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When Amazon announced its shortlist of cities for its new HQ2 in January, many job seekers rejoiced, while most talent acquisition professionals were filled with feelings of dread. With Amazon planning to hire upwards of 50,000 employees, the tech giant poses a serious threat to a company’s ability to attract and hire key talent.

Competition in the shortlisted cities is already fierce, especially for those high potential people who will deliver innovative solutions or go above and beyond for your customers. So what can recruiters do to make sure their pipeline won’t be decimated if an Amazon-like company comes to town?

Data-driven recruitment is one smart strategy that you can take to mitigate the risks–and identify the opportunities–associated with big moves like Amazon’s. Here are some people analytics best practices to use in order to mitigate the risk of talent shortfalls:

1. Focus on Job Candidates who Fit Top Quality Hire Profiles

People analytics gives you the ability to track hires across the employee lifecycle–which includes their successes and failures from the moment they applied for their jobs until they left your organization years later–so you can see which candidates end up being the best employees in the long-term.

There’s a finite number of qualified top talent in a city and focusing your efforts on these candidates is one way to snag them before Amazon comes calling. Create a profile of quality hires based on data such as:

  • Qualified applicants-per-requisition (which indicates whether your sourcing practices are delivering those effective employees)
  • Resignations and involuntary turnover for less than three months of service
  • New hire performance by lead source
  • Top talent characteristics (advanced “in-memory” people analytics solutions make it easy to run tailored algorithms to help identify these — otherwise, you can manually calculate using some elbow grease)
2. Estimate Speed of Hire Times with More Accuracy

Getting to great candidates before a company like Amazon is key to keeping your organization filled with high quality talent. When properly done, people analytics enables you to know with confidence how long it is likely to take to hire for a certain role, including time in each stage of the hiring process. With this information, you can provide more credible timelines to stakeholders.

Likewise, this data-driven approach can reveal the bottlenecks slowing down hiring and inform you on the right actions to take to fix them.

Visier People™: Talent Acquisition Eliminates Time to Hire Guesswork - YouTube

3. Create the Best Candidate Experience Possible

While candidate experience has been a hot topic for decades, many organizations still struggle to improve this important part of the hiring process. Analytics brings the factors that impact candidate experience to the forefront so you can measure the effectiveness of each.

Whether it’s time since initial contact, time between stages, interviewer name, etc, you’ll be able to tell what’s increasing or decreasing the likelihood of a candidate withdrawing his or her application — and create strategies to decrease the odds of losing strong candidates.

4. Attract More Diverse Candidates

Hiring diverse talent is in a company’s best interest: Ethnically diverse companies are 35% more likely to have financial returns above national industry medians and gender diverse companies are 15% more likely to do the same.

Traditional recruiting methods make it hard to tell whether you’ll hit your diversity targets or ensure equity during the process. Instead of guessing, use analytics to continuously monitor your hiring funnel for important demographic ratios such as gender, ethnicity, and veteran status. This enables you to better track diversity and implement the correct evidence-based programs to increase diversity throughout your pipeline.

5. Build Realistic Hiring Plans

Recruiting is a fine balance, especially in high risk situations such as a large competitor for talent moving into the neighborhood. While over-hiring can create an unnecessary cost burden, under-hiring can reduce productivity. This is why it’s important for Talent Acquisition to work closely with HR and Finance on data-driven workforce plans that will keep recruiters on target, help them prepare for all hiring scenarios associated with Amazon’s move, and keep everyone on budget.

Position Your Team For Success

The entire HR function is making strides to use data to inform workforce decisions involving the entire employee lifecycle—from identifying the best recruiting sources for finding quality hires to creating hiring plans for impending talent shortfalls.

If there’s one thing you should do to prepare for an Amazon-type move in your city, it’s to look beyond your Applicant Tracking System for analytics. Since these systems are unable to pull data from the full employee lifecycle, you may be at a disadvantage when Amazon–and other risks–come calling. Cloud-based people analytics solutions can offer the complete end-to-end view needed to not only monitor your entire recruiting pipeline (and identify any bottlenecks), but also pull all the historical information on top-performing employees into a single place, enabling you to hire better and faster, and also get ahead of business demand.

Whatever method you use, remember that analytics is not a “one-and-done” process. In order for recruitment to be successful, you must continuously look for ways to improve hiring. Analytics enables you to confidently double down on your strengths and eliminate the areas where you’re weakest so you can meet every talent need of your organization.

A version of this article originally appeared on Recruiter.com.

The post How to Compete For Talent Against the Amazons of Your Industry–and Win appeared first on Visier Inc..

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The Brexit Day countdown is on, and yet, political tussles over whether the UK will keep its close financial services ties with the European Union show little signs of resolving. For large American banks using London as a major European hub, this means there are still multiple futures ahead, each carrying its own implications for talent supply and demand.

JPMorgan, for example, will move between 500 and 1,000 jobs from Britain after the UK’s exit from the EU in March 2019, reported a January 2018 Reuters article. But according to the company’s CEO, if Brexit talks result in “a divergence of regulations and trade agreements” between Britain and the EU, that number would be closer to 4,000.

While a 21-month transition period following the official exit from the EU on March 2019 has bought banks more time to prepare for whatever changes are in store, top US financial services players have started making moves just in case.

Bloomberg has reported that Citigroup Inc. is making plans to have a new Frankfurt trading hub up and running by the end of 2018. Other news outlets have reported that Bank of America is moving 125 UK jobs to Ireland, and Goldman Sachs has started transferring senior staff to Frankfurt.

At the same time, according to a March 2018 Reuters story, top US banks appear to be “keeping plans for large scale recruitment in continental Europe on ice and investing in their well-established London offices instead.”

What Uncertain Business Environments Reveal About Modern Workforce Planning Needs

The lesson here for workforce planners across all industries is this: when the future is unknown, contingency plan with the most dramatic scenario in mind, but book the more conservative plan in the interim until key developments become clear.

Brexit is just one sign of the current topsy-turvy VUCA environment that businesses are operating in today. Typically, VUCA (short for Volatility, Uncertainty, Complexity, and Ambiguity) is associated with the drastic demographic and technological shifts that are making it increasingly difficult to predict future market trends and talent needs. But as recent developments (such as the uncertainty over the DACA program in the US) have shown, politics can also contribute to a VUCA world.

