hear the already up-to-their-ears-in-work HR director acknowledge the importance of data.

However, the common complaint, and more importantly, the derailment of effectuating a Big Data plan, stems from the simple fact that those companies don’t have the resources and/or knowledge to develop and implement a wide-range Big Data plan on their own.

Why going into Big Data makes sense

As a former Senior HR leader at Hitachi and previously in HR Technology at Peoplesoft, I understand the dilemma all too well. Change, no matter how small, can be disruptive, time-consuming, and misunderstood.

With that in mind, I think it makes the most sense to first explain why going BIG into Big Data might not be the most prudent course of action. Let’s first take a look at some of the other “BIGS” (other than the big potential rewards) associated with creating an extensive internal Big Data initiative from scratch.

These include:

• The BIG investment in technology infrastructure;

• The BIG time investment in data collection, data cleansing, and data governance;

• The BIG investment to develop an on-staff team into advanced analytics experts;

• The BIG efforts it takes to source and recruit outside talent;

• The BIG challenge in determining which data should be analyzed and how to collect it;

• The BIG shifts required in organizational processes and work culture to adopt a data-centric enterprise;

• The history at many companies of BIG failures and the general unpreparedness for “the data deluge.”

Considering these challenges, many of you could be waiting a long time to leverage your internal data – much less multi-sourced Big Data. It’s unlikely that any HR organization would be funded strictly due to the intensity of effort (cost, time, resources). And besides, even it were … (see above).

However, that doesn’t mean that HR has to sit on the sidelines and hold off on making evidence-based, predictive decisions using Big Data. There is a way you can start small with Big Data. In fact, it makes sense for many companies to ease its way into Big Data.

6 steps to get into Big Data

Here are six baby step approaches toward that goal:

  1. Don’t invest in a huge Big Data infrastructure. There are many ways to minimize your technology investment.  Start with your own data. The benefits and insights of your own data can be a real eye-opener. Your Applicant Tracking System or HRIS should provide you the basic query tools needed to report out and better understand the meaning in your data.  If your company is already using an advanced reporting tool like SAP’s Business Objects, then you should pursue using that type of tool as well.  It’s imperative, though, that you understand your own data before taking the next step – comparing outside data against your own.
  2. Reduce your risk. You’ve already invested in your own data resources and understand what you have; and more importantly, what you don’t have. Knowing what you “don’t have” will enable you to begin to focus on the data you require to round-out how your company stacks up against your competitors and the market in general. This data can be provided by a wide range of third party vendors depending on what you need.
  3. Learn from role models and mentors.  Even if you understand what data you have, what it means, and what you need, the sheer amount of possible ways the data can be analyzed can be paralyzing. I come across many customers who have everything, or almost everything they need to make incredible and decisive decisions but lack the internal analysts or statisticians required to make sense of all this data. An outside Big Data vendor can provide analysts in a more cost-effective way to sort out this specific, actionable information and tailor results to your exact company specifications – utilizing a combination of your own data with insightful market data the vendor possesses.
  4. Leverage quick results. As I’ve pointed out above, you don’t have to wait months or even years to effectuate a Big Data plan. Many Big Data vendors can get you started in just a few days. I’m a strong believer in out-sourcing what you need to quickly gain a bit of one-upmanship in the market.
  5. Stay focused to start. Going BIG into Big Data can be a shock – like diving headlong into the Bering Straits. Starting small with Big Data is like dipping your toe into the water, allowing you to get comfortable as you begin to immerse yourself. The benefits of this walk-before-you-run approach are invaluable. It allows you to see the value of having a proactive and evidence-based decision-making process in one area, and recognize how you can expand it to other areas of your job. It also helps you gauge how your management and organization responds to the approach.
  6. Partnering. Organizations that are looking to put the infrastructure and staff together to mine and analyze Big Data can gather valuable insights from partnering with a vendor to explore one aspect while building their own capabilities.

“Most companies should act now”

There was a recent article in the Harvard Business Review by Dominic Barton and David Court of the global management consulting firm McKinsey & Company, titled Making Advance Analytics Work for You. They write:

The Era of Big Data is evolving rapidly and our experience suggests most companies should act now. But rather than undertaking massive overhauls of their companies, executives should concentrate on targeted efforts to source data, build models, and transform the organizational culture.  As companies learn the core skills of using big data, building superior capabilities may soon become a decisive competitive asset.”

In other words, you can implement Big Data now. But start small. Then expand. There’s nothing wrong with baby steps. Isn’t that how we all started?

This was originally published on eQuests’ Floating Point blog

David Bernstein is the head of eQuest's Big Data for HR/Predictive Analytics Division. This division studies the performance and effectiveness of job postings on job boards and social media sites, enabling organizations to make better-informed decisions about their recruiting and hiring strategy. Bernstein's focus is on yielding critical insights for HR departments to drive talent acquisition and workforce planning strategies. Contact him at david.bernstein@equest.com.
  • http://twitter.com/Expansa_HR Expansa Ltd

    Absolutely agree. So many companies waste time and money on “big data” which is irrelevant to what they are trying to achieve.

  • nicopretorius

    Without the proper strategy and goal in place for a big data implementation, the result will be as effective as having Access on an employee’s personal computer. First determine what you want, then start the process of how you going to get it.

  • Norm Perreault

    I’d propose another kind of “partnering”: Partnering with a public university to assist with data analysis. My alma mater, the University of Connecticut, set up a non-profit entity that they call “Industrial Psychology Applications Center (IPAC)” specifically with these situations in mind. Companies with loads of interesting employee data but no time to cull through it can engage the services of one of these groups and discover some real interesting connections. Everyone wins: Companies get unique, actionable insights on the cheap, and the university and its students get great, meaty problems to solve. I’ve seen similar programs at Bowling Green State University (called “IPRA”), Southern Illinois (“ARC”), and many other Industrial-Organizational and Applied Psychology programs.