Analytics is getting due importance in the HR business for its various capabilities. HR can now make fit business cases and showcase its investments just like other functions in the organizations. However there is ample room to encounter misconceptions when a new technology is fed into the system chief among them the attempt to term metric studies as analytics. The previous article dealt with why we need analytics. This article clears the confusion over metrics and analytics.
Analytics and Business Objectives: Analytics studies the data to identify and present trends and patterns on it. Porting into visual formats enables data to project the trends and patterns more dramatically. Intelligence is obtained with various correlation, permutations, combinations, comparisons etc.
In the words of Josh Bersin, the principal and founder of Bersin By Deloitte: Companies using people analytics “generate high returns for their work - their stock market returns are 30% higher than the S&P 500, they are twice as likely to be delivering high impact recruiting solutions, and their leadership pipelines are 2.5x healthier. These HR teams are 4x more likely to be respected by their business counterparts for their data-driven decision making, giving them true potential to help change the business.”
But this is useful when the analytics is in context to the business objectives and goals. Any HR function be it in Capacity Planning, Succession Planning, Competency Assessment, Workforce Management in Pre and Post Re-organization or Mergers and Acquisitions, Leadership Pool Creation, Attrition Management or the ambiguous Talent Acquisition is besotted with realizing business goals and returning maximum outcomes for every shekel invested.
For this reason analytics must reach out to business goals and be responsible for the outcomes.
Business goals ----> Analytics ----> Business outcomes
Such glove-fit alignments brings in a windfall of benefits to the organizations.
True Analytics enables you to insights into your HR data. But not all these insight inducing data can be construed as analytics. The same applies to some processes professing to be analytics but are actually analysis of a different kind. Here, sample these:
Analysing Gaps in Skills/Performance: When you undertake exercises to find gaps in skills, performance of individuals or departments, you collate these data and then analyse them. You can also perform this on a year-on-year basis to understand the deltas on these parameters. This will result in possible ranking on best skill/performance. But are products of these analyses analytics? No, because we aren’t showing how they impact the business. What are the business goals and what outcomes are sought to be achieved through this exercise?
Notion of business alignment: on the same argument efforts to ensure alignment with respective business (sales, engineering, marketing etc.) as claimed by heads of HR is one of alignment. There isn’t a case of cause and effect relationship to suggest increased productivity/profitability to support alignment. Hence this exercise is of process adherence and the analysed data pertaining to it is not analytics.
Recruitment metrics are not analytics: tracking time to hire, number of hires etc. is construed by some HR folks as analytics. It is metrics and not analytics. Ask yourself this question “Are there insights to relate quality of the talent hired with indent to hire time?” So, the number of hires is a scorecard as also the time to hire. Accumulation of such data/scorecards with no business value (especially outside HR) is not analytics.
Benchmark parameters: companies would want to know their employees feedback to benchmark their organizations against others in the industry. This is important and qualifies as metric. Benchmarking data do not pass off as analytics because the business outcome of such opinions and returns on investment made on improving benchmarks do not seem to have a connection. At the most it is another way of perceiving such data but in absence of business value (business goal-outcome relation) it is not analytics.
Benchmark parameters: companies would want to know their employees feedback to benchmark their organizations against others in the industry. This is important and qualifies as metric. Benchmarking data do not pass off as analytics because the business outcome of such opinions and returns on investment made on improving benchmarks do not seem to have a connection. At the most it is another way of perceiving such data but in absence of business value (business goal-outcome relation) it is not analytics. Drawing Correlation between types of data: this is another area of misconception. Collecting information from various functions within the HR on people and business might throw up strange coincidences between these types of data. However these may not trigger decisions to make right investment from HR perspective. That is because they are not analytics but a motley bunch of data.
HR no doubt is saddled with metrics. And analytics can play a yeoman’s role in meeting HR needs to make it an efficient business and add value to the organization. Speaking Analytics, one company that is steadily changing the landscape of Big data technologies is Spire Technologies. Spire’s technology solutions take care of the entire gamut of Talent management making your HR function effective.