As future business environments become increasingly unpredictable, so too do an organization’s talent needs. But when long-term talent needs cannot be predicted, it is still possible to plan strategically. Approached proactively, agile workforce planning in a VUCA world can help HR anticipate potential issues and opportunities early and often.

Agile Workforce Planning: Best Practices for Strategic HR Pros

Here are three agile workforce planning best practices that will help HR leaders win in an era of uncertainty:

#1. Explore multiple futures

Scenario planning enables HR leaders to rapidly execute a talent plan when new developments suddenly crop up. While this kind of activity is often driven by broader business contingency planning, it is important to note that HR does not necessarily need to wait for an operational plan before mapping out various talent scenarios.

To make this process easier, HR leaders can look for technology and tools that enable them to create and compare different workforce planning scenarios (each with different workforce movement and cost assumptions) so that not only can they choose the best option for your organization, they can have contingency plans in place. In this way, scenario planning is a key component of agility.

#2. Plan continuously

Typically, the workforce planning cadence is driven by finance, with budgets firmly set for the year. But when a business faces unprecedented levels of change — such as a digital-driven competitor emerging partway through the year — there may be a need to correct course in a much shorter time frame.

One large financial services company, for example, uses a monthly planning process to capture workforce demand for the different groups within the organization. The planning process involves over 100 VPs, directors, and managers, but other stakeholders are pulled in as necessary: If hiring isn’t progressing as fast as required, they talk to recruiting; if the plan is over budget, they discuss it with finance. This continuous, collaborative planning approach enables HR to react more appropriately to changing business requirements.

#3. Focus on costs

At our recent Outsmart 2018 event, a conference for data-driven leaders, one theme that emerged is the importance of understanding the organization’s Total Cost of Workforce (TCOW). This is the full cost for people who contribute work to the organization, including all of the labor costs and the workforce overhead costs, and all the costs that roll up into those two categories.

During a panel discussion, one HR leader from a travel technology company emphasized the importance of using this information when considering areas such as centralization and how to control costs. This lets HR take a very targeted approach when dealing with high-priority business problems.

When there are multiple options to explore, HR leaders who can shed light on the cost implications for talent are in high demand.

Plan Big, Act Prudently

The RBL group, a global professional services firm, surveyed thousands of professionals and found that the most effective HR professionals “make an organization’s internal capacity for change match or lead the external pace of change.”  

Continuous, cost-driven planning — when combined with a consideration of several dramatic and status quo possibilities — enables HR leaders to stay ahead of the curve. This kind of approach enables businesses to hire based on genuine need, and respond more quickly to market shifts, while forecasting more accurately.

When addressed head-on, uncertain futures provide HR leaders with an opportunity to shape the business alongside their functional peers. For strategic HR leaders, this focus on agile workforce planning can yield many positive returns.

The post How Businesses Will Win in An Era of Uncertainty appeared first on Visier Inc..

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The Brexit Day countdown is on, and yet, political tussles over whether the UK will keep its close financial services ties with the European Union show little signs of resolving. For large American banks using London as a major European hub, this means there are still multiple futures ahead, each carrying its own implications for talent supply and demand.

JPMorgan, for example, will move between 500 and 1,000 jobs from Britain after the UK’s exit from the EU in March 2019, reported a January 2018 Reuters article. But according to the company’s CEO, if Brexit talks result in “a divergence of regulations and trade agreements” between Britain and the EU, that number would be closer to 4,000.

While a 21-month transition period following the official exit from the EU on March 2019 has bought banks more time to prepare for whatever changes are in store, top US financial services players have started making moves just in case.

Bloomberg has reported that Citigroup Inc. is making plans to have a new Frankfurt trading hub up and running by the end of 2018. Other news outlets have reported that Bank of America is moving 125 UK jobs to Ireland, and Goldman Sachs has started transferring senior staff to Frankfurt.

At the same time, according to a March 2018 Reuters story, top US banks appear to be “keeping plans for large scale recruitment in continental Europe on ice and investing in their well-established London offices instead.”

What Uncertain Business Environments Reveal About Modern Workforce Planning Needs

The lesson here for workforce planners across all industries is this: when the future is unknown, contingency plan with the most dramatic scenario in mind, but book the more conservative plan in the interim until key developments become clear.

Brexit is just one sign of the current topsy-turvy VUCA environment that businesses are operating in today. Typically, VUCA (short for Volatility, Uncertainty, Complexity, and Ambiguity) is associated with the drastic demographic and technological shifts that are making it increasingly difficult to predict future market trends and talent needs. But as recent developments (such as the uncertainty over the DACA program in the US) have shown, politics can also contribute to a VUCA world.

As future business environments become increasingly unpredictable, so too do an organization’s talent needs. But when long-term talent needs cannot be predicted, it is still possible to plan strategically. Approached proactively, agile workforce planning in a VUCA world can help HR anticipate potential issues and opportunities early and often.

Agile Workforce Planning: Best Practices for Strategic HR Pros

Here are three agile workforce planning best practices that will help HR leaders win in an era of uncertainty:

#1. Explore multiple futures

Scenario planning enables HR leaders to rapidly execute a talent plan when new developments suddenly crop up. While this kind of activity is often driven by broader business contingency planning, it is important to note that HR does not necessarily need to wait for an operational plan before mapping out various talent scenarios.

To make this process easier, HR leaders can look for technology and tools that enable them to create and compare different workforce planning scenarios (each with different workforce movement and cost assumptions) so that not only can they choose the best option for your organization, they can have contingency plans in place. In this way, scenario planning is a key component of agility.

#2. Plan continuously

Typically, the workforce planning cadence is driven by finance, with budgets firmly set for the year. But when a business faces unprecedented levels of change — such as a digital-driven competitor emerging partway through the year — there may be a need to correct course in a much shorter time frame.

One large financial services company, for example, uses a monthly planning process to capture workforce demand for the different groups within the organization. The planning process involves over 100 VPs, directors, and managers, but other stakeholders are pulled in as necessary: If hiring isn’t progressing as fast as required, they talk to recruiting; if the plan is over budget, they discuss it with finance. This continuous, collaborative planning approach enables HR to react more appropriately to changing business requirements.

#3. Focus on costs

At our recent Outsmart 2018 event, a conference for data-driven leaders, one theme that emerged is the importance of understanding the organization’s Total Cost of Workforce (TCOW). This is the full cost for people who contribute work to the organization, including all of the labor costs and the workforce overhead costs, and all the costs that roll up into those two categories.

