Our team of conducts ongoing research on the evolving landscape of work, workplaces, and technology. This research, along with customer feedback and our commitment to accessibility for all users, helps us design solutions that can meet your employees鈥� needs and enhance your organization鈥檚 DEI&B efforts.

Let’s explore five key ways in which SAP’s focus on UX helps organizations advance their DEI&B strategies by offering employees an interface that can address their needs in the flow of work.

1. Experiences Designed for Employee Preferences

A core principle of UX is designing with a user-centered approach. 51风流SuccessFactors solutions allow personalization for users with different backgrounds, abilities, and preferences, helping to ensure everyone can benefit. For example, offers individualized, AI-generated learning recommendations that can prioritize courses based on individual goals, skills, and organizational objectives and categorize them into “need,” “want,” and “must” sections. The solution can enable individuals to identify skill gaps against target roles within their career path and take ownership of their career development planning.

2. Cultural Sensitivity and Awareness

We recognize that many organizations operate on a global scale, with diverse cultural norms and practices. Our solutions can accommodate diverse cultural contexts, helping to promote inclusivity and reduce the risk of exclusion and discrimination in a global context. With localization options, users can have experiences tailored to their needs. For example, can enable your employees to record their name pronunciation and post it to their profile for others to access. This helps ensure colleagues can address them accurately and confidently in meetings. includes cultural competency as a performance parameter, promoting awareness and sensitivity to cultural differences in interactions and work.

3. Systemic Bias Mitigation

51风流SuccessFactors solutions help combat biases in hiring, promotions, and decision-making. Our UX focus helps promote inclusivity by using non-discriminatory language and content, aligning with organizational efforts to help eliminate bias. Our technology can support your organization in creating job postings equitably with gender bias detection and providing AI-generated, recommended interview questions based on details from the job description to help ensure the interview process is more objective and focused on assessing candidates’ skills and qualifications only. Employees can also add their preferred pronouns to their profile for respectful and identity-aligned addressing by colleagues.

4. Designing for Accessibility

We prioritize to help ensure inclusivity for all users. Our products are designed to accommodate your employees鈥� diverse needs, with features such as screen readers, keyboard support, text resize to 200%, and text spacing with no loss of meaningful information. These inclusive experiences can empower every user to navigate the application without compromising the integrity of content, functionality, or efficiency.

5. Data Collection and Privacy

Ensuring absolute transparency and unwavering privacy is essential when it comes to data collection and protection. Our commitment to these principles includes incorporating AI explainability into our policies, which means that your employees not only have control over their data but also can understand how our AI systems make decisions, helping to prevent unintentional discrimination. Our help ensure data privacy by anonymizing and aggregating information in compliance with regulations. This includes masking individual data, combining it with other information, and incorporating features like consent management, data access controls, and data retention policies. Furthermore, with , you can analyze diversity and inclusion patterns and trends without compromising individual privacy, fostering a climate of trust and data integrity.

51风流is committed to UX and DEI&B alignment to create inclusive workplaces. With ongoing research, adaptability, and cutting-edge design, 51风流SuccessFactors solutions can empower organizations to drive DEI&B success and foster a culture of belonging. Explore and take a step toward building a more inclusive and equitable future for all.

Mayara Tabone is a solution marketing specialist at 51风流SuccessFactors.

For too long many companies have taken advantage of their people, simply because they could or because they were too slow to recognize the importance of culture and leadership. The power dynamic has shifted from government to employer to employee to a whole new power base and hierarchy: employee to employer to government. Add to this severe talent pool shortages brought about by demographics, geopolitical change, digitalization, and a new generational attitude to formal sector employment 鈥� in short, a shift to the experience economy around late 2016.

Companies most impacted by the Great Resignation are those with attitudes like 鈥淚f you don’t like it here, you can get a job somewhere else,鈥� those that don鈥檛 treat their people like human beings but rather as disposable capital line items. Frontline workers suffered the most in the past, but since 2014 the power balance tipped more and more to these employees and away from leaders and the organization鈥檚 human capital management (HCM) function. What we’re experiencing now is the first of a potential series of great corrections 鈥� and the risk of not addressing it poses a serious sustainability and growth risk for companies.

