Impact of employee absenteeism
Unplanned employee absenteeism is undoubtedly a significant cost driver for any business. It is also something that can be very difficult to measure the true cost of. The direct costs — things like wages, administrative workload, and so on — may be relatively simple to measure and forecast. However, the indirect costs — for example reduced employee morale from understaffing, reduced productivity, and the greater burdens on HR departments — can easily be overlooked. Beyond this, if not addressed properly, unplanned absenteeism can even affect the way that key stakeholders perceive your company, having knock-on impacts on your bottom line in a range of negative ways.
For these reasons and more, businesses across all industries are increasingly devoting significant resources to combat their internal issues with unplanned absenteeism. One of the most popular ways to approach this is to analyze HR-sourced employee data to try and gain useful insights into the workforce.
Unfortunately, this type of approach has some common limitations. For example, the statistical relevance of the insights is often insufficient to convince C-Suite members to commit appropriate funding. Additionally, the task of scanning through extensive databases and performing complex statistical analyses can be offputting for HR personnel and may seem too detached from the frontline HR tasks of working directly with staff.
So, how should organizations ensure that HR departments are equipped with the necessary tools to access valuable insights, gain bargaining power with the C-Suite, and become more effective? We believe that the solution lies in advanced people analytics.
What is People Analytics?
The use of data in Marketing
Perhaps the best way to introduce anybody to the world of people analytics is to use the analogy of marketing. Prior to the 21st Century, the field of marketing was regularly stuck in the ‘one-ad-fits-all’ mentality, where advertisements were designed for mass appeal and distributed via the medium with the widest immediate reach. In essence, this methodology focused on forcing as many people as possible directly to the ‘action’ segment of the marketing funnel in the hope that it would boost sales.
In more recent years, with the advent of the internet and ever-advancing computing power, the marketing funnel has undergone a rapid and transformative evolution. This new marketing funnel is vastly more efficient and, importantly, more targeted. By ultra-focusing marketing efforts to carefully identified niches, companies can now almost guarantee high levels of conversions for a lower investment than ever before. Now, customers are neatly guided through the funnel by being offered the right content and the right time, making them far more inclined to play ball. In addition, the ever-present influx of data now enables marketing departments to identify and track KPIs, gain actionable insights, and influence the C-Suite more readily.
The use of data in HR
This marketing revolution has been driven by one thing — data. By recognizing the power of data, marketing teams worldwide have found ways to get more for their money, but HR departments are still largely reluctant to adapt in the same way by putting their data to work. Group-level learning and development, standardized compensation and benefits schemes and generalized absenteeism programs are still the go-to solution for most HR departments. While they are sometimes effective, relying solely on these methods is undeniably an outdated strategy, particularly when one takes into account the vast amounts of revealing data now at these departments’ fingertips.
People analytics is about trying to evoke the relevance of these concepts on a wide scale, and convincing the world of business that data science and its companion technologies are inherently adaptable, and have an important role to play across HR departments.
The four levels of business analytics
The versatility of analytics is well illustrated by Gartner’s Analytic Value Escalator framework, which subdivides business analytics into four levels:
1. DESCRIPTIVE ANALYTICS: answers the question ‘What has happened?’
2. DIAGNOSTICS ANALYTICS: answers the question ‘Why did it happen?’
3. PREDICTIVE ANALYTICS: answers the question ‘What will happen?’
4. PRESCRIPTIVE ANALYTICS: answers the question ‘How can we make it happen?’