During a panel discussion, one HR leader from a travel technology company emphasized the importance of using this information when considering areas such as centralization and how to control costs. This lets HR take a very targeted approach when dealing with high-priority business problems.

When there are multiple options to explore, HR leaders who can shed light on the cost implications for talent are in high demand.

Plan Big, Act Prudently

The RBL group, a global professional services firm, surveyed thousands of professionals and found that the most effective HR professionals “make an organization’s internal capacity for change match or lead the external pace of change.”  

Continuous, cost-driven planning — when combined with a consideration of several dramatic and status quo possibilities — enables HR leaders to stay ahead of the curve. This kind of approach enables businesses to hire based on genuine need, and respond more quickly to market shifts, while forecasting more accurately.

When addressed head-on, uncertain futures provide HR leaders with an opportunity to shape the business alongside their functional peers. For strategic HR leaders, this focus on agile workforce planning can yield many positive returns.

The post How Businesses Will Win in An Era of Uncertainty appeared first on Visier Inc..

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Editor’s note: This popular article has been updated to include new research and data.

According to LinkedIn’s 2018 Global Recruiting Trends report, 56% of recruiters use talent acquisition data to increase employee retention. 

Employee retention is a key measure for quality hire, but it’s only one of three factors that you should be monitoring. Additionally, in order to more accurately measure these factors, you need to look beyond the data in your ATS.

A Fortune 1000 organization hired a third-party assessment consultant to rate job candidates using a scoring process that promised to identify which candidates would stay and perform well long-term. However, when these scores were applied to employees once they started working, the organization learned that so-called “high scoring” candidates (who were hired!) were actually the people leaving the company the fastest. It was only when post-hire data was analyzed that quality of hire could be more accurately assessed.

According to Mollie Lombardi, CEO of Aptitude Research Partners:

“The ability to integrate hiring data with individual and team performance data, as well as with other talent management data, is an incredibly important element to understanding whether or not you are getting real value from your new hires.”

In order for the pre-hire data in your ATS to be useful, a complete picture of the employee lifecycle is need. You must first look at post-hire data on high performers in your organization, specifically those related to whether these people Stay, Perform, and Progress.

These three factors provide the critical insights you need to determine what a quality hire means at your organization, so that when you go into your ATS to assess candidates, you’ll have a more reliable way of selecting the ones that will perform well at your organization long-term.

Let’s look at these three critical factors in more depth:

1. Stay: How long did the hire stay at the organization?

For an employee to be considered a quality hire, he or she should return more value to the business than was used to source, train, and develop them. It takes time for true value — the kind that makes a solid impact on business objectives — to be created, which is why tenure is the first measure of quality.

The longer an employee is with the organization, the more time they have to contribute to value creation, such as sales or customer satisfaction, and therefore, exceed the investment the business first made when they were hired.

On a very basic level, if it costs more to recruit and hire someone than the value returned by that individual when they’re employed with you, then the hire should not be considered to meet the foundational criteria for quality.

If it cost a bakery more to source flour than it made from selling bread, it would soon be out of business! Similarly, the minimum bar for assessing quality is that the value delivered by the employee exceeds the investment in their acquisition.

However, the ways in which employees deliver value is varied and complex. In some call center situations, an employee can be fully competent in days, and have covered their acquisition costs in weeks. In certain high tech situations, the payback period could run into months. Or, for a Sales Executive joining an Enterprise Software firm, the payback period may be as long as a year or more. It is common to use 90 days (the typical probationary period) as a measurement time frame in these cases.

2. Perform: What is the hire’s performance like?

If spending time to deliver value is the foundational criteria, then the next critical factor is the quality of the work done in that time. Remember: the purpose of assessing hire quality is to determine whether or not the people being added to the business are increasing the capacity to create value. Hence, the next key factor is the performance level of the new hires.

Simply put, a quality hire is a high performing hire. Strong performers make the difference between hitting business objectives and missing them.

Human performance is varied and assessment needs to take place over time. Therefore, in assessing the quality of a hire, their ability to meet or exceed performance expectations should happen regularly.

For this reason some organizations include multiple assessments of performance during the employee’s first year and as part of the onboarding process. In addition to keeping the new employee on track, this provides a valuable source of data in assessing quality.

There is an unbreakable link between the organization’s processes and the ability to measure important results. Without any form of performance assessment it is not possible to properly assess the quality of a hire.

Whether the assessment is focused on the first two years of an employee’s tenure in order to determine if your recruitment strategies are bringing in people who can create value, or if the view is longer term and focused on understanding whether the organization is able to retain these people and increase their capacity to deliver value — without the right processes, and supporting data, these types of critical insights are not possible.

3. Progress: Did the new hire progress through their role or move to a higher position? How long did it take?

The final and most significant measure of hire quality is whether or not the new hire is able to progress up the organization. A promotion to a more complex role is a clear sign that the person who was hired is aligned to the organization’s value creation needs. However, even intra-role progression, such as being trusted with more complex work or a higher volume of work, shows the type of progress that is an indicator of hiring quality.

One caveat is that progression within role is often expected and therefore, when it comes to assessing how progression contributes to quality, it is the relative speed of progression that is most important. For example, if an individual moves forward faster than average they should be seen as a higher quality of hire.

However, the relative speed of the progression is the most differentiating factor — and also hardest to measure.

In addition, if a new hire does not get promoted it is by no means an indication that they were low quality. Every organization needs solid performers who are content to consistently deliver in their role.

Understanding the extent to which the rate of progression distinguishes a good hire from an exceptional hire requires a detailed understanding of the organization and its specific roles, and the application of robust data science to turn this into an appropriate measurement model.

Using Talent Acquisition Analytics to Measure Quality of Hire

Now that you know what the Stay, Perform, and Progress measures are about, you can use analytics to examine the data related to each one:

  • Your goal is to find out which individuals have stayed the longest, performed the best, and progressed quickly through the organization — this data will reveal who are your top performers.
  • Once you’ve identified these employees, run another analysis to determine what attributes they have in common. Is it their prior experience? Is it their manager? Are they on a team with other high performing individuals? Did they receive more onboarding or less training than others?
  • Compile these attributes together and combine it with data from your ATS or candidate CRM. Compare these attributes to the job candidates in your slate and use it to find the next superstar for your organization.