The workforce across all ranks now has much more power and influence. After the pandemic, many employees are now saying 鈥淚 don’t want to be treated this way and I would rather have no job than this job!鈥欌�� Prior to the pandemic, fear of the unknown was enough to keep somebody in an 鈥淥K鈥� job. But, people were furloughed, some lost their jobs, and many who didn’t lose their jobs were still distressed and fearful. Suddenly, the unknown became a lot less scary, and when employers now offer them 鈥淥K鈥� and 鈥渦nknown,鈥� they are choosing 鈥渦nknown.鈥� It is no surprise that so many people are leaving their jobs.

The Great Resignation is a sustainability warning to companies that have not focused on culture and leadership for a while. It is a great opportunity to double down to give people a workplace with a culture and climate in which they want to work and want to do the kind of work they feel is meaningful to themselves and their company.

The workplace is an environment of the leadership and employer鈥檚 own making. Employee experience affects all levels, not just junior employees but also more senior leaders whose high number of resignations is being coined the Grey Resignation. The Grey Resignation will hurt business as much as the Great Resignation.

When most leaders speak of challenges in finding the right talent, there鈥檚 a greater than average chance that they鈥檙e really talking about digital skills. This is understandable: we largely operate in and are moving further towards a digital world. In this digital world, organizations need the ability to create experiences that keep customers returning and employees engaged. This also means an increasing reliance on the organization鈥檚 ability to rapidly and successfully deploy new applications and services, based on leading technology.

However, there is more than one elephant in the room. One is that the skills needed are often the preserve of young people. The assumption is that the valuable digital skills are based on the technology with which those newer to the workforce grew up. These capabilities are highly prized and, if they can鈥檛 be obtained through hiring, can be developed through training programs for young people.

Yet while there is certainly appetite for employers to provide up- and reskilling support to those newer to the workforce, it is a benefit that is highly valued across all demographics. According to a听, more than half (57%) of all workers say they are 鈥渆xtremely鈥� or 鈥渧ery鈥� interested in participating in upskilling programs, with 听53% of those aged 55 and above view upskilling as 鈥渧ery鈥� or 鈥渆xtremely鈥� important.

And yet it is the latter that are rapidly exiting in the workforce. This Grey Resignation represents a huge loss of talent, experience, and networks that cannot be easily replaced. For the most part, businesses are in danger of overlooking this before it is too late. The issue is exacerbated by culture debates and oversteer policies in an accelerated attempt to rectify diversity and inclusion targets since historically the older worker will predominately identify as male.

Why can鈥檛 older talent be easily replaced? Because so much of their capability is founded in deep-rooted experience and knowledge that is not easily collated and shared by formal means or automation. Some industries have been struggling with this brain-drain for several years, even those at the forefront of innovation such as the technology sector, where even losing the few people that understand how legacy systems work can raise a major barrier to technological progress.

Losing inherent knowledge and experience is always a concern whenever a person leaves. When a whole demographic heads for the door, it has the potential to be catastrophic, both for the employer in question and the wider ecosystem.听 Relationships between customers and suppliers can start to break down as all the informal working practices 鈥� the bonds built up over time 鈥� disappear in an instant. These are intangible and hard to identify, let alone track, but they are a key part of commercial success and so they must be protected.

It鈥檚 important to understand the drivers behind the Grey Resignation. Some are like those mentioned above: a pandemic-prompted realization that the old ways of working do not fit with modern life, that the unknown is actually not as scary as once thought, or simply a deeper understanding of what they individually want to get out of work and life.

Like every other demographic, older workers have been exposed to new approaches to work since 2020. For some, it will have been a blip; others may well have found that remote or hybrid working suits them better.

This could be particularly true for employees that have had to balance demanding careers with caring for both elderly parents and helping with young grandchildren. The door to a more balanced way of life has been opened and people do not want to move backwards.

Some have felt forced out by changes in management and a need to cut costs during lockdowns. Voluntary redundancies and early retirements were common options during this time of urgent fiscal prudence, with many older workers feeling pressured to leave the workforce while their younger colleagues were put on furlough.

