Predictive Analytics for Human Resources: Everything you need to know about Predictive HR Analytics
- What is Predictive Analytics in HR?
- How is Predictive Analytics used in HR?
- What Other Predictive Analytics can be Leveraged to Support HR Deliverables?
- Predictive Analytics Tools for HR
- HR Predictive Analytics can Change your Business Outcomes
- 4 Common Misconceptions About People Analytics
- Predictive Analytics HR Examples
- Five Key Employee Turnover Statistics to Help You Reduce Attrition
- Predictive HR Analytics: Mastering the Metric Employee Decisions
- What are some Tools and Techniques for Predictive HR analytics?
- Predictive HR Analytics: Utilizing The Future Of Work
- Predictive HR Analytics And System Interoperability
- Assessing Predictive Analytics Software for HR: A Buyer Checklist
HR predictive analytics are changing the way organizations do business, and HR professionals are critical players in determining an organization’s growth. Here, we explore how predictive analytics can assist strategic planning to improve processes for organizational success.
Business leaders too are realizing how important predictive people analytics are to the bottom line. Executives know human error and long lag times are impacting their ability to make real-time decisions for their businesses.
Even those who rely on an enterprise or end-to-end system recognize these modules or disparate streams from best-of-breed HR technology applications don’t truly speak to each other and the data is frequently misclassified, duplicated, has different naming structures, or was loaded improperly. The majority, however, are using best-of-breed solutions, each system designed to do what it does best, but few in alignment around reporting or data normalization.
What is Predictive Analytics in HR?
Before we discuss everything, let’s first define exactly what predictive analytics for HR is and how it can be used.
- Predictive analytics for HR is a powerful tool that has made Human Resources professionals crucial players in determining the direction of an organization’s growth
- Predictive HR analytics software can be used to make talent decisions, reduce attrition rates, increase hiring accuracy, and improve employee engagement levels
- A predictive HR analytics platform helps companies identify performance gaps before they become larger problems by identifying areas where employees are struggling or could have more room for improvement. This information can then help identify potential training programs or other interventions that may be needed to address these gaps. It also provides data on which employees are likely to excel at their jobs and which employees may be better suited for different positions
- Predictive HR Analytics software is also a useful tool for businesses because it can help companies reduce their attrition rates by identifying the conditions that lead to high turnover. By finding patterns in data related to employee turnover, organizations can determine how to retain their best employees, as well as the steps that they can take to prevent turnover
- Predictive analytics software for HR allows HR departments to forecast attrition rates for employees across their organizations, monitor the effectiveness of compensation and benefits programs, determine who has strong potential for advancement within an organization, etc.
How is Predictive Analytics used in HR?
HR plays a crucial role in shaping a business’ brand and contributing to its growth, from hiring the right candidate to ensuring high engagement and a positive employee experience until exit.
HR can use predictive analytics to enhance the way employees are assessed before recruitment as well as during their tenure in an organization. The results of these efforts are actionable points that positively impact the organization’s bottom line.
Human Resources is a key contributor to business success. But predictive analytics can help HR have an even bigger impact on the bottom line. That’s because predictive analytics helps assess employees before recruitment, during tenure, and after exit.
By taking historical data, internal and external events, demographics, compensation, mergers and acquisitions, even compliance, engagement, and training data, it can predict retention spikes, employer brand efficacy, performance, operational productivity, talent acquisition trends, hiring spikes, even where high-performing employees were sourced from. It can even tell you which of your job applicants are more likely to stay with the company for years or quit in six months!
This helps business leaders prepare ahead of time, predicting events so you can mitigate risk or leverage success and/or market events. Predictive analytics software for HR improves HR metrics by providing actionable points that positively impact the organization’s bottom line.
Predictive Analytics HR Examples
The field of predictive analytics is part of predictive modeling. The concept is to use statistical algorithms and data analysis to predict future outcomes and behaviors, such as purchase patterns or which customers are likely to respond positively to an offer; HR predictive analytics applies this concept to human resources. Predictive analytics in general has been gaining momentum due to its predictive power, but HR analytics are also attractive to companies because it can help minimize risk and prevent costly bad hires.