Keep in mind that all this information is contained within disparate systems, which makes doing this by hand on spreadsheets or relying on the analytics included with your HRMS a costly, risky and time-consuming venture.

If finding out quality of hire attributes is truly important to your Talent Acquisition team, consider investing in a workforce intelligence solution. This technology connects all your data systems together in one place and makes analyzing the information as easy as selecting the relevant question from a preloaded list.

To help you understand what other actions your team can take to improve quality of hire, check out the post 4 C’s of Quality Hire by Mollie Lombardi.

The post Measure Quality of Hire With These Three Critical Factors appeared first on Visier Inc..

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Nurse burnout–a state of physical, mental and emotional exhaustion caused by chronic stress–is a common problem in healthcare, one that came up often when I served as Director of Workforce Analytics and Special Projects at Vancouver Coastal Health, one of the largest healthcare organizations in British Columbia.

It’s a prevalent problem industry-wide. According to a 2010 study of California’s policy by Linda Aiken, et al., 29% of nurses in California experienced high burnout, compared with 34% of nurses in New Jersey and 36% of nurses in Pennsylvania.

Nurse burnout has impacts that can be subtle–a nurse who has a lack of empathy for their patient because they are simply too tired to be able to be kind–or severe–a nurse who is off work and seeking counselling to recover their mental health before being able to go return to the hospital floor.

“Nurses are nurses because they genuinely want to take care of people,” says Dr. Stacy Sprague, PhD, R Psych, Executive Director, Employee Wellness at Vancouver Coastal Health. “They feel compassion for their patients, but years of exposure to long hours, strenuous shifts where they are often tasked to run short, and difficult patients can cause compassion fatigue, which is a really clear indicator of nurse burnout. Compassion fatigue can look like a nurse feeling detached, and cynical about their job, and that they are failing as a nurse. This can result in a higher level of moral distress for a nurse and can compromise their ability to give their usual high level of patient care and can push them towards taking long-term leave. This in turn puts even more strain on an already taxed system.”

HR needs to take a compassionate approach to reducing nurse burnout and, strange as it may sound, people analytics and data can truly help in the effort to see the issues from the nurse’s point of view.

What’s Driving Nurses to Burnout?

According to a 2017 study by Maura MacPhee, PHD RN, Professor, University of British Columbia School of Nursing: “Burnout has been linked to higher rates of absenteeism than the general population and to increased nurse turnover and decreased job satisfaction.”

McPhee also found that “nurses who experienced heavy workloads on a daily basis were 3.5x more likely to report high emotional exhaustion than nurses who experienced heavy workloads less frequently.”

Clearly, nurse burnout is bad for patients and bad for business, so why is it so hard to avoid? There are certain forces that put pressure on nurses to work past their limits:

Systemic forces

As baby boomers reach post-retirement age, their demands on the healthcare system increase. Additionally, as the older generation of nursing staff reach retirement age, the supply of experienced nurses reduces, especially in areas that require higher levels of training such as critical care (e.g. intensive care unit nurses). Put simply, there aren’t enough nurses to serve the patient population.

24/7/365 scheduling

Scheduling and deployment of nurses are based on patient needs. This means that even though nurses are professionals, they are deployed as shift workers. In order to meet patient needs, 12-hour and 8-hour shifts operate on a rotational pattern. Nurses on 12-hour shifts experience higher levels of chronic fatigue, cognitive anxiety and emotional exhaustion and are also 2.5x more likely to burnout. However, nurses often choose 12-hour shifts because it provides them with a shorter work week (a “4 days on/4 days off” shift pattern).

The significant systemic and personal pressures that nurses face can make it difficult to make rational choices, especially in an industry where empathy and compassion are so critical. This is where people analytics can make a difference.

How to Leverage Data as Your Diagnostic Tool

People analytics uses data to illustrate behavior in the workplace and can uncover issues such as chronic overwork. This empowers the business to devise a plan to effectively solve workplace issues.

Adds Dr. Sprague, “To me using people analytics is a whole new way of doing business. We used to say that finances drove a business, but I think people analytics shows us that behavior also drives a business, and the more we can understand our business using people analytics, the more successful we will be at providing it.”

Here are four data-driven strategies you can use to reduce the burden on nurses.

1. Determine the metrics that will to shed insight into overwork and use them to inform a fatigue policy

Many healthcare organizations have metrics such as overtime compared to straight time worked. These help to illustrate how much a person is working above the job that they have taken.

I propose a total burden-of-work metric that includes straight time work that the employee has agreed to (e.g. I am part-time so expect to work 0.6 FTE or 40hours X 0.6 = 24 hours per week), plus whatever actual overtime hours, on-call hours, etc.

Comparing the amount that employees are actually working compared to the amount they are contractually obligated to perform is very helpful in uncovering issues. Identifying these issues (e.g. unusually high burden of on-call shifts) and engaging in collaborative planning can lead to staffing solutions which distribute the workload better or determine creative ways to off-load this burden, and can increase efficiency (e.g. lower overtime hours and costs which also benefits employers).

2. Link data from all your disparate HR and business systems to gain insight

Reducing burnout requires data to come together from multiple sources. This gives you a more accurate picture of the employee lifecycle, so you can identify where to focus your efforts. For example, determine which nursing group is experiencing the most burnout or may be on the verge of burnout (based on historical trends) by pulling HRMS records to get job and turnover information, as well as actual compensation or timekeeping data to get hours worked.

Use analytics-driven workforce planning to create forecasts and scenario models that will help you fill the staffing gaps. Bring in talent acquisition data to set achievable targets for recruiters to find already trained staff and dive into learning analytics to set education targets for how many highly skilled nurses you can expect to train. Link the learning data to job records and turnover to ensure your training spend is achieving ROI – that nurses are staying in the jobs you are training them for.

3. Implement a data-driven scheduling model

Likewise, having regular and easy access to all the data in your employee lifecycle enables you to proactively build more creative and flexible scheduling systems, ones that affords more frequent opportunities to choose a level of work that is sustainable on the individual’s side while meeting the scheduling needs of the employer. Test different scheduling models with outcome measures – employee groups with lower turnover and sick rates are probably working healthier schedules.

This can be as simple as implementing a break relief schedule where the data indicates employees are missing meal breaks or as complicated as forming a relief staffing strategy for areas with more pervasive, longer standing issues.