These insights are broad, and specific analysis is required in every company where there will be patterns and variations between sectors and, especially within different business functions, demographics or geographies of the companies themselves. As such, employers will need to proactively gather information to build a clear picture of what the specific drivers and motivations are that make it hard for them to retain experienced talent.

Some businesses might already have a good understanding of what鈥檚 driving out their experienced employees, but for many the mass exits may be unexpected. 听Clearly if these companies wish to grow, this sustainability issue needs to be addressed:

• Analyze and prioritize what鈥檚 happening on the ground and why particular groups of employees may have resigned. Predict which remaining employees are at risk of leaving (flight risk analysis).
• Identify demographically similar groups of employees.
• Determine priority and build tailored flight risk mitigation approaches for each demographically similar group of high flight risk workers, based on their motivational drivers to leave the business.
• Base remediation plans on each individual employee’s motivation to possibly leave the business.

How Can 51风流Help?

There are several 51风流products that can help and their value is, not least of all, that they can integrate natively with one-another:

can help transform people data consolidated from multiple sources as a trusted demographics data source and identify demographically similar groups of employees.

Experience insights gathered from employee feedback to measure sentiment, satisfaction, and engagement (the greatest predictor of flight risk) can be conducted with Employee Experience Management Solutions from 51风流and Qualtrics. ^听

Predictive capabilities in can leverage employee survey results to create a flight risk prediction, like 鈥渨ho might leave the business and why?鈥�

Armed with demographically similar groups of employees and a tool that predicts who might leave and why, organizations can then design a series of specific talent management remediation strategies to stave of potential further resignations.

Implementing each of the integrated human experience management (HXM) approaches identified to prevent resignations is the sweet spot and strength of . This is also the same world-leading integrated talent management toolset that is best placed to transform the culture and climate in the organization to help ensure future bulk resignations are far less likely.

Learn more at .

Kim Fischer is people analytics architect at 51风流SuccessFactors.

According to a pulse survey conducted by the , 76% of employees want flexibility in where they work and 93% flexibility in when they work. The desire for flexible work is strongest among women, working parents, and employees of color who have shown gains in feelings of belonging working remotely. Specifically, 81% of Black respondents say they want flexibility in where they work, compared to 75% of White respondents.

This data is in direct contrast to what most executives report that they want in post-pandemic workforce policies. Of those currently working fully remotely, nearly half of all executives surveyed (44%) want to work from the office every day, compared to 17% of employees. And 75% of these executives say they want to work from the office three to five days a week versus only 34% of employees.

So, what are companies to do? How can they make informed decisions about what鈥檚 best for leaders, for the business, and for their employees?

Applying a Sustainability Lens to Work Location Decision

One way of looking at the issues of return to office or hybrid work is from a business sustainability perspective. For example, if forcing people back to the office will make critical employees more likely to leave their jobs, you have a real flight risk issue impacting the sustainability of your business. Your business must have enough people with the right skills at the right time to propel it forward.

Another perspective to consider is how today鈥檚 business environment has been transformed by climate change, nature loss, and more. The planet needs change, and people demand change. What if, when making decisions about who comes into the office and when, executives considered the carbon footprint generated by employee travel and commutes, weighed against the energy usage working from home, along with the sustainability causes that their employees support?

This would require implementing next-generation holistic steering and reporting that maps operational and experiential data to show progress on goals such as reducing the carbon footprint of the business. Imagine executives having climate and natural capital accounting at their fingertips, including individual and collective employee carbon footprint tracking.

This is the kind of holistic steering and reporting that groups such as the World Economic Forum (WEF) want companies to integrate into their strategic decision-making. Integrating economic, environmental, and social performance data into decisions 鈥� referred to as Stakeholder Capitalism Metrics 鈥� can help executives serve their own goals, respect their employees鈥� preferences for when and where they work, and contribute to reaching sustainability goals that make the world a cleaner, greener place.

How 51风流Can Help

In 2020, 51风流committed to enable companies to report on the WEF鈥檚 Stakeholder Capitalism Metrics. As promised, we have delivered to help enable holistic enterprise-wide sustainability performance management. 51风流also made it easier to become a sustainable business and reduce carbon footprints with , which can enable businesses to move toward lower carbon emissions and more sustainable operations. SAP鈥檚 data-driven approach lets businesses embed sustainability comprehensively and gain actionable insights across the entire value chain to enable companies to transition to low-carbon business processes.