HR predictive analytics enhances the way employees are assessed before recruitment by pinpointing which applicants are more likely to stay for years or quit in six months. When predictive analytics software has been applied to hiring, the typical result time is reduced by 50%.
Turnover costs the U.S economy over $30 billion every year; predictive analytics transforms employees into assets through predictive retention models, identifying what influences an individual to leave or stay with a company. A predictive model can determine when someone is predisposed to resign depending on various variables that include their role in the organization, years of experience, and their manager.
Also, predictive analytics in HR is helpful during tenure by identifying which employees are most likely to be engaged or even to be promoted. Monitoring predictive data throughout an employee’s tenure can enable managers to offer additional training or support, which can positively impact motivation and job satisfaction.
Predictive analytics in HR is a predictive model that takes data from an individual’s tenure at the organization as well as their performance on job tests to gauge how successful they might be in advancing within the company.
What Other Predictive Analytics can be Leveraged to Support HR Deliverables?
- Discover if you’re meeting diversity goals
- Identify recruiting bottlenecks
- Track headcount versus plan
- Decide when raises will be most effective
- Map demographics to performance
- Shift your employer brand based on drive time
- Use employee survey data and exit interview feedback to create your succession plans and train managers
- Understand how mergers and acquisitions will impact your productivity
- Locate the best people area for your newest location
- See which hiring managers are tanking interviews or creating bottlenecks
- Headcount: Actual vs Planned, Headcount, Hires, and Terms, Headcount Growth, Workforce Planning, Performance Headcount, Tenure Headcount, Employee Maps, Employee Demographics
- Talent Acquisition: Actual Hires vs Forecast, Talent Acquisition Overview, Hiring Statistics, Global Cost per Hire, Time to Fill Position, Sources of all Hires, Open Requisition Overview, Open Positions by Department, Current Candidate Activity, Skills Heatmap, ENGAGE Talent (embed other software apps into PHR)
- Retention: Rolling Annualized Attrition, Termination, Turnover Rates by All, Annualized by All, Global Retention, Global Reason for Attrition, Global 90-day Predictive Reason for Attrition, Employee Risk List, Employee Risk Heatmap, Attrition with Events, AI Attrition Insights, Attrition Indicators, Retention Insights, Promotability, Time in Role, Tenure, Detail Attrition, Survey Scores by Org, Survey Scores by Department, Engagement, and Satisfaction by Department, Predictive Pathways
- Performance: Organization Summaries, Employee Summary, Performance (9-Box), Executive Summary -inc. Key Actions to Take and Retention Risks
- Productivity: Employee Goals, Employee Goals Aligned, Data Integrity Engine, Industry and Location-Specific Workforce Planning, People Impact on Revenue
Predictive Analytics Tools for HR
Many professionals look for an AI platform that takes disparate systems, applications and data sources and combines and normalizes the data, removes duplicates and mistakes, and then creates role-based lenses based on internal and external people, financial and operational data to deliver reports and visualizations.
Predictive HR software is different from predictive analytics software. Predictive HR software is used to make predictive decisions about one’s own workforce, such as predictive hiring and predictive attrition for better forecasting. Predictive Analytics Software on the other hand is used to help optimize your organization by showing you what needs to be improved so you can grow and continue leading in the future.
Would you like an example of predictive HR software? Imagine if your organization did predictive hiring and predictive attrition so you could forecast who might leave the company and who might show up in your jobs section, we can even do predictive succession planning! We’ll show how predictive analytics helps by analyzing your data and telling you where things need improvement.
It’s not all about predictive HR software, though. There is also predictive analytics for HR as a whole. Predictive analytics uses data to make predictions about the future and help us better understand our workforce for future success by discovering what we don’t know yet or where we can improve.
Predictive Analytics is a science that is finding future outcomes based on previous data. Basically, data analytics help you to predict the future prospects of each or both parties.
Predictive analysis in human resources is rapidly evolving. Now HR departments can predict when an employee might leave, when they’re ready to retire, when things just aren’t working out, and much more. In this way, HR professionals can make the right decisions for their company’s employees, save on turnover costs, find qualified candidates for open positions, and improve their hiring success rate.
