Pooja Patil
Pooja Patil

The term "big data" materialized in 2005, when technology expert, Roger Magoulas, encountered challenges processing a vast dataset using traditional business intelligence solutions. As a result, companies have since relied on specialized tools and data analysts to analyze data, leading to improved customer relations, sales, and operational efficiency.

The emergence of big data has presented the most significant opportunity for marketing and sales since the widespread adoption of the Internet two decades ago. The explosion of data has provided insights into various topics, including customer behavior, weather patterns, and emerging market demographics. It is clear that companies that can leverage data to achieve above-market growth excel in three critical areas:

  • Utilizing data analytics to discover profitable business prospects and facilitate informed decision-making, thereby augmenting marketing return on investment (MROI).
  • Transforming the acquired knowledge into meticulously crafted products and offers that satisfy customers.
  • Efficiently bringing these products and incentives to the market.

The goldmine of data available to marketing and sales leaders represents a critical juncture.

Companies integrating big data and analytics into their operations experience higher productivity and profitability, surpassing their peers by 5 to 6 percent.

This advantage is too valuable for any company to ignore.

Considering the current situation where a significant number of employees are quitting their jobs, it is crucial to leverage the potential of data in human resource decisions. The principles of employee value proposition (EVP) management are outdated and in need of revision. Many organizations still rely on short-term tactics to address long-term systemic challenges associated with the future of work. It's time to reassess and adapt to the changing landscape.

The upcoming changes in the future of work call for a departure from relying solely on gut instincts and conventional practices that have been employed for years. Companies must adopt a more analytical approach to managing their human resources to stay ahead of the competition. With increasing globalization and industry demands, data-driven HR decision-making has become vital to organizational success. Through predictive analytics, companies can obtain valuable insights into workforce dynamics, enabling them to make informed decisions that boost business performance. Join our session below to learn about data-driven HR, how to draw actionable insights from data, and ten critical steps to build a data-driven HR strategy.

What is data-driven HR? 

Data-driven HR is a methodology that utilizes data and analytics to aid in decision-making processes within the human resources domain. This approach enables HR practitioners to make better, impartial, and tactical decisions that significantly impact different facets of the company and address challenges related to talent management. The first step in this process is to gather pertinent information by conducting surveys, assessments, evaluating metrics, and utilizing predictive analytics around some areas, such as:

  • Performance
  • Learning and development
  • Turnover
  • Engagement
  • Workforce demographics

Once you have enough data to evaluate, identifying patterns and trends based on this data serves as the basis for strategic decision-making to drive business success. In addition, this approach enables organizations to create solutions for foreseen obstacles proactively.

Also Read: Top Four Trends in Performance Management in 2023

Drawing actionable insights from the available data

Employers have an untapped repository of employee data that largely remains unexplored. Moreover, organizations find it challenging to extract actionable insights from this data. Here are a few examples where data analysis can uncover both strengths and weaknesses within the workforce, enabling HR teams to make decisive actions that benefit their employees and the business.

  • Attracting and retaining talent

    If the data exhibits that your organization is experiencing high employee turnover rates or struggling to recruit top talent, a possible solution could be to develop customized total rewards statements. This approach enables HR teams to showcase the concrete benefits that the company provides, which helps candidates and current staff have a better understanding of their overall compensation package value.

  • Benefits utilization

    If the data indicates that your employees are not utilizing the benefits offered by your company, further investigation may be necessary to determine whether the issue is due to poor communication or a genuine lack of interest in certain benefits. To address this, your HR department may consider reallocating resources and funds to better meet employees' needs and preferences or revising communication tactics to encourage greater engagement with the benefits program.

  • Debt load and savings rates

    If the data shows that your staff members have student loan debts exceeding the national average or a particular group of employees is facing difficulties creating emergency funds, it may be beneficial to consider providing student loan aid or arranging emergency savings accounts for your employees.

  • Retirement readiness

    If employees postpone their retirement, it could result in a substantial expense of up to $50,000 per employee per year for businesses.

    If the data analysis shows that your employees are not readily accepting retirement options, you can provide personalized retirement education or early retirement programs with added incentives.

  • Diversity, equity, and inclusion

    If there are different financial prospects for various employee groups in your organization, it is advisable to closely observe how the offered benefits are being utilized to ensure that they meet the diverse needs of your employees. Additionally, keeping track of hiring and promotion policies would be beneficial in ensuring they are equitable. Employers can examine the conduct and requirements of their employees based on factors such as age, gender, race, ethnicity, disability, or other demographics to identify potential discrepancies and opportunities for improvement that may not have been previously recognized.

How do you build a data-driven HR? 10 key steps to build a data-driven HR strategy

  • Define a business problem

    Gathering data without a defined objective can lead to unfavorable consequences. For instance, you may find yourself inundated with figures that you cannot utilize effectively. Therefore, it is advisable first to identify a particular challenge or aim to focus on. This strategy guarantees that your people analytics endeavors will generate meaningful outcomes.

    In addition, instead of commencing with an HR-related matter, such as decreasing employee turnover, consider enhancing overall business earnings or quarterly revenue. Establish a larger business objective and determine the necessary measures to accomplish it.

