There are numerous hazards along the path to successfully using and embedding People Analytics in an organization. The following represent some of the more common or dangerous traps, along with various authors’ perspectives on why they should be avoided:
Measuring the easy stuff rather than what is critical
HR teams often focus on tactical operational metrics that improve the efficiency of their own function rather than staying focused on the business imperatives and getting more strategic with their approach.
Thinking that Benchmarking is Analytics
Benchmarking is merely a comparator tool to drive comparisons across sim- ilar phenomena to understand where one stands versus competition. It does
not generate by itself any actionable insights that would impact individual or organizational performance.
Assuming that one solution fits all situations and contexts
Drawing conclusions on the back of generalizations without researching the current situation or context is a common pitfall. A simple example is employee engagement: the drivers could be dramatically different even though the companies concerned may be in the same sector or location.
Getting caught in the ROI conundrum
The ROI approach is a myopic one, is constraining and does not do justice to the complete possibilities that People Analytics and decision science can uncover. People Analytics is not about here and now business benefits; it is about anticipating the future on the back of decision support tools and predictive insights, the monetary value of which cannot be computed accurately upfront, but which has the potential to transform business models and drive strategic shifts in thinking.
Striving for perfection rather than getting started first
There could be occasions when you may not have all the relevant data to run the analysis which often is used as an excuse not to get started. The other pitfall is to strive for that perfect statistical model or correlation that would prove or disprove a particular hypothesis. This approach does not help the business; it is critical to get started and work with data that is available; also deploy the models which bring out the key insights that can be actioned upon rather than the perfect correlation.
Claiming People Analytics for HR and HR only
Data science and People Analytics is a cross-functional domain and requires people with multiple backgrounds and competencies to collaborate and work together; it cannot be deployed in a silo, compartmentalized approach.
Other Common Mistakes
• Holding on to a metric even when it has ceased to be relevant
• Banking on only a few metrics to evaluate performance which exposes you to
• riskInsisting on perfection and total accuracy of data before even starting an analysis
• Restricting oneself to simple measures to predict success, such as test scores or qualifications
• Deploying analytics only for mass hiring at lower levels rather than niche hiring at senior levels where the cost of mistakes could even lead to the company shutting down
• Focusing on HR efficiency metrics only instead of HR and talent management on business performance.
Some other barriers could be:
Cultural—Workforce analytics will be implemented by individuals in organi- zations. As a result, it could happen that personal biases and feelings, which are natural aspects of the human condition, will have its effect here too. These factors may impact the pace of the data juggernaut, but will be powerless to contain it.
There are still many leaders who base their decisions on gut, intuition and wisdom of experience. However, evidence-based insights from rigorous data mining can quickly expose gaps and loopholes in such decisions, thus potentially undermin- ing those who solely relied on them. Does this therefore make leaders insecure?
This fear is, however, completely unfounded. Evidence-based insight using ana- lytics should be viewed as an enabler, not a one or the other. The responsibility of making decisions will continue to rest on the manager: that is certainly not going away. The only change that has come in is that the data ecosystem with its tools and methods are available to managers to enhance the probability of them taking the right and optimal decisions for the business and acting proactively on the back of hard evidence and insights.
Ethical—Big data brings with it critical issues of ethics, data privacy and data security, the various aspects of which are still in the process of being understood by organizations and society as a whole. Companies now have the tools to peek into and collect all kinds of personal information related to their employees as well as prospective hires and candidates but can they legally do so? To what extent should an organization go in collecting personal data of employees or candidates and who decides the acceptable limits or data thresholds? Further, how will companies respond to the conclusions of their own analytics evidence? Will it lead them to, for instance, passing on or avoiding hiring those candidates that as per the data analysed are more likely to churn relatively early?
To overcome these pitfalls and obstacles, organizations need to focus on the following:
Enhance critical analytics related competencies within HR teams; ensure high- quality and standardized data, thereby getting it analytics ready; run those projects that are key to solving business problems; be rigorous in analysis; strike a balance between accuracy and pattern development. Go for small wins, the big ones will follow shortly. Go with the cross-functional approach around data collection and integration and analysis. Engage with your people and provide them the comfort that analytics deployment is meant to support decision-making and enhance their capabilities and not seek to make them redundant. Understand the legal and ethical complexities of employee monitoring. organizations will need to be open about their sources of data; why a particular set of data is being collected and for what purpose? They need to explain how all this data collection and analysis will benefit the employee and the organization in times to come.
People Analytics brings together people and talent, roles, processes, compe- tencies and goals to build an integrated view of the organization. It is this view understood and analysed holistically that enables fact and data-based decision- making, thereby contributing to enhanced business performance on a sustainable basis (Exhibits 4.3 and 4.4).
Copyright: Acumetric Global Solutions Pvt Ltd – all rights reserved Exhibit 4.3 People Analytics framework
Exhibit 4.4 Deployment road-map