Basically, predictive analytics help you to predict the future prospects of each or both parties. individual’s potential to pay back in time and assign a particular limit. It will provide predictive analysis by applying predictive analysis in investigating vast amounts of data that will help predict the future and help you move forward.
As the hype of big data and analytics enhances, making analytics a booming market, many organizations are utilizing data to facilitate digital transformation throughout every aspect of their organization.
Businesses across all industries are experiencing a growing amount of data at their disposal as they grow in size. As a result, organizations strive to find a solution that alleviates the pain of obtaining and reporting workforce data from multiple, disparate HR and non-HR systems.
HR predictive analytics can help you to predict who will leave your company and when they’ll be ready for retirement. The predictive HR software, PREDICTIVEHR™, helps HR professionals make the right decisions for their company’s employees by analyzing data and telling them where things need improvement.
To improve efficiencies across the entire organization, companies need good, quality data to improve the accuracy of their analytics.
So, how can this be solved? By employing advanced analytics to convert big data into knowledge and action. So, how are organizations using data analytics to inform and improve strategic and operational decisions?
Below are a few statistics showing how applying analytics can unearth new insights, control organizational costs, increase profitability, and manage talent.
Big Data and HR Analytics Statistics You Need to Know
- In HR.com’s recent Big Data and Analytics 2019 survey, most HR professionals give low grades to their organization in terms of its overall ability to gather, evaluate, visualize, and share high-quality talent analytics. Only 36% of HR professionals say their firms are either good (23%) or very good (13%) in these areas.
- Few HR professionals use talent-oriented reports or dashboards to a great extent.
- Just 26% use descriptive talent analytics to a high or very high extent.
- Even fewer (15%) use HR predictive analysis to the same extent.
- Fewer yet (14%) use prescriptive talent analytics.
- Talent analytics are most important in five key functional areas:
- Compensation (50%)
- Recruitment and selection (43%)
- Organizational development (42%)
- Retention (36%)
- Succession planning (33%)
- In HR.com’s recent Big Data and Analytics 2019 survey, only 22% of HR professionals say they often or always integrate non-HR data with HR data, though one-third (33%) sometimes integrate these types of data.
- Three practices are cited most widely as being useful for improving talent analytics:
- Consistent and regular collection of data
- Turning data into insights
- Sharing data or knowledge with others
- Only 9% of individuals strongly agree that research designs help get the most value out of talent analytics, though another 27% moderately agree.
- The three most widely used HR business intelligence or analytics solutions are:
- Spreadsheet software (50%)
- Analytics tools built into HRIS/HCMS (38%)
- Analytics tools built into other HR systems such as an ATS (30%)
- Most HR professionals consider these resources as the best solutions to present talent analytics:
- Graphical presentations (i.e., PowerPoint)
- Spreadsheets (45%)
- Interactive visualizations (34%)
- In HR.com’s recent Big Data and Analytics 2019 survey, only 23% of HR departments agree or strongly agree their organization has implemented a big data platform that is delivering actionable insights.
- More than two-thirds of enterprises using big data initiatives have seen a decrease in operational expenses. (Leftronic, 2019)
- About 40% of businesses say they need to manage unstructured data frequently (Forbes, 2019)
- Businesses using big data saw a 10% reduction in overall costs. (Entrepreneur, 2019)
- 97.2% of organizations are investing in big data and AI. (Business Wire, 2018)
- By 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy. (Gartner, 2018)
Without big data and analytics, achieving organizational efficiency and leading change will be difficult. Without a data-driven approach, businesses will find it difficult to realize organizational efficiency and induce change.
Analytics can help executives develop a new mindset that encourages a new set of behaviors as well as explains how data has an impact on various decision-making styles and how people can use predictive analytics in HR today.