Using analytics, identify the most effective way to backfill for vacancies, long-term leaves, and short-term predictable leaves (yes, it is possible to predict sick time with the right data sources and analytical solutions).

4. Get ahead of turnover

Voluntary turnover in the form of resignation is a strong indicator that there is an issue with burnout in a particular unit. Nurses may choose to change their full-time status moving to part time or even casual status in order to exert more control over their work life and have more choice over which shifts they work.

Monitoring data on the number of hours being worked or time off for sickness may also provide earlier warning signs. Engagement or culture surveys offer a rich source of data as well that can provide forewarning of systemic issues.

I cannot stress enough the importance of moving beyond reporting into analysis to see the hidden patterns that are driving turnover and if possible, move to machine learning-based predictive analytics. Putting these together with a collaborative workforce planning tool will give your management teams insight into whether the actions they are undertaking are having an actual effect on improving the well-being of nurses.

Pondering Future Uses of People Analytics in Healthcare

A solution such as a people strategy platform enables you to set and control access to people analytics within your organization. Usually, access is given to the HR team and in increasing cases, directly to people leaders, but it’s also worth imagining a future where analytics is used even more broadly, such as by the nurses themselves.

For example, sharing data in a way that would help nurses see patterns in their work-life balance. Or what if each employee had a personal dashboard where they could see the amount of overtime, straight time, sick time, on-call that they were working in comparison to the distribution of their peers?

I can imagine that this data would be very helpful in conversations with their manager to identify longer term patterns that are not necessarily apparent in the moment. This could range from realizations of ‘I seem to be calling in sick more than my peers’ or ‘I’m taking on more overtime than my peers’ leading to a productive discussion of what wellness and scheduling programs can be used to help the employee.

I don’t mean to over simplify the situation here and I realize these discussions are complex. I also realize each person is different and can and may want to choose a different level of work. The important point is that transparency and data can help to illustrate patterns that are important discussion topics between the employee and the employer–and lead to a healthier workforce and industry overall. 

The post Diagnosing and Preventing Nurse Burnout Using People Analytics appeared first on Visier Inc..

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Our annual people analytics and workforce planning conference, Visier Outsmart, has wrapped and we’re excited to share all that happened with you. “Be Courageous” was a theme overheard in many of the sessions and conversations. With people analytics and data-driven workforce planning both ever-evolving, HR and business leaders must continuously be fearless in their pursuit of innovation and change within their organizations. Here’s a recap of Visier Outsmart 2018:

Two days packed with insights

We had many fantastic speakers at this year’s conference, covering topics that included the key ingredients for success when implement people analytics and workforce planning solutions, pushing the boundaries of people analytics, the Future of HR, talent acquisition analytics, improving learning and performance with data, storytelling with data, and transforming leadership dialogs with people analytics. Please feel free to download our notes straight from the link below!

Download Visier Outsmart 2018 Key Takeaways

Here’s are a few highlights from the sessions:

  • Don’t just think about retention predictors, but use analytics to figure out how to solve an issue like productivity
  • People want to have a Netflix-like experience, but the issue with that it provides recommendations based on what you’ve done in the past, but if you want to change and pivot where you want to go?
  • You can start strategic planning without doing the operational planning. You can start modeling out future-states right away. Jump right into that long-range planning without going the operational route.
  • HR has a responsibility to put the tools and strategies in place that will help the company do good things
  • Your CHRO is your most effective champion. If they’re saying “this is a tool to solve business problems,” it changes the tone of adoption and use.
  • Talent has the same challenges as other HR functions. They need to start talking business. Time to fill is of no interest. Talk about what that competitive differentiator is in talent and then, you can set a different stage.
  • Don’t make assumptions and truly listen to your community and stakeholders
  • Show people data compelling to the work that they’re doing and they’re likely to be receptive
Congratulations to our Vizzies

We also held our inaugural Vizzies at this year’s Outsmart conference. The Vizzies recognize stand-out individuals and teams in the areas of people analytics, data-driven workforce planning, data-driven storytelling, HR impact and business results, and more.

“We are honored to partner with leading organizations from around the world to help transform their people strategies. The Vizzies symbolize the impact that effective people analytics and workforce planning can have improving business performance,” said John Schwarz, Visier’s Co-Founder and CEO.

Congratulations to our winners from BNY Mellon, Merck KGaA, Ascension, Genentech, Realogy, Indiana Packers, BBVA, and more! View the full list in our press release.

A Look Into the Future (Literally)

Visier Outsmart is one of the first places you’ll hear (and see) the latest innovations going into our award-winning solution, Visier People. This year, we announced the availability of Career Journeys, a first-of-its-kind capability – now included in Visier People: Talent – that analyzes the lifecycle of an organization’s people to answer important questions about the movement and development of talent. With Career Journeys, people managers can understand career mobility like never before, answering questions such as:

  • What intermediate roles should I consider to achieve my career goals?
  • Which path is the quickest, and which is the most common?
  • How long does an individual typically stay in each role?

Career Journeys is an exciting capability that will help talent leaders calculate the many routes employees have taken from one role to another. The outcome is a map of all the career paths taken within an organization, with insights into the fastest and most common paths. Read more about Career Journeys here.

Thank you to everyone that joined us at this year’s Visier Outsmart! You can see even more of what happened at the conference at #VisierOutsmart

The post Be Courageous with People Analytics: Recap of Visier Outsmart 2018 appeared first on Visier Inc..

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It turns out that HR shares a passion with economists. Hiring, vacancies and turnover are critical measures on both the state of the economy and the health of the organization.

If you read the financial papers, economists will point to record levels of new job openings, and what follows — voluntary resignations. While most organizations will focus on improving their ability to hire, the savvy ones know that retaining talent is just as critical. Some turnover is healthy for organizations, but the danger in such record-setting times is passing a critical threshold of talent loss.

Every organization has the resiliency to absorb the loss of talent, but that resiliency has a limit before serious business impacts start occurring. Identifying the why, where and who of flight risks before they appear is the only way to proactively avoid losses in productivity, revenue and profits.

For many organizations, voluntary turnover costs millions of dollars. When the direct costs of replacing an employee, interim reduction in labor costs, and costs of lost productivity are all taken into account, the total cost of voluntary turnover is $109,676 per exiting employee for an average U.S. organization, according to Bersin by Deloitte research.