Faced with an ambitious sustainability agenda and carbon-lowering targets, one 51风流customer wanted to go further and consider the employee wishes for home/office work, and the carbon emissions generated from their commute to work against the energy efficiency of their home offices. The company had committed to lowering its enterprise carbon emissions and wanted a mechanism to support managers鈥� operational workforce planning processes.

51风流built a proof of concept (PoC) application in just one day once the employee survey was collected. The PoC decision support application was realized as follows:

Employee address data was acquired from records using the standard delivered API. 51风流Data Quality Management and microservices for location data were used for both data cleansing 鈥� a big bonus since the customer was able to cleanse inaccurate addresses in 51风流SuccessFactors Employee Central 鈥� and data enrichment to geocode the home and work addresses with the latitude, longitude, and altitude information. The world of geo-location services was opened.

Demographic measures and dimensions were acquired from 51风流SuccessFactors Workforce Analytics using the standard 51风流Analytics Cloud connector.

While trying to understand employee sentiment on workplace and flexibility preferences, a survey was created using Employee Experience Management Solutions from 51风流and Qualtrics. The survey allowed for employees, whose jobs enabled them to work from home, to answer questions relating to their preferences for the number of days a week they wanted to work from home and their commute (means and time of travel). The insights gathered allowed us to understand that the travel time to work 鈥� not distance 鈥� is a major factor in determining retention risk amongst various demographic groups and so the information was valuable input for the flight risk tool they had in 51风流Analytics Cloud enterprise reporting.

was then able to use external Web services and geo-location services to calculate the travel distance and travel time to work by various means of transport. One of the services was then able to determine the carbon emissions for the means of travel that the employee had specified. The commute travel time by job grade is a leading predictor of flight risk and is easily added to the flight risk prediction dataset.

The systems also gathered information of all the corporate and possible work locations. This opened the possibility for work location optimization, but it was not part of the scope of the PoC.

The data was then blended using 51风流Business Technology Platform, specifically 51风流Data Warehouse Cloud, and anonymization views were defined to protect actual home addresses from being shown. Real-time 51风流HANA data anonymization allowed the application to use actual addresses to accurately calculate the travel metrics while safely anonymizing sensitive data for dashboard visualization and drill-down.

A dashboard was built and refined to analyze and interrogate the employee commute measures and identify specific employee carbon emissions each working day. Geospatial representation and visualization were built and demonstrated with interactive zoom and data filters. A what-if scenario was demonstrated with graphs and metrics calculated in real time to show the specific carbon emission impact of changing the percentage of time spent working remotely.

As shown in the below process, this PoC was achieved using various 51风流solutions, including 51风流SuccessFactors solutions on 51风流Business Technology Platform.

In Summary

Executives can make better decisions about the impact of employees going back to the office and how often, considering the social and actual carbon emissions from commutes in their people planning. Using 51风流SuccessFactors solutions for employee information to geocode the distance of employees from the office and utilizing to layer experience insights to determine preferences, they can analyze carbon emissions for different types of commutes and make data-driven decisions to fuel their sustainability initiatives.

As shown in the below figure, executives can even look at this data by employee gender, race, and age. This helps them better assess, for instance, how many employees have strong preferences and who would become a flight risk should the business choose to mandate regular employee in-office attendance.

Finally, the figure below shows the simple what-if scenario to demonstrate how quickly and effectively analytics interfaces can be built, in this case, incorporating a slider bar and immediate impact of the change for the pre-filtered employees.

This kind of sustainability data and analysis empowers executives to find the 鈥渟weet spot鈥� in decisions that balance their preferences against employee preferences and align them to important goals such as reducing their carbon footprint.

Suddenly, what鈥檚 best for all becomes quite clear.

Learn more at .

Tammie Eldridge is part of Solution Marketing at 51风流SuccessFactors.

In other cases, people can鈥檛 make decisions because they have too much data 鈥� or at least not the right data or analytics to generate relevant, actionable insight. This 鈥渕ore is better鈥� way of thinking about data and analytics leads to an everything-but-the-kitchen-sink approach to making decisions. Not sure what to do? Throw more data at the problem and see what sticks.