  • Create a basic hypothesis before examining the data

    To ensure accurate and valuable insights from data analysis, it is important to begin by creating a hypothesis based on a specific problem or goal. Rushing into data analysis without a clear hypothesis can lead to misleading or incomplete conclusions. Hypotheses can be developed through various methods such as surveys, round tables, or forms. For example, a hypothesis such as "improving career opportunities and transparency in career advancement reduces employee turnover" can be tested through data analysis. This approach of incorporating human aspects into people analytics through hypothesis testing helps to validate assumptions and generate meaningful insights.

  • Collect data

    To start with, assess your current data sources and determine if you have gathered feedback from various channels, such as pulse surveys, 360-degree feedback, or exit interviews, to gain comprehensive insights. If you have overlooked any important feedback sources, it's crucial to include them to ensure that you obtain a complete picture. Furthermore, it's essential to collect diverse data types to eliminate potential biases and increase the accuracy of your analysis.

  •  Analyze data

    Look for evidence in your data that supports or disproves your hypothesis. When reviewing your data sources, it is important to search for patterns and connections between different variables. For example, you might explore cause-and-effect relationships, such as the impact of changes in hiring practices on employee retention rates. You can consider different analytical techniques, including:

    • Text analytics: This involves analyzing large amounts of text data, such as emails, surveys, job applications, or performance reviews, to extract relevant insights.

    • Predictive analytics: By leveraging artificial intelligence and historical data, you can estimate the likelihood of future events or trends.

    • Voice or speech analytics: Analyzing audio recordings can help you identify the main topics discussed or the tone and words used by speakers.

    • Video analytics: Using CCTV footage, you can gather useful information, such as whether your construction crew follows safety regulations by wearing appropriate gear.

    • Image analytics: This technique uses pattern recognition to extract information from images or graphics.

    • Sentiment analytics: Combining text analytics and other methods, you can better understand your employees' overall attitudes and experiences.

  • Count on historical data

    To establish a baseline for measuring progress and identifying trends, organizations must rely on historical data. HR leaders can make evidence-based decisions and identify actionable insights by utilizing various pre-existing HR metrics such as compensation history, turnover rates, and employee engagement. By analyzing this data, companies can identify patterns and trends, allowing them to make informed strategic decisions.

  • Reveal insights

    Having access to abundant data doesn't always mean having valuable insights. Therefore, it's important to transform collected data into meaningful insights that provide solutions to strategic questions and contribute to achieving strategic objectives. To do so, it's important to present the data in a way that appeals to different learning styles. This can be done by creating a narrative that incorporates visual aids such as charts, pictures, or videos to support the statistical evidence presented. Additionally, consolidating information into a centralized source can help organizations detect trends and identify areas for improvement.

  • Make an HR bid to enhance the business situation

    Start by analyzing the data to gain insights into a specific business problem or opportunity, such as identifying a key talent pool that can drive sales growth. Next, use these insights to develop a comprehensive HR strategy that aligns with the organization’s overall goals and objectives. It is essential to engage stakeholders in the decision-making process to secure their support and ensure the strategy's success. By using data-driven decision-making, HR can demonstrate the value of its contribution to the organization and drive positive business outcomes.

  • Understand cultural nuances

    Cultural differences can affect how job candidates engage with potential employers and the criteria they use to evaluate desirable metrics. Therefore, it is essential to consider cultural nuances to avoid misunderstandings and misinterpretations of data sets. HR professionals should be mindful of these differences and strive to create an inclusive and diverse recruitment process that considers cultural factors.

  • Always tell a story

    To create a persuasive argument based on data, it is crucial to construct a coherent narrative that provides context for the numbers. Develop concise presentations that illustrate the proposed solution as a result of the insights gained from internal research. Use storytelling techniques, such as using anecdotes or case studies, to make the data more relatable and engaging to stakeholders. This approach can help build support for the proposed solution and increase the likelihood of its successful implementation.

  • Make a data-driven HR mission and vision statement.

    The HR strategy's summary and guiding principles are encapsulated in the mission and vision statements, which act as a guiding light for all future policies and decisions. Therefore, it is crucial to make a data-driven HR mission and vision statement that incorporates insights gained from data analysis. This approach will ensure that HR initiatives are aligned with the overall business objectives and that data-driven decision-making is at the core of HR practices.

Wrapping up! 

To effectively support employees' needs, HR should adopt a proactive approach, and leveraging data is crucial to achieving this goal. Organizations should prioritize investing in data and analytics to equip their HR leaders with the necessary insights to drive measurable business impact. With real-time insights, HR teams can create specific strategies that enhance employee well-being and drive business performance.

Exela HR Solutions, a leading firm specializing in HR outsourcing, provides a data-driven approach to tackling HR challenges. Our team of experts can assist you in navigating the complexities of HR by delivering reliable and assertive solutions. Contact Exela HR Solutions now for all your HR needs.

DISCLAIMER: The information on this site is for general information purposes only and is not intended to serve as legal advice. Laws governing the subject matter may change quickly, and Exela cannot guarantee that all the information on this site is current or correct. Should you have specific legal questions about any of the information on this site, you should consult with a licensed attorney in your area.

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