But when well-intended employee retention tactics are applied to everyone in the organization, their results can be limited, doing little to alleviate flight risk. We would never consider a “peanut butter” strategy for compensation adjustments, but retention programs are too often spread thin across the organization, which increases costs and decreases effectiveness.

The answer? Rather than crafting across-the-board retention programs, HR organizations need to sharpen their focus and apply dollars where they’ll have the most impact. This requires businesses to be far more sophisticated in uncovering the root causes of turnover, and to adopt more analytical approaches that increase their ability to identify flight risk factors and arm business partners with the data to drive action.

Here are three key questions HR leaders need to ask when tackling turnover and how analytics can help uncover the relevant insights:

Question #1: Where is the greatest business risk?

Before designing retention initiatives, you must first figure out the impact of churn. To determine this, drill down to understand the consequences of losing talent in different departments, roles, functions or geographies. After all, what counts as high turnover in one area may be normal in another. Ultimately, the greatest business risk exists where exceptionally high turnover exists for talent with high impact to business outcomes.

For example, the people analytics team at BBVA Compass, a U.S. banking franchise, discovered that turnover was highest for one particular revenue-producing role. By using an analytics platform, they quickly discovered that at certain branches, turnover for that role was significantly higher: 70 branches — about 10 percent of all branches — accounted for 41 percent of all turnover.

To help improve retention, the team crafted a strategy targeting the 70 high-turnover branches. The results have been significant: Annual turnover for the revenue-producing role has improved dramatically at those branches, dropping by 44 percent since the start of the project.

Another organization, Children’s Health, used analytics to build a compelling business case that supported the implementation of programs to reduce turnover. This included a detailed cost-of-turnover analysis with a bottom line of almost $15 million of projected savings over three years.

Drilling into the data, the HR team discovered that some hospitals had a higher than average first-year turnover rate. After examining onboarding practices and other infrastructure, they focused on several key initiatives, such as pay. It turned out that a very slight increase in hourly wages was a powerful retention tool, and far less expensive than what the organization was incurring with chronic turnover costs.

Thanks to these programs, the HR team was able to drive down first-year voluntary turnover from 17.8 percent to 15.3 percent.

As these examples show, by pinpointing where the problem is happening and the impact to the business, HR can strategically invest in programs that will have the biggest results.

Question #2: Why are people leaving? Why are they staying?

To tackle flight risk effectively, it’s also important to uncover the why of the turnover problem.

Micron, a world leader in memory technology, focused on creating clearer job descriptions after it discovered that workers were more likely to leave if they felt their job hadn’t been accurately described when they were hired.

For other companies, the solution involves a greater emphasis on hiring from within the community (if relocation is an issue) or helping employees establish social ties at work (if job embeddedness is the problem).

The reasons for turnover vary, and identifying the key drivers of resignations allows HR to develop refined retention programs by targeting root causes.

Machine-learning techniques can scan hundreds of employee attributes to uncover hidden patterns behind increasing, or decreasing, resignations. Trained on the thousands of historical resignations, these advanced analytical approaches often find the patterns that humans miss: Unsupportive managers, excessive commute times, lack of training, poor onboarding and other factors may be difficult for leaders to observe.

With an analytics platform that pulls together records from the HRIS, talent management, applicant tracking, engagement, learning management and other HR systems, and connects the data, the patterns subsequently uncovered can span the employee lifecycle. The processes of hiring, performance management, compensation and training shouldn’t exist in silos, and neither should analysis of the data these processes collect.

Question #3: Who exactly is likely to leave?

Ultimately, machine learning algorithms that bring data together across the employee lifecycle can go beyond finding the patterns of why people are leaving, and make predictions about who presents the greatest flight risk. Knowing who is likely to leave is incredibly important, because it allows you to make the most targeted action plans to retain talent. Individual retention plans can be created for key talent that addresses factors personal to them.

Predicting flight risk can involve some pretty sophisticated technology and techniques, but it need not be rocket science: Ultimately, it’s about building a profile of the organization’s talent who left in the past, which can then be used to identify similar characteristics in existing employees.

Advanced “in-memory” workforce intelligence applications make it easy to run tailored algorithms to help identify flight risk. Many predictive technologies are based on simple regressions or static models, instead of machine learning which involves continual adaptation and refinement.

One particular machine learning technique, called “random forests,” examines historical employee data and employee events like promotions, resignations and internal hires to learn a set of patterns and construct decision trees that help predict the occurrence of an event. This has been proven by data scientists to be up to 17 times more accurate than other methods.

The End of Retention Guesswork

“We see some problems as just part of the fabric of everyday life, inevitable and immutable, and miss spotting the potential to do something about them,” writes business journalist Amanda Lang in her book, The Power of Why. High levels of attrition need not be accepted as a fact of life.

Armed with workforce data, HR can tackle turnover with a razor-sharp focus on the issues at hand. A more data-driven approach makes it easier to quantify the impact of key programs, helping HR garner the kind of executive support that is crucial to retention success.

This post first appeared on Recruiting Trends.

The post 3 Ways People Analytics Ends Employee Retention Guesswork appeared first on Visier Inc..

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“Build vs. Rent” is a common dichotomy in technology buying, but what does it mean when applied to people analytics? What should you be aware of before committing to one path or the other?

The race to adopt people analytics is heating up: according to the Bersin by Deloitte HR Technology Disruptions for 2018 report, “people analytics is now a must-have discipline within HR and business.”

But, as more and more HR organizations grow their analytics function, I’ve noticed that not all journeys are the same. While the same talent challenges are spurring companies to become more data-driven in workforce decision making, the approaches they are taking fall mainly into two different camps: build or rent.

Building your People Analytics Solution

Recently, I learned about a large software organization’s quest to build a people analytics solution. The goal was to better enable HR and business leaders to make talent decisions that would have an impact on the business. To achieve this, the company hired an HR business intelligence team, standardized their reporting metrics, and invested over $3 million in a data warehouse and business intelligence (BI) software.

This company took the “Build” route to people analytics — a traditional approach that with modern tools, like Tableau, Qlik, or TIBCO, may initially look cost effective, and even “easy.” However, the purchase of a few relatively inexpensive BI licenses is just the tip of the iceberg: there are many more costs and complexities “below the waterline” that are only revealed the further you go.

