Archive for the ‘HR Analytics’ Category

March 28, 2011

Alchemy and Algorithms – Recruiting by Ego or Evidence

Alchemy attempts to take common materials and transform them into something rare and valuable. I don’t think anyone has succeeded in this endeavor to date.

Algorithms Can Be Derived from HR Analytics

Unlike alchemy, algorithms can turn raw goods into gold. The raw goods can be candidate evaluation data and the gold is on-the-job performance. However, many recruiters have not invested in the data collection and analysis required to create an algorithm. As such, they make decisions based upon anecdote and conjecture.

Stock traders want to predict future prices and values of individual companies and broader indices. Recruiters want to predict future behaviors and on-the-job results of candidates. Algorithms are used by the best-in-class of both of these disciplines. And the results they achieve are documented by superior outcomes.

The reason both of these professions use algorithms is to identify meaningful relationships among complex data sets.

Variables that drive company performance and market fluctuations are complex. And, there is likely no doubt in your mind that variables which drive people’s performance are complex, very complex. In fact you might assert people are unpredictable. If that was really the case the workplace would be chaos. And that is just not true. There are some predictable elements.

Algorithms are special equations, expressly for the purpose of teasing out insights and conclusions from complexity.

When used well, the outcome of algorithms increases the probability of making a correct decision more often than not. An algorithm based upon pre-employment testing brings a sophisticated level of HR Analytics that can dramatically improve your quality of hire.

Algorithms were used to determine the premium for your auto insurance, your credit score, the offer you received for a vacation package, and the books recommended for you in on-line shopping. In each case two or more large data sets were analyzed to determine the nature and significance of relationship that exist between and among the variables.

Big Bucks for Equations.

In a current algorithm competition $3 million is being offered for the equation that takes large data sets of health care and lifestyle information and calculates the likelihood of an individual being hospitalized sometime in the future. The underlying assumptions are two-fold. You could be charged a higher insurance premium based upon your probable path to the hospital, or you could be given a specific preventative intervention to reduce or eliminate the necessity of being admitted for medical care.

Why a competition? The analysis and mental energy required to derive the equation is significant. Asking one individual to undertake the work may take a long time. A competition can attract the intellectually curious and competitively driven statisticians. Having a solution sooner than later is valuable.

How much would your organization pay for an algorithm that predicted your customer’s behavior? Or possibly a more accurate question is how much has your organization already paid in an effort to better understand and predict your customer’s behavior. Go ask your chief marketing officer.

Ego or Evidence?

Best-in-class recruiting professionals use algorithms. (We can introduce you to some of them.) Each hiring decision is supported with evidence. But, just like the challenge in the competition, developing algorithms require thoughtful effort. When I describe the process of developing a recruiting algorithm, I get two reactions. One says,”That seems like a lot of work.” The other states. “That seems like it can add significant value to our process.”

Algorithms are derived from analyzing large data sets. Three data sets are required for transforming recruiting raw goods into job performance gold:

Candidate Evaluation data – pre