HR Predictive Analytics can Change your Business Outcomes
Employee retention tells a lot about a company. A high retention rate shows employees are engaged, motivated, and enjoy their jobs. When employees give good reviews on websites like Glassdoor, it shows candidates your open roles are worth fighting for. With high retention rates, the company also benefits from higher productivity, better quality work, and lower turnover. So, what would you say if we told you predictive analytics could help you increase your retention rate?
At the Risk of Human Error in HR Analysis
It is common for businesses to conduct a company-wide satisfaction survey to determine how engaged employees are. However, the results of these surveys are heavily influenced by participants’ honesty. There’s no doubt that management is telling employees what they want to hear when 48% of employees believe that such studies don’t accurately reflect the company. This data set could be considered compromised.
Take control of your company’s retention rate by removing employee emotions and false information. Instead, leverage the data you already have on your employees. Take note of demographics. Also, consider company factors such as benefits, pay & promotions, paid time off, and sick days. By looking at factual data, you can eliminate employees’ attitudes towards their jobs and any inaccurate information portrayed in surveys. The data should speak for itself without emotions getting in the way.
Using the information you’ve collected, the analyst will identify patterns in the data. For instance, he or she may identify a correlation between turnover and retention. For example, do employees who live within five miles of the office stay with the company longer than those who live further away? Are employees who have received a hefty holiday bonus more likely to stay with the company than those who have received a smaller annual bonus? When properly analyzed, the correlations between demographics will give you valuable insights.
How PREDICTIVEHR Leverages Your Pre-existing Demographic Data
In contrast to the option above, your company can utilize people analytics too, like PREDICTIVEHR. By integrating your disparate Human Resources technologies with our analytics software, you’ll skip the busy work of collecting, normalizing, and cleaning data. Our easy-to-use collaborative software will pull this information straight from the original sources and provide you with correlations in both your turnover and retention. Our powerhouse software will become your single source of truth.
Using Analytics to Increase Employee Engagement and Employee Retention
The next step is the same whether you use a human analyst or a predictive AI. Give your management team the tools and support it needs to understand the insights provided by the data before starting to develop a plan of action. Describe how the information was developed and what it means to their department or sector.
Then, gather for a strategic planning meeting where each person will outline the low-hanging fruit as well as the essential projects that are a must for their sector. Use the data-driven insights to develop an action plan.
Employees with dependents on their health insurance might take more paid time off than those without dependents. Think about providing opportunities for flexible work, personal time, or work from home for employees to make up hours missed during appointments, child sporting events, or when a daycare provider can’t make it to work. Consider allocating money into the budget to retain knowledgeable, well-qualified employees who stay three years after receiving an end of year bonus.
Only 20% of employees think their managers will act upon survey results. Prove them wrong by actively making changes. Communicate where you got the data to make these decisions. Whether you’re using AI or have an outsourced team to help you make strategic decisions, your team should know you’re not making changes just to throw a wrench in everyone’s day. This transparency will not only let them know actions are being taken but also that the company values employee retention.
4 Common Misconceptions About People Analytics
The importance of establishing a people analytics program is well-known. People analytics allows HR professionals to simplify their decisions by rationalizing complex data into actionable insights that support workforce initiatives. However, despite the various benefits of implementing a data-driven approach, many businesses haven’t fully utilized successful analytics in their people strategy. Why?
Common misconceptions are somewhat to blame. Not only are organizations losing the significant cost and time-saving benefits people analytics can provide them, but they’re willingly staying behind the competitors to source, attract, hire, engage and retain the right talent.
Truthfully, people analytics misconceptions have held organizations back from establishing a data-driven approach. Let’s dig in:
Predictive Analytics HR Examples
If organizations are passionate about one thing, it’s their people. Yet, as an influx of people continue to join the workforce, it can be hard to keep others from changing or leaving their job. According to a study, 65% of employees think they can find a better position elsewhere. So, how can organizations get ahead and minimize their employee turnover problem? People analytics is the answer.
With voluntary resignations at an all-time high, adhering to employee retention has been the objective for many organizations. To actively uncover insight into how to alleviate employee turnover, organizations need a more in-depth analysis of the real causes of turnover affecting different parts of their organization.