According to a recent report by Gartner, which compares the total three-year BI platform ownership costs across vendors, vendor types, and deployment sizes: “Buying low license cost platforms does not always translate into low business intelligence platform ownership cost (BIPOC) over time or into higher business benefits.”*

In fact, if you isolate the purchase of the initial BI tool licenses, you are looking at just 10% of the total cost of the platform being built — the tip of the iceberg.

What seems like a straightforward toolset purchase at the beginning turns out to be a much larger and costlier project, requiring:

  • Additional Data Discovery licenses
  • Hardware purchase and maintenance
  • Data warehouse software licenses
  • Data integration tools licenses
  • Data center maintenance costs
  • IT administrators
  • Subject Matter Experts to determine questions to ask
  • Analysts to determine metric definitions and create reports
  • Software developers to build each output
  • Software maintenance fees
  • Other implementation costs, such as the development of dashboards and training

Why is this the case with the build path?

BI vendors, whether they sell Data Discovery, Data Integration, or Data Warehouse tools, are focused on providing their technology to you as a toolset. The actual work to build a solution that is tailored to meet your needs — such as answering questions about recruiting, employee retention and engagement, or diversity and inclusion — requires you or a vendor you hire to develop the solution from the ground up. Some BI toolsets might provide “starter packs,” to help you get going, but ultimately, you must still design and develop your own solution, integrate your data, and perform ongoing maintenance and updates.

Once the costs of the necessary hardware, software, development, IT, and admin requirements are added together, enterprise companies will have typically spent millions of dollars on an implementation that might have looked low-cost and quick at the start.

And this only includes the workforce analytics component of the solution. A true people analytics solution will also be part of a people strategy platform that enables data-driven workforce planning —  a capability set not supported by BI tools.

Fortunately, there is an alternate path — one that is becoming recognized as a leading practice —  where everything involved with the people analytics iceberg is known and taken care of upfront at a fraction of the cost: the “Rent” option.

Renting your People Analytics Solution

Software-as-a-Service (SaaS) refers to software that is licensed or “rented” to customers for use over the web or in the cloud. This means your costs are transparent and fixed (although you need to vet this, as not all SaaS solutions are the same), and the risks associated with managing your own BI project are removed.

A SaaS solution for people analytics should work “out of the box” and can be rented for a fraction of the cost to build a BI solution. At Visier, we refer to this as “add data and stir.” However, not all solutions are equal — and it is important to understand what services are provided as part of your SaaS fee, and what you are expected to do yourself.

Be sure to check the following services and capabilities are included in your fixed SaaS subscription fee to ensure no hidden costs:

  • Virtual Big Data Warehouse (What do you need to do to get your data onboarded into this warehouse?)
  • Data integration (How much will the vendor do for you? How much must you do? What happens if you need to add or switch data sources?)
  • Data discovery (Is this all done for you?)
  • Workforce metrics, analytics, and visualization (What is the scope of the content provided to you?)
  • Workforce planning capabilities (What is the scope of the capabilities provided to you?)
  • Product updates
  • Ongoing data management, maintenance, and support
  • Secure hosting in the cloud

(For more about what to look for in a SaaS solution, download the free checklist for Choosing the Right People Analytics and Workforce Planning Solution for Your Organization)

Ensure your SaaS solution for people analytics also doesn’t limit the number of users due to cost. To enable true adoption of a data-driven mindset in your organization, you need to make “self-service access” to insights widely available.

Comparing Build vs. Rent Head-to-Head

Let me illustrate the differences between the Build and Rent paths by returning to our example of the software company from earlier.

The chart below shows the company situation after three years of building their own solution:

Their progress looks good having reached the strategic level on the “People Analytics Maturity Curve.” However, the money invested and the staffing levels required are significant. They currently support only 200 users, yet have a 15-person analytics team: a team size even large enterprises can only dream of, and a team five times larger than necessary — the benchmark is one analytics team member per 3500 staff in an organization. To support more users at the same level, they must spend even more money, hire more members to their analytics team, and buy more toolset licenses and hardware.

On the other hand, a Fortune 500 company opted for the Rent option in their data-driven journey and implemented Visier. These were their results, compared to the software company that followed the Build path:

This side-by-side comparison shows the advantages of choosing the rent option for the datafication of your HR function. Our iceberg example illustrates this point as well:

If you look at just estimated staffing costs, the difference in team size alone demonstrates the efficacy of the “Rent” option. Forrester Consulting found that Yahoo experienced a cost savings of over $2.2 million because renting enabled a cost avoidance of 10 FTEs.

Keep Scalability Top of Mind

When assessing the path you want to take, scalability is an important factor. What can get a result in the short term is unlikely to serve your longer-term goals. Time and time again, we’ve had customers tell us that once they showed their people analytics solution to business leaders, everyone wanted to get their hands on it. If they didn’t have a SAAS solution, it would have cost more than the organization was willing to invest to provide self-serve analytics to the full enterprise.

To borrow from Stephen Covey: “Begin with the end in mind.”

*Gartner, Survey Analysis: Customers Rate Their Business Intelligence Platform Ownership Cost, Rita L. Sallam, Josh Parenteau, Cindi Howson, Ehtisham Zaidi, 27 August 2015

The post Build vs. Rent: Don’t Crash on the Do-It-Yourself Iceberg for People Analytics appeared first on Visier Inc..

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For humanity, major socio-economic transformation is nothing new, but the rise of artificial intelligence (AI) requires the world to adapt and realign to a new reality more rapidly than ever before. How will we cope?

It took 150,000 years to become an agrarian society and complete the transition from hunting and gathering. Over the next 10,000 years, the economy slowly evolved as populations grew. The real change came with the advent of the industrial revolution. 200 years ago, we began to move from farms to factories. Enabled by fast transportation, open foreign currency exchange, trade policies and communications, the economies quickly became global. We are still completing our most recent, 50-year shift to a services-based economy. Relatively speaking, these were all gradual shifts—and yet, they disrupted lives and dramatically transformed whole societies.

Now, we stand on the brink of a fourth economic revolution, one that will reshape society with rapid advances in robotics automation and AI. Expected to generate dramatic returns for society, the AI revolution is predicted to make a massive impact in 20 to 25 years, about half of a single work career.

It’s easy to envision a doomsday scenario about the displacement of workers in the face of this rapid advance. Will the coming AI disruptions leave millions unemployable?

