As the year 2012 comes to an end, there is already a huge movement towards Cloud with other future shaping trends being Social Media and Big Data. Opportunities in Big Data are immense and there is much that remains to be explored in the areas. Companies in marketing, retail and healthcare are already using Big Data to predict customer behavior for business effectiveness. The buzz has made companies, across industry types, realize that it will not be possible to maintain a competitive edge in the market just based on individual gut feel and that insights from a diverse dataset will be a valuable asset in decision making in the long run.
Big Data is going to impact HR as never before and is changing the way the function is working from purely system based to a more output and employee driven platform. As a result, a large amount of HR data resides in multiple layers and systems with low or no integration. Some distinct data pools that exist in the HR domain today with little overlap and low integration are given in Figure 1.
This data is huge and is constantly increasing. Making sense out of this data is a challenge and an opportunity as well. For HR to truly play a significant role in Business, it is important to move from measuring Efficiency (with a focus on cost) to Effectiveness (of HR to Impact (on Business Performance). This is where Big Data processing and analytics comes to our rescue.
What is Big Data?
It is already being said that Web 3.0 is all about Big Data. Wikipedia defines Big Data as: “… a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.” Big Data processing and analytics have a very important role to play wherever a huge amount of data is being captured, e.g. Internet search, social networks, web logs, call logs, mobile access logs, ecommerce, etc. See Figure 2.
|Figure 2: Estimated rate of data generation the world over. Source:CRISIL Global Research & Analytics (GR&A)|
There are many techniques that draw on disciplines such as statistics and computer science algorithms that can be used to analyze datasets. Some of the techniques are Predictive Modelling, Time Series Analysis, Simulation, Statistics, Regression, Pattern Recognition, Cluster analysis, Crowd- sourcing, and Data mining. How Big Data can be useful in HR and Recruitment?
HR is still at a basic level of understanding as to what Big Data can do for business. A large chunk of Big Data is human capital data and this can be leveraged in a number of ways for Talent Acquisition and Management. For example:
»» Demand (Jobs) and Supply (Candidates) information drilling down to pin-code level categorized by Industry, Functional Area, Years of Experience and other demographics.
»» A consolidated profile of Candidate with data aggregated from his/her resume and multiple social media platforms
»» Manning/Staffing ratios in relation to business forecast numbers.
»» Identifying the right fit for your organization by creating a positive profiling of a candidate. Clearly establishing the link between the positive profile (quality of hire) with the overall productivity
»» Variable pay analysis for establishing productivity and attrition
»» Utilization with respect to Employee Demographics, Leave and Time processes.
Where do we begin?
While Big Data may look overwhelming, it can be utilized and mined in a planned and systematic manner as mentioned in Figure 3. To really create Business Impact, these must be included in your Big Data Roadmap.
The infrastructure required to do the data churning is huge. So, it is recommended to move from an onpremise setup to a scalable, Cloud-based platform that can securely access your company’s data and is able to aggregate the same with other data sources such as social media platforms.
|Step 1||Step 2||Step 3||Step 4||Step 5|
|Measuring transactions such as Recruitment, Onboarding, Payroll, Exit, etc.||Identification of Metrics that are important for your Business||Benchmarking with others in the Industry||Understanding past behaviour and outcomes||Predicting future likelihoods|