Businesses worldwide use people analytics to help them assess critical factors affecting employee turnover. The integration of people analytics into any organization offers significant insights and benefits that allow businesses to make more informed and impactful workforce decisions. So, how can people analytics help improve your bottom line?
Five Key Employee Turnover Statistics to Help You Reduce Attrition
We all know turnover is a problem, but how big is it?
Did you know:
- More than 3.5 million Americans quit their jobs every month?
- The median employee tenure among workers in the United States is 4.2 years.
- According to the U.S. Bureau of Statistics, the average turnover rate in the U.S. is about 12% to 15% annually.
- A report from the Center for American Progress found turnover can cost organizations anywhere from 16% to 213% of the lost employee’s salary.
- More than 50% of all organizations globally have difficulty retaining some of their most valued employee groups.
- On average, a higher retention rate can maximize a company’s profits up to four times.
- Employees that don’t feel recognized when they do great work are almost 2x as likely to be job hunting.
- Between 60 to 70% of all employee turnover is voluntary.
- Employee turnover costs anywhere from 16% to 213% of annual salary depending on the position.
- Companies rated highly on employee training saw 53% lower attrition.
What are the common drivers of employee turnover in the U.S.?
- Personal/Family (57%)
- Promotion Opportunity (35%)
- Career Change (27%)
- Base Salary (24%)
- Job Satisfaction (24%)
Predictive HR Analytics: Mastering the Metric Employee Decisions
Right now, retention is everyone’s issue. To stay ahead of the game, organizations need to establish proactive retention tactics and apply them throughout the entire company. How? By utilizing an analytical approach, such as people analytics, to identify flight risk factors and leverage the power of data to drive action.
Identify the Problem. Determine the leading causes of high turnover to assess if there’s significant damage already done. Calculate:
- Resignation rate: Identify which segments are resigning. Is it your top performers, senior leadership, or managers?
- Business metrics: People analytics provides a bigger picture of how employee turnover affects your business, helping you to make proactive action faster.
Uncover the root causes of turnover. Now that you know there’s a turnover problem, people analytics can dig deeper to help you find why your employees are leaving. Calculate:
- Key drivers: Perform a thorough analysis to determine which factors increase and decrease turnover reformat retention strategies with insights, rather than intuition.
- Uncover correlations: Determine how employee turnover affects categories such as compensation, promotions, pay increases, performance, and training opportunities. With insights at hand, managers can support their decisions around enhancing developmental opportunities, benefits, and promotions, to manage costs, and retain the right people.
Recognize which groups are experiencing turnover. Remember, not all turnover is bad. With people analytics, HR teams and professionals can assess which groups experience turnover, whether that be your low-performers or high-performers, and evaluate the impact employee resignation has on the business. Calculate:
- Evaluate workforce attributes. Analyze who’s at risk of leaving from crucial characteristics such as location, role, age, diversity, performance, and more.
- Risk of exit. People analytics allows organizations to predict employees at risk of leaving before they turn in their resignation letter. PREDICTIVEHR supplies managers with an at-a-glance view of analytics and reporting to identify issues before they arise with powerful, visual, and predictive tools.
Design an impactful employee retention program. After you’ve recognized issues that are causing employee turnover, you can direct your focus on creating an employee retention program to retain key individuals in your organization.
- Internal mobility. Assess and review employees’ skills and attributes to identify which internal candidates you want to hire for specific roles within your organization before recruiting candidates. HR managers can also look externally to see what other positions are being filled and hire candidates according to the demands of the labor market.
- Provide more promotions. Are employees leaving due to the lack of advancement opportunities? By assessing the percentage of people promoted from the organization they worked at, during the start of their reviewal period, will allow organizations to gauge which employees deserve a promotion.
- Performance on new hires. New hire performance can give you insight into how effectively new talent is adapting and performing in the workplace and if your onboarding program needs improvement.
- Pinpoint recruitment trends. Data on past and present recruitment strategies and workforce planning can help HR teams improve L&D programs to ensure staff members have the necessary skills to perform or take over other roles within.