I believe it will not — not if we plan ahead.

Doomsday Or Development?

Past innovations automated routine, menial work. Displaced workers could (and typically did) simply educate and re-skill themselves back into employability. In the past, they had the time to do it.

In contrast, AI’s looming threat is to replace high-level, judgment-based skill-sets, such as complex analysis, discretionary decision-making and even creative ideation. Robotics will replace many of the services and manufacturing positions. What kind of jobs will be left for people to do?

This is a pressing concern without clear answers, but doomsdayers neglect a crucial fact: Investments cannot capitalize on AI’s gains in the absence of human consumption. I believe AI will only be meaningful if humans are able to capture the benefits of AI technology.

The McKinsey Global Institute recently observed that the only way to realize the productivity dividends of AI will be to have people in place to capture them. Managing this transition will be a competitive imperative.

In other words, all jobs will not disappear — they will undergo a significant metamorphosis.

Past Economic Shifts Offer Hope

However unprecedented the pending revolution may be, studying the past is still reassuring and helpful. If we take the whole of human history as our dataset, it is apparent that, ignoring local dislocations and the resulting need to migrate, humanity has typically landed on its feet and moved forward.

For example, a little over two centuries ago, 90% of Americans lived and worked on farms. Today, only about 2% do. Yet, 88% of the population isn’t unemployed, they simply have new jobs.

That’s how large-scale transformation works. As past advances displaced workers, so too have they given rise to a new, previously unimagined class of employment. Hunter-gatherers became farmers. Farmers morphed into factory workers. As we peer into the future, it’s difficult to predict exactly who society’s workers will be, but the past forecasts that human employment will be alive and well.

Of course, one key challenge of the AI revolution is that workers will have far less time to retrain themselves. Previous economic shifts occurred slowly, over many generations; this one is likely to happen well before many of today’s workers retire. It will take deliberate forethought, planning and action to avoid a disastrous disruption.

I suggest a four-pronged strategy.

1. Identify Skills

To start training and upskilling the workforce, the first task will be to forecast the new wave of jobs and identify their corresponding skills. Once we do so, we can develop specific training curricula and socialize it. This process will have to be constant and flexible, as the skills needs will likely change every five to 10 years.

2. Retain Your Current Employees

As a workforce strategy, it’s clearly more efficient and fiscally responsible to retain and retrain your employees, rather than engage in large-scale layoffs and rehiring. Existing employees are already familiar with your company culture. They know your customers and have working dynamics that may have taken years to optimize. Except for dealing with poor performers, in my view, there’s no need to replace when retraining is a cheaper option.

3. Develop And Deploy Training

In the past, most workers had a single career in their lifetime. As automation accelerates, workers will require a new skills portfolio about once a decade. Predictive analytics technology can help pinpoint three things: employees in your business that are most likely to leave, those who can benefit most from being re-skilled and the likely impact that re-skilling programs will bring to your workforce overall.

Developing and deploying useful training takes years. Rather than simply throwing money at it, one should investigate the cause of every notable success and failure. I recommend measuring inputs, tracking outcomes, modeling different policies and closely following early adopters to learn and emulate best practices.

4. Reimagine Education

The children of tomorrow need to know how to both manage the advanced machines and systems that will surround them from childhood and how to harness the resulting insights. The current education curricula are not designed to deal with these needs, and time is running short.

I recommend that businesses involve themselves in assisting their source schools in shaping the curriculum, providing teaching assistance, funding teacher development programs, sending their key innovators into the classrooms and developing teacher sabbatical exchange programs. Technology firms should provide assistance in terms of free access to products and co-op programs in collaboration with their local colleges.

The challenge we face is dramatic, and it will require unconventional thinking and experimentation. The earlier and more aggressively we engage in a global discourse on this issue, the more likely we will develop coping mechanisms and avoid another rust-belt calamity.

This article first appeared in Forbes.

The post 4 Steps to Retraining Employees in the Age of A.I. appeared first on Visier Inc..

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In May 2016, wildfire broke out in Wood Buffalo Municipal District near the City of Fort McMurray, Alberta, Canada and became possibly the costliest disaster in Canadian history. As the fire grew to nearly 2,000 square miles (approximately 590,000 hectares) in size, more than 80,000 residents were forced to evacuate. The City of Edmonton responded to this unmatched crisis by putting “all hands on deck.”

Edmonton Fire Rescue Services sent firefighters and equipment to help fight the blaze.  Edmonton Transit, the Animal Care and Control Center, and other special services also assisted with the effort. In addition, our Emergency Support Response Team opened up a Reception Centre, which provided a range of services and supplies to nearly 25,000 evacuees.

As a steward of public funds, it’s critical that we stay on top of costs and use best practices for workforce cost management. With so many regular City workers putting in extra hours, sorting donations for evacuees and manning the evacuation centre, we knew there would be a spike in overtime for the month of May. We immediately looked at how we could track the overtime due to Wood Buffalo versus regular operational overtime in our people strategy platform, Visier.

Prior to the fire, we used Visier to give us an accurate picture of our overtime situation on a monthly basis. When the fire broke out, we started loading work order numbers along with our regular employee data to identify the overtime hours due to the Wood Buffalo wildfire response. This is the first time we’ve had an HR tool available to help us separate overtime due to a major event from overtime for regular operations.

Prior to having our workforce intelligence solution in place, gathering this kind of insight would have been very difficult. Our HR team would have needed to pull reports and then work through the data on spreadsheets. It would have been a time-consuming and error-prone process.

Whether employees signed up for shifts at the evacuation response center, the donation collection depots, or maintained municipal services, all City employees responded to help our neighbours through the crisis. We didn’t know how long this crisis would last and needed everyone to perform their best in order to properly support both the evacuees and the rest of the community. We are happy to have Visier available to help management understand the impact the Wood Buffalo wildfire relief had on our operations.

Municipal employees responded to the fire in Slave Lake in 2011 as well as the flooding in Calgary in 2013. As the capital city, we will be called on to help again when a large emergency response arises in the province. Now we have accessible data to predict the overtime hours that we would accrue so we can prepare for these costs. We will be better able to answer time-sensitive questions about the impact of overtime for each department and job role, and therefore better understand where we will be experiencing the greatest increase in costs.

The post Using HR Analytics for Workforce Cost Management [Case Study] appeared first on Visier Inc..

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