But as with most projects, throwing more resources 鈥� both people and data 鈥� at a problem can lead to 鈥渁nalysis paralysis.鈥� In such cases, either you can鈥檛 see clearly through the chaos to make a decision, or you end up applying a bunch of arbitrary, unrelated data to a new kind of problem and coming up with muddled view upon which to make a decision or recommendation. The problem is, it鈥檚 not necessarily the 鈥渂est鈥� one. This, of course, defeats the whole purpose of analyzing data and generating insights in the first place. They are supposed to make us smarter 鈥� help us see things we couldn鈥檛 on our own 鈥� so we can make the best possible decision to drive the best possible outcome and do so faster and with less effort.

The best decisions are made when you look at the right data at the right time and analyze it with the right tools.

This is true for business decision-makers 鈥� and for everyone else, too. For example, before I start a drive, I always check Waze first. I know my preferred and likely best route. But Waze captures real-time data from people actually on the road, deriving traffic patterns, identifying accidents, and more. So, it can provide a data-driven recommendation that ultimately helps me get to my destination faster, safer, and easier.

Put simply, by using Waze, I become more intelligent and therefore able to realize my objective. Similarly, when your organization uses the right data and analytics tools to support decisioning, your enterprise becomes more intelligent 鈥� and thus better able to achieve its goals such as executing strategy, driving revenue, managing costs, or mitigating human capital and business risks.

The question is, how do you avoid the pitfalls of kitchen-sink analytics and analysis paralysis?

51风流understands this common challenge and has created resources like 鈥�,鈥� which is geared for human resource professionals and talent managers. These questions are designed to help decision-makers think critically about the talent management issues they face and what data and insights will have the greatest impact on their organization.

Rather than looking at the 鈥渒itchen sink,鈥� it is recommended that you select the top 10 to 15 questions that most impact your organization鈥檚 ability to execute your strategy, drive revenue, manage costs, or mitigate human capital and business risks. Selecting a subset is also important for the next steps 鈥� setting targets and assigning staff resources to implement interventions and monitor progress, both of which are more feasible with a smaller number of metrics. The document also provides guidance on selecting key performance indicators (KPIs) that can demonstrate progress toward addressing your specific questions.

For example, if your business strategy is to increase market share, focus on questions relating to talent drivers that impact the execution of that strategy and the metrics that HR should monitor to demonstrate progress toward strategic goals, such as:

• Average manager tenure
• Employee retention index
• Managerial quality index
• Staffing rate 鈥� expatriates
• Training hours per full-time employee

Here are five recommendations for how to select and manage a set of KPIs.

Focus on a small core set of KPIs.

When in doubt, leave it out. Select only as many KPIs as you can actively manage. Resist the temptation to include everything you can measure as a KPI. Use three key criteria: a clear link to strategy, a willingness to set targets against the measure, and a willingness to commit resources to managing progress.

Get management buy-in and continuous support.

The saying 鈥渨hat isn鈥檛 measured, isn鈥檛 managed, and what isn鈥檛 managed, isn鈥檛 done鈥� applies here 鈥� active support from executives helps ensure that progress is tracked. Several organizations involve their CEO or head of business unit in KPI selection workshops, which helps with the challenge of gaining executive support. Firms also routinely report performance against KPIs to their boards or executive committees.

Help ensure data quality.

Nothing makes managing KPIs more difficult than suspect data, so you should spot-check the data needed to populate your KPIs. Conduct a structured data verification process to help ensure definition consistency and data validity.

Communicate performance actively and often.

Keep KPIs top of mind. Reports, social media, e-mails, conference calls, and manager question-and-answer sessions all help reinforce the importance of the business objective being measured by a KPI. You should set targets and use benchmarks wisely.

Revisit KPIs periodically.

As your organization鈥檚 strategy changes, so should your KPIs. Your organization should actively pressure test your KPIs at least once a year.

Armed with the right data-driven metrics and insights, your organization can better execute your strategy, drive revenue, manage costs, and mitigate human capital and business risks.

Want to learn more about the power of data-driven decisioning for human capital management 鈥� and how you can start taking advantage of 51风流SuccessFactors Workforce Analytics quickly?