Reducing employee turnover can’t be solved when businesses are still operating from multiple, disparate systems or still utilizing spreadsheets to manage their workforce. Not only does this create a scattered, unorganized process, but it makes it difficult to assess what’s going on in your workforce. So, what’s the right solution to help you? PREDICTIVEHR is a game-changer.
At PREDICTIVEHR, we provide companies with workforce analytics so they can make the right business decisions to alleviate employee turnover. With ongoing support and Human Resources expertise from our staff, we help HR professionals understand their workforce, predict talent trends, reduce turnover, and make evidence-based predictions.
What are some Tools and Techniques for Predictive HR analytics?
There are many tools and techniques for Predictive HR analytics. These include standardizing data, aggregating data, improving data hygiene, and normalizing data. Let’s explore these tools and techniques in action.
The Age of Analytics: Standardizing Data for Improved Quality
Today, many companies are at a tipping point. In this ever-evolving age of big data, organizations hold an abundance of data at their fingertips that wasn’t available to them before. Yet, with all this available data at hand, internal and external, it seems as though the quantity of data can eclipse the quality of data and the insights HR Leaders and organizational executives are able to glean from it.
Data is still relatively messy and inaccurate. It takes analysts weeks to gather the data, compile it and clean the data before they can even start to extract meaning and insights, all while they jockey between multiple spreadsheets. And, once they’ve finally completed their Herculean task, it’s time to get started on the next month’s report.
Data then becomes a lagging indicator.
Because they have to wait for all the data to be gathered and spend time creating analytical reports, the executives who depend on those insights are often two or more weeks behind the business reality.
Executives know human error and long lag times impact their ability to make real-time decisions for their businesses. Even those who rely on an enterprise or end-to-end system recognize these modules, or disparate streams from best-of-breed HR technology applications, don’t truly speak to each other. As a result, individuals responsible for cleansing the data frequently misclassify and duplicate data, categorize it under different naming structures, or load data incorrectly. For example:
- Wrong departments – Stating that an employee works in the sales department when they work in the finance department.
- Employee salaries converted from one currency to another -Incorrectly converting an employee’s salary from US dollars to Euros.
- Job reclassifications – Treating independent contractors as employees.
- Organizational restructures – Forgetting to account for minor changes in senior roles and reporting during a regional growth initiative or merger.
If you’re using an all-in-one solution, you’ll still only be able to report on data housed within that system. Layering in any external system data tends to be a very time-consuming manual process.
The majority, however, are using best-of-breed solutions, each system designed to do what it does best, but few in alignment around reporting or data normalization.
If you have the right tools to clean and provide a granular view of high-quality data, organizations will gain actionable insights into their workforce to improve their operational effectiveness, reduce attrition, and identify new business opportunities. But when data is misclassified, stored in spreadsheets, or stemming from disparate systems both internally and externally, business initiatives cannot be completed, or worse be delayed to the point of facilitating poor business decisions. According to a study, 98% of organizations believe they have inaccurate data.
Unfortunately, many organizations today are prone to adapting poor data management practices to obtain the insights they need to solve their business issues and support their decision-making. Without a centralized and standardized approach to data management, constant inconsistencies throughout data will continue to occur, resulting in reactive decisions, rather than proactive ones. In addition, executives spend more capital and operational resources to store data, instead of using it to analyze on how to improve day-to-day operations.
So, what is the solution?
Simply, the course of action starts with improving the organization and insight into workforce data. Only then can you predict outcomes.
As a transformative shift occurs throughout the market, organizations must move away from the traditional approaches of dealing with data to a proactive approach that breaks down data silos, cleanses and normalizes data, and considers business intelligence first, rather than an afterthought.
Your workforce data should provide the insight to make the right business decisions in near real-time.
Aggregating Organizational Data
Today, ineffective data aggregation is a significant component limiting query quality. With various amounts of organizational data sets, internal and external, data can exist in multiple HR systems or spreadsheets within your organization at the same time. Most of the time, these systems aren’t connected, which will negatively impact the way you use data and the overall quality of your data.
