Statistics is the process of analyzing, interpreting, and using data to make well-informed judgments and decisions. This involves employing appropriate HR data (knowledge) to make less biased, more objective decisions and recommendations in the HR environment. In other words, statistics can assist HR professionals in becoming more evidence-based rather than relying solely on gut instinct or intuition. Starting with the problem your organization is trying to solve, such as a high attrition rate, is crucial in any people analytics effort. HR professionals can use statistics to understand better and confirm why this is the case.
Every human resource department needs to be able to analyze HR statistics. Following an examination of many projections, we developed a list of common data pieces that will assist us in developing new strategies for the future year. This will aid in identifying existing industry trends, limitations, opportunities for improvement, training requirements, and employee satisfaction.
So, how does the field of statistics assist HR?
Human resources, like people in general, can be exceedingly unpredictable. Statistics can aid in understanding, capturing, and foreseeing the uncertainty of our world. It can assist in risk mitigation by estimating uncertainty and revealing hidden aspects of day-to-day HR tasks. For example, you can use analytics to anticipate who is most likely to leave the company, assess whether you are fairly rewarding different employees, and uncover hiring biases. You'll miss out on a lot of essential knowledge that can help you make better people's judgments if you don't have it.
Statistics, in some form or another, always come to the rescue!
Step 1: Making Everyday Decisions with Democratized Data
A good data strategy begins with transactional data, which is the substance of everyday company interactions, insight, efficiency, and output, says Tom Starner. Here HR executives must concentrate on giving information to employees, HR personnel, and line managers so that they can, in turn, take action to reach a better degree of productivity and success. It may be at the most basic level, but it's vital. HR and department leaders need access to necessary data to make decisions. It must make data accessible across the company while ensuring security.
In terms of data decentralization:
- Keep it simple; for your fundamental data strategy, make a brief list of essential HR and business needs.
- Ensure that company governance allows all data to be accessed.
- Provide management teams robust dashboard-style tools that enable them to access several data points for strategic choices and core transactional data for team and people management decisions.
Step 2: Leveraging Talent Insights to Build a Stronger, More Engaged Workforce
Once data democratization is in place and basic dashboards are in the hands of HR, business partners, managers, and most importantly, employees, engagement building through HR statistics should take center stage. Retention is the best place to begin. Gauging turnover in a certain business unit or job family—or any other easily isolated cluster—can lead to discovering crucial data indicators for increasing employee engagement.
You can analyze what employees are thinking and feeling using engagement scores, social listening, or any number of other new tools. For example, you may build a retention plan based on an employee's learning history and invest in continued growth. It might be a tuition-assistance program. Any variety of statistics-driven decisions might be made to improve retention and engagement.
Keeping talent engaged is primarily dependent on ensuring that they are learning and gaining new abilities, according to Adamsen—echoing Workday's Yang. You can achieve this by determining relevant information for an employee's function that is useful for them to learn, for example. What kind of abilities do other people in their position earn? What are the most popular training videos on the internet right now? HR statistics can be used in this way to continue to encourage employee learning and skill development, which is a major factor in employee engagement."
Statistics could aid these initial and ongoing career transfers by recording an employee's skills and indicating the next steps, or by tracking most likely shifts from one role to the next based on prior employee movement. People want to ensure that they are always learning, gaining new skills, and receiving feedback. HR must remain on top of everything. They want to know how well the person is doing and whether or not they are receiving adequate feedback on their professional development. Employers may use HR Statistics to measure success across the employee lifecycle, from sourcing and employing increasingly diverse employees to providing internal growth opportunities for employee development. As a result, they may improve talent retention and diversity at the same time.
To increase engagement:
- Provide managers with dashboard-based tools to measure and manage engagement elements including diversity, pay equity, retention risk, succession pipeline reporting, and recruiting metrics like time to hire, pipeline health, and hiring source performance—all of which are engagement-boosting factors.
- Monitor an employee's cycle to find key tipping points that can be recognized using HR Statistics, such as critical determinants of when an employee is disengaged and likely to seek new employment.
- Provide employees with the data they need to discover areas for improvement and encourage their development, resulting in increased levels of engagement.
- Assist employees in better understanding their skills and what alternative internal routes correspond to their skills.
Step 3: Using Statistics and Insights to Infuse and Chart Organizational Strategy
In HR, here is where you get to the most complex and difficult level of data use. While the other two phases are more extensive, this phase focuses on how HR may aid in the development of company strategy using data and contribute to executive-level planning. It's here that HR can use statistics to become strategic, which is a much-discussed but elusive HR ideal. Complex concepts like big data, predictive and prescriptive statistics, and combining internal and third-party statistics all play a role here.
This third phase may entail looking into topics like workforce planning. Establishing how HR can collaborate with finance to combine workforce analytics with financial data to support top-level company objectives such as entering a new market, successfully executing acquisitions and mergers, introducing a new product, or converting to a sustainable business model.
HR moves into predictive statistics at this level. Instead of informing business leaders what happened (descriptive statistics), HR will tell them what will happen. Although predictive and prescriptive modes can be valuable in data analytics planning, most organizations are seeking answers to their problems rather than these specific types of analytics, adds Schlampp. In a related area, the aforementioned blending of operational data with employer data from the HR system is a last tough but in-demand area in this higher level use of data analytics. Employers are increasingly expressing a desire to combine external data with their own, but many are disappointed by the current limitations in their ability to do so. And this may indicate that they are unable to provide the analysis that company leaders require.
Why does HR require a variety of data sources, including operational data? This data is frequently the key to an HR-related insight. Companies evaluate employee performance based on various factors, including calls per shift, defect rates, and client retention. Non-traditional HR data sources, such as a customer relationship management system, a point-of-sale system, or an industry-specific system, provide the statistics you need to measure this. Using this data in conjunction with HR Statistics can help you better understand worker productivity, organizational performance, and other critical issues. When combining data, it's critical to ensure that the appropriate data preparation and security capability are available.
If it comes to producing the most of HR statistics, consider the following:
- To acquire a bird's-eye view of crucial indicators and KPIs at the leadership level, use workforce, and organizational performance scorecards.
- Ascertain a strong and unmistakable link between HR statistics and organizational strategy.
- When presenting HR statistics-driven results to business leaders, make sure clarity is at the top of the list. They don't want to be mystified by jargon; instead, they want to understand how data can help them address problems and build their organization.
Other intriguing facts, the Human Capital Hub states that:
- According to 47 percent of HR executives, the top workforce management problem is employee retention and turnover, followed by recruiting and company culture management.
- Employees cite a lack of career advancement (22%), lack of support with work-life balance (12%), their manager's behaviour (11%), unacceptable remuneration and benefits (9%), and low well-being as the main reasons for leaving their positions (9 percent ).
- In 2020, 97 percent of HR executives expected to increase their investment in recruiting technology, with nearly a quarter (22%) expecting a 30-50 percent rise in cost. (Workplace of the Future)
When it comes to using statistics to make better HR and general company strategy initiatives, there is no turning back. . HR decision-makers want to know how statistics influence the success of their workforces, both in terms of knowledge and skills and self-service, as well as the overall company.
Denzel Moyo is a Business Analytics Consultant at Industrial Psychology Consultants (Pvt) Ltd a management and human resources consulting firm.
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