Think about it this way: Facebook has "datafied" our friend network. Google has "datafied" our search and information retrieval. Twitter is "datafying" news and real time information. Waze is "datafying" our driving. LinkedIn has datafied our professional connections. GE is "datafying" all its engines, power plants, and machines.
Each of these businesses is harnessing what we now call BigData to store, analyze, and monetize the information around its business. This is why I like the word - it defines the "rethinking" of what we do around the data, not just the product and the process.
For me as a "data geek" this is not really new. Business execs have been trying to analyze and "datafy" sales, customer acquisition, product profitability, and supply chain costs for many years. But what is new is the rapid speed and amazing tools we now have to store, manipulate, and analyze this information.
How do we Datify Human Resources?
Just as marketing became a data-centric function about 25 years ago (the beginnings of market segmentation, customer scoring, customer relationship management), so is HR beginning to go down the same path.
I met with the COO of a high-tech company last week and her background is in marketing. She was looking at their HR organization and the high turnover rate in their company and asking some very basic questions: who are the segments that are leaving? What data do we have on these people and their managers? How can we understand the "model" for retention in our business?
These are questions which come naturally to data geeks, but not naturally to HR. While the marketing function has been applying data science for decades, HR is just beginning. And it's about time.
Consider the opportunity. Businesses spend 50-60% of their total revenues on payroll (sometimes higher, sometimes lower) and this large expense is rarely well analyzed. Do we have the right people in the right jobs and are we paying them the right amount of money? Yes we clearly have budgets and headcount targets, but do we really know how to optimize our employee spending?
We've done some research in this area and a large healthcare provider recently saved almost 4% of their payroll simply by analyzing what we call "payroll leakage." Using some proprietary algorithms (developed by Deloitte), this organization was able to see that a large number of its hourly staff was on hourly duty when they were statistically not needed. This somewhat mundane finding enabled the company to deliver tens of millions of dollars to the bottom line.
Datafying HR Has Many Applications
Our research on Integrated Talent Analytics shows a small percentage of companies (less than 8%) are starting to "datafy" some very interesting things. Let me cite a few examples.
- A large technology and services company looked at its employee turnover and didn't like what they saw. After several months their engineering team uncovered some new keys to employee retention. It turns out that mid-performing employees (those not in the top 10% performing group) are willing to stay even if their compensation is reduced to near 90% of compensation averages. Top performers, on the other hand, will leave if they do not see compensation well above the average. The impact of this finding? Managers can now shift compensation dollars from mid-performers to high-performers and dramatically improve retention without major changes in payroll expense.
- A large financial services company analyzed the profitability of its financial services products and found a set of sales teams that seem to be delivering "above-average" profitability. After looking at a wide variety of HR and product data elements, they found a set of sales people who were more seasoned, better trained, and simply more business-aware of the products they were selling. The result: an enhance hiring and training program that is expected to deliver millions to the bottom line.
- A major customer service provider analyzed 7,240 employees over seven locations around the world and found that "relevant job experience" in the area of customer service had no impact on tenure, performance, or long term employee engagement. They also found that candidates with many prior positions (ie. job hoppers) did not perform any better or worse than employees who had long term employment with their prior employer. The result: a very powerful model now in use to hire and predict high performers in customer service.
Datafication Changes Many Things
Many things in HR are starting to change, and we will be discussing this in the coming months:
- HR data management: How is your HR data managed? Is it credible and up to date? There are lots of new data management tools available to bring data together. Our research shows that companies are still very weak at managing HR information.
- HR analytics tools: Oracle, SuccessFactors, Workday, SumTotal Systems, LinkedIN, ADP, and nearly every other HR software provider is adding data analysis tools to their HR platforms. While tools alone are not the answer, it is no easier than ever to make sense of the data you have. Dozens of small companies now offer data visualization and analysis tools, making it easier than ever to see the data you have.
- HR data providers: A flurry of new companies are now offering people and workforce data like never before. Not only can you download excellent US workforce data from the Bureau of Labor Statistics, but companies like Burning Glass Technologies and eQuest are selling access to data which lets you analyze job postings, workforce demand, and important hiring trends. We at Bersin by Deloitte offer a wide range of benchmarking data to help you optimize your spending and resource allocation.
- HR analytics education: dozens of companies now offer free training (YouTube is filled with courses) and low cost training in statistics, visualization, and the concepts of data analysis. I"m particularly excited by O'Reilly's Strata conferences and all the great data resources they pull together. There are so many books on BigData and analytics it makes my head spin (I've been in this space for 20+ years so it's amazing to me how this cottage industry has gone mainstream).
- New decision-making processes: the more datafication grows, the more HR decisions themselves will be "data-driven." While most CHRO's I talk with are working to get their analytics act together, our research shows that the High-Impact HR organizations (the top 10% organziations in our research) are all well ahead of their peers in analytics and workforce planning. These companies are already making the shift toward "datafying HR."
Learn how to Datify HR: Much More to ComeWe will be launching our new Talent Analytics research at the HR Technology Conference in Las Vegas, where we are hosting an open discussion on BigData in HR. (I will also be presenting a session called "Understanding MOOC's and the Learning Management Market", which I know you'll want to attend.) I am going also to be speaking on this topic at the HR Technology Europe conference in October if you can make it to Amsterdam.
(Note you can get a $500 discount on the Las Vegas HR Technology Conference between now and September 23 if you register with the code BERSIN13).
HR and training managers have been trying to implement HR analytics and measurement systems for many years. Today if we just apply the buzzword of "datafication" to HR, we can see huge benefits in our own organizations.
I'm not always crazy about fads, but this one is meaningful, powerful, and it's here.
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