Implementing a competent people analytics solution can be the answer to your query quality problems. The right people analytics software provides executives a 360-view of data and adds value to the data organizations already possess. But, you want to ensure the right solution can support the aggregation of any data type from any data source, whether from your sales, finance, operations, or external market and industry metrics.
With a platform to aggregate and cross-reference your workforce data, you can solve for nearly any business problem:
- Track headcount versus plan and tie it financial outcomes
- Identify attrition before it happens
- Identify recruiting bottlenecks
- Decide when raises will be most effective
- Use employee survey data and exit interview feedback to increase employee engagement and train managers
- Drive internal mobility and retention efforts
Every executive claims talent is their differentiator, but how many truly know the numbers behind workforce productivity, employee skill sets, talent acquisition, and what really drives retention?
Improving Data Hygiene
In the age of information, it’s crucial to have proper data cleansing methods to ensure your decisions stem from fact-based statistics rather than intuition-based outcomes. Historical data must be viewed as an asset to your business. But how?
The answer can be simple if you can provide the time and tools to understand how data is developed, stored, managed, governed, accessed, analyzed, and reported upon. For leaders, this consists of knowing what data you have on hand, identifying where it’s stored, and planning how you are going to record, monitor, and measure the quality of data present. According to HR.com’s Big Data and Talent Analytics 2019 report, about 50% of respondents identified Data Collection or Data Clean-Up was “Difficult” or “Fairly Difficult.”
By utilizing a people analytics solution, you can alleviate the manual effort of going through data. The right people analytics platform not only cleanses your data, but it highlights errors and gaps throughout your data records to help you find meaningful insights fast. More importantly, we analyze data to tell the story of your organization.
For every company, department, team, and individual leader, the “need to know” numbers are not cookie-cutter, but unique. With insights based on company, demographic and industry data that is accurate, clean, de-duped, and consistent across systems, executive teams can plan for things ahead of time. Some executives know exactly where their people or workforce issues lie, but for many, both the problem and the solution are in the data. Here are some common issues that can be solved faster with clean, organized data sets.
Why do we have an attrition problem?
Where do our people impact revenue and sales the most?
What qualities make up high-performers?
What is the long-term impact of our employer brand?
Once your executive team has addressed certain common workforce issues, you can start pulling the clean data you already have and gain more reliable insight into business needs and pain points that may be unique to your organization. Most importantly, many thorny people issues aren’t found until the data is cross-referenced internally, and compared to historical or demographic data.
According to HR.com’s Big Data and Analytics survey, businesses find talent analytics most important in five key functional areas:
- Compensation (50%)
- Recruitment and selection (43%)
- Organizational development (42%)
- Retention (36%)
- Succession and planning (33%)
Cataloging your data according to your objectives establishes criteria for defining how your organization will use data and the goal of its usage. Ensuring data is accurate and up-to-date can help you maintain maximum value from your data analysis.
You can’t solve any of the above if you have dirty data that’s only accessible to some of your executives, some of the time.
If you want to use your data effectively, it must undergo data normalization. Data normalization allows organizations to get rid of anomalies and redundancies that make data hard to report on or provide truthful insights across all systems.
Some of those anomalies stem from deleting data, inserting additional information, or updating existing information. For instance, you may have classified an employee as part-time when they are full-time or have multiple data sets on one individual but have stated different roles for them throughout your data set. With data normalization, it can correct potential errors from your data set.
In addition, data normalization resolves any conflicting workforce data within your data sets. As a result, data normalization addresses this issue and solves it before organizing your data structures.
Once completed, data is in a consistent format for further processing and analysis. Finally, data normalization consolidates business data into an organized structure. With data normalization, information within a database can then be used to create visualizations or analyze, whether that be is done through a team of experts examining your organization’s data or one person surveying the data themselves. Without data normalization, any organization can collect all the data it wants, but most of it will go unused, take up space, and not benefit the organization in any meaningful way.
Now that redundancies and errors are absent, HR teams will find it easier to change and update data within your workforce systems and glean insights accurately.
Every role has different responsibilities and uses for the data that may impact the high-visibility decisions they must make. As such, they need to see different sides of the same data to better understand how to move forward.