• Be sure to download the document.
• Watch and learn how you can for downstream usage, from a library of over 2,000 metrics with built-in intelligence, and .
• And if you just want a little bit of fun, check out our .

For more information, visit .

Tammie Eldridge is part of Solution Marketing for 51风流SuccessFactors.

For many, Martin Luther King Jr.鈥檚 name is synonymous with his dream of a United States void of segregation and racism. And while his dream has been recognized globally, there is still much work to do to realize it.

I recently sat down with to discuss how people analytics can support organizations’ diversity, equity, and inclusion (DE&I) strategy. Dias is the managing director of as well as the chair and founder of the . He specializes in supporting businesses to make better HR decisions using people analytics and enabling data-driven HR culture.

Q: How does people analytics help HR to solve diversity problems?

A: What areas of your business have the lowest levels of diversity and inclusion, and how bad is the imbalance? Over the years, which HR decisions have caused and added to that inequality? Do different types of employees get promoted differently? Rewarded differently? Hired and retained faster or slower? If you do not change anything, how much worse will the inequality get? If you want to reduce inequality within five years, what HR strategies are most likely to achieve that goal?

With or without data, organizations are making decisions to try to become fairer and more equal. The purpose of people analytics is to enable organizations to make better people decisions; in this case, about achieving diversity goals and solving inequality. By using HR data to answer questions, people analytics helps organizations to make better decisions increasing the likelihood of achieving diversity outcomes across the entire employee experience.

What types of diversity questions are 51风流SuccessFactors customers answering using their data?

In the 2020 Benchmarking study by the HR Analytics ThinkTank, , which is no surprise given DE&I is a priority for most organizations.

These people analytics functions are empowering their HR leaders to solve diversity problems by supplementing HR expertise with answers gleaned directly from data. From day one, people analytics teams can answer descriptive questions, providing facts about what happened in the past and over time. For example, within a particular job family or location, a specific minority group was three times more likely to be promoted than another. Other functions may go one step further, answering questions that diagnose a problem and use data to answer why an outcome has occurred in the past. For example, they might be able to answer why minority groups are more like to resign in particular locations.

The more advanced functions, which research shows take two to three years to build, will create even more value. Some will be asked to spend more time answering critical questions, predicting how the gender equity gap will increase if nothing changes. The most advanced will provide answers to questions by prescribing what should be done; for example, what strategies are most likely to achieve 25% ethnic minority representation at board level within six years.

How are 51风流SuccessFactors customers using Workforce Analytics and Report Stories to tackle diversity problems?

The 51风流SuccessFactors People Analytics solutions has the functionality to support organizations to tackle their diversity issues.

In order to support strategic decision-making, they use 51风流SuccessFactors Workforce Analytics to transform HR data into metrics and dashboards, showing end users the answers to questions about what has happened in the past, displaying insights and trends over time. For example, where is minority representation worsening? In particular grades, job families or geographies is there a difference in the way in which different workers are promoted or hired? Using 51风流SuccessFactors Workforce Analytics, HR leaders can create better strategies and track progress over time.

Using report stories, 51风流SuccessFactors software can provide anyone in the entire business with a snapshot view of their business area. Stories will allow end users to check an answer at any given moment; for example, whether their recruitment pipeline contains a diverse selection of candidates or if all the resignations in the last month have been women.

What steps can 51风流SuccessFactors customers take to prepare for diversity analytics?

The first thing that organizations should do is confirm the objectives that leaders are trying to achieve and identify the questions they need answered to make better choices. In our 2020 study, 94% of 51风流SuccessFactors People Analytics leaders said their function was directly sponsored by an HR executive but only 32% were positive that they knew what their leader鈥檚 goals were. HR leaders need to clearly articulate what their diversity goals are and establish what questions they would like answered by the people analytics team.

The second thing they should do is audit the foundations for data-driven HR success and prepare for the journey. According to the same study, only 42% of 51风流SuccessFactors customers had a plan for what data to capture, only 16% were sure they knew how the people analytics team should be structured, and only six percent were confident that decision-makers understood how to use their insights in decision-making. A lot of diversity questions can be answered on day one using standard 51风流SuccessFactors data, but a plan will be required to provide more complex answers over time.