While obtaining quality insights for various corporate roles can seem daunting, it doesn’t have to be hard. Investing in data as a strategic asset and improving organizational performance is an option for companies of all sizes. In order to improve your business’ bottom line, ensuring you have a people analytics strategy and solution enables you to develop intuitive insights based on factual statistics in order to mitigate risks and plan for things ahead of time.
PREDICTIVEHR aggregates, cleanses, and normalizes data across multiple systems into actionable insights and transforms them into real-time, dynamic visuals HR leaders can receive immediately. With the power and quality of clean data, organizations can unearth attributes such as employee performance, attrition, recruitment, engagement, and more, while having the support you need to improve workforce outcomes.
Data can be used as a strategic asset and to improve organizational performance by companies of all sizes. Take control of your company by leveraging the data you have. With emotions removed from the equation, factual data can be analyzed to see trends. Use the delivered insights to improve engagement, retention, and, in turn, business.
Predictive HR Analytics: Utilizing The Future Of Work
Workers no longer want to work in a physical office where everyone gathers to work. There is a push to work remotely for companies across the country. The future of work is going to rely heavily on the advancement of technology.
PREDICTIVEHR is the future of work that brings all of your data, metrics, and recruiting solutions into one place. You can discover your diversity goals, track headcount, shift your employer brand, and so much more.
Predictive HR Analytics And System Interoperability
System interoperability allows unrestricted sharing of data between disparate systems. This is the basic ability of different computerized products or systems to connect and exchange information with each other.
PREDICTIVEHR allows systems to seamlessly connect and share information with one another, allowing your team to work in harmony. We can manage the implementation, allowing you to focus on your team.
Assessing Predictive Analytics Software for HR: A Buyer Checklist
Every executive claims talent is their differentiator, but how many truly know the numbers behind workforce, productivity, acquisition and retention? That’s where HR predictive analytics comes into play. In order to find the right predictive people analytics software for your business, you have to map out what features you need. Use this list to narrow down, or expand your definition of crucial HR Metrics.
At the very least, your new HRM analytics system should be able to integrate any employee or people systems wherein you have data housed today. Generating reports in formats all execs can digest and understand is another baseline function necessary to get the most out of your HR analytics platform.
- Integrates all your people and finance systems
- Point and click reporting functionality
- At-a-glance lenses show trends and insights
- Export to PDF, PPT among other formats for non-users
- Product-wide filters include regional, role-based, and organizational filtering
Once you’ve established your non-negotiables, you can move on to the next rung of software assessment, the nice to have features. While not all of these are necessary in order to make your data work for you, if you’re planning to make the investment in predictive people analytics software, it’s wise to get your arms around things that will make your life easier when considering every day use.
Nice to Have Features:
- Every data point can be drilled down into granular data with one click
- Share and download visualizations and reports easily right from the dashboard
- Maintain data integrity with single sign-on that allows for a data trail to the original system when needed
- Change access according to user role ensuring everyone has access to just the data they need
- Benchmarking data included
Once you find a platform that fits your needs (and your wants) you may want to spend a little time dreaming about what would actually move the needle significantly for your organization. Would it be useful to have real-time data visualizations? Would having built-in insights and action items free up time that could be spent more strategically?
- Use included forecasting ability for workforce and succession planning
- Near real-time updates from every connected system
- Predictive functionality offers solutions and action items
- All product-wide filters are customizable to your company
Okay! Now you have a nice list of what you need in your predictive analytics software. The next step is figuring out what data you have and what can really give you insight. PREDICTIVEHR’s analytics platform offers filtering in these areas:
- Managers (anyone with direct reports)
- Business unit
- Direct reports
- Span of control (where your managers stop recruiting and cannot go there)
- Manager Tenure Record
- Capability to onboard
- Talent Acquisition
- Hiring manager tenure
- Pay equity use case
- Historical data
- Raises and compensation data
- Performance review
- Performance ratings
- Distance and drive time to the office
- Exit interviews
- Employee surveys
- Historic episodes
- Mergers and acquisitions
- Impact of employer brand
- Years of experience
- Assessment profile