The final tip is to provide answers with evidence to help ensure that decision-makers are empowered to actually use the insight. If given the option, most HR and business professionals will welcome evidence that helps them achieve their goals, but they will only use the evidence if it is easy to access and formatted in a way that makes it easy to use in the context of their job. The organizations most successful with data-driven HR make sure that decision-makers are enabled with the right skills, and their dashboards create the best experience for users to find the answers they are looking for.

To hear more on this topic, for the upcoming webinar (or listen to the recording), 鈥溾�� on January 26, or visit .

The problem is that every organization is unique in ways that are often not appreciated. Each business has its own culture, strengths and weaknesses, geographic context and impacts, internal and community dynamics, and more that influence what works 鈥� and what doesn鈥檛 鈥� from an HR perspective. Equally important, organizations continuously evolve, so strategies and actions that worked yesterday may not work in the future.

The big “so what鈥� is this: When HR professionals make their decisions based solely on their training and experience 鈥� even when tempered by the recommendations of others 鈥� it can lead to unintended outcomes. Experiences and assumptions must be tested within the current context in each unique business using people analytics.

I like to think of this testing process as 鈥渕yth busting,鈥� which was popularized by the beloved show that goes by a similar name. In the HR world, this means using models of actual employee and organization data to test assumptions and gut instincts. The results are often surprising 鈥� and lead to different decisions and better outcomes for employees and the business.

If this sounds like a lot of work, it鈥檚 not. The 51风流SuccessFactors Workforce Analytics solution is so incredibly intuitive that just about anyone in HR can use it 鈥� no analytics training or expertise required. Plus, it comes with more than 2,000 prebuilt HR metrics. To help focus on the metrics that matter most, the 鈥溾�� brief includes a series of questions designed to help you and your organization understand HR metrics and help you make decisions that will support your executive strategy, drive revenues, manage costs, and mitigate human capital and business risks.

To understand the power of people analytics and why myth busting is more important than ever, consider the findings uncovered by an 51风流customer using 51风流SuccessFactors Workforce Analytics. We showed them how to test widely embraced assumptions and preconceived notions within the HR department against actual business data. Here are just a few examples.

Assumption: The Best Source of New Hires Is Your Current Employees Through Employee Referrals

When we looked at the data for this company, this was not necessarily the case. The best referrals came from top performers only; people referred from average performers did not typically become top performers and turned over at twice the typical rate.

Assumption: Commute Time Is a Key Driver of Turnover

This assumption did prove to be true. The data showed that for this business, turnover correlates to both commute time, travel cost, and geographic location, but not directly to distance. Using 51风流SuccessFactors Workforce Analytics, the business was able to filter for various variables and identify real drivers of turnover as it relates to commuting.

Assumption: Employee Equity Awards of Any Size Increase Retention

At this company, this proved to be true. Giving employees equity in the business through stock, for example, was highly correlated to employee retention.

Assumption: Industry Experience Is a Key Factor in Successful Salespeople

At this company, this long-held assumption did not prove to be true. In some positions studied, salespeople with little or no industry sales experience outperformed seasoned salespeople. This freed HR and hiring managers to focus on a new set of candidates for sales positions and increase the likelihood of having high performers.

Assumption: Previous Work Experience Can Be an Indication of a Candidate’s Future Performance and Expected Tenure

This is a logical and common assumption that did not prove to be true at this business. 51风流SuccessFactors Workforce Analytics revealed that, for this company, previous work experience is not an indicator of future performance or even tenure.

Assumption: The Longer a Person Is with the Company, the Better Their Performance Will Be

Again, this is a logical and common assumption, as employees tend to know their job better over time. But 51风流SuccessFactors Workforce Analytics revealed that for this business, this is not true. The analytics showed that Millennials reach peak performance at one year in a position; after that, boredom sets in and they are ready to change jobs and learn something new. For older workers such as Baby Boomers, they reach peak performance at three years in a role. HR was able to use these data-driven insights to help create an evolving job program for Millennials and Baby Boomers that timed job changes around their respective peak performance timeframes.

It鈥檚 important to note that these analytics results are unique to this business. Another firm in the same industry or other geographic location may uncover very different findings, which would in turn result in very different decisions by HR professionals. Every business needs to understand their own people-related data using people analytics.

Did any of these findings surprise you and challenge your assumptions and experience? What kinds of assumptions and preconceived notions 鈥� many based on logic and past experience 鈥� might you be bringing to your decision-making process? I encourage you to become an HR myth buster by adopting 51风流SuccessFactors Workforce Analytics. To learn more, visit us online at .

Tammie Eldridge is in Solution Marketing at 51风流SuccessFactors.

The funny thing is, in most cases, HR staff already has all the data they need, lots of it. They just don鈥檛 know how to turn it into insights when they need them most 鈥� in the course of their day-to-day work. In recent years, organizations have made vast improvements in collecting and managing their data, including HR and people data. But most of it is stored in silos, making it almost impossible to provide the holistic view of how the organization is doing and what actions to take in the future to realize business goals.

And without these insights, they are back to making countless decisions based on gut instinct, intuition, and habit. This can lead to less-than-optimal outcomes not just for the business, but for employees as well. For example, an HR professional may assume the best recruits come from employee referrals, which may not be true, or falsely assume that industry experience is a key factor in hiring successful salespeople.

There鈥檚 a sign I have that captures the gist of this problem very well. It reads, 鈥淢irror, mirror on the wall, what the heck happened?鈥� When people make decisions based on the insights they鈥檝e gleaned off the surface of things and the habits they鈥檝e developed over the years, they are making decisions based on their intuition, not the hard evidence data can provide. Their insights and habits form the edges of the mirror, constraining their view and limiting their insight to only what they can see in front of them: themselves, their knowledge, and their gut instinct. When their decisions don鈥檛 yield what they expected, they say, 鈥淲hat the heck happened?鈥� Even the outcomes can be hard for them to explain.

HR analytics vastly expand what HR professionals can see and understand. In fact, with the right solutions, they can even get 360-degree views of their workforce, departments, teams, individual employees and contractors, and more. When built-for-purpose HR algorithms crunch all this data, the constraints of the mirror鈥檚 edges are gone. HR staff and executives can see and understand things that their natural mind and eyes would never be able to discern. They can make data-driven, unbiased decisions by looking at metrics, running scenarios, and predicting expected outcomes. And this empowers them to be more effective, unbiased, and strategic decision-makers who are not only more effective HR professionals, but better strategic advisors to the business. For example, they can:

• Identify the promotion rate of minority employees at different levels.
• Monitor employee engagement to see if it increased or decreased in the last 12 months, six months, or three months.

The challenge, however, is making it easy for HR professionals to access and consume HR analytics 鈥� without having to bother IT for custom reports, data models, and other costly resource- and time-intensive requests. They need analytics at their fingertips, all the time.

At SAP, we work to solve this with the 51风流SuccessFactors Workforce Analytics solution. 51风流SuccessFactors Workforce Analytics connects your people, data, and ideas from multiple sources to help enable fast and confident decision-making. It allows users to discover, visualize, plan, and predict, all in one place. And it works to democratize analytics so that anyone 鈥� even nontechnical HR professionals 鈥� can access and use it with ease, every day.

51风流SuccessFactors Workforce Analytics helps you gain the insights you need to lead your workforce, accelerate change, and drive results with:

• Standardized HR metrics: Take advantage of an extensive catalog of more than 2,000 pre-delivered HR and talent metrics. Each metric is described in terms HR professionals understand so they can interpret outputs with ease and make faster decisions.
• Data trending: Track trends through time and across different periods, such as annual, quarterly, monthly, and seasonal time models.
• Actionable analytics: Answer key questions about your workforce and spot risks and opportunities rapidly with visual, interactive HR analytics.
• Integrated data foundation: Integrate data from multiple systems to create a solid data foundation and rely on 51风流software to help manage data quality.

I invite you to explore the “” whitepaper, which includes a series of questions designed to help you and your organization understand HR metrics and help you make decisions that will support your executive strategy, drive revenues, manage costs, and mitigate human capital and business risks. This document provides helpful tips to avoid one of the biggest risks in deploying a workforce metrics capability: 鈥渋nformation overload.鈥�

Find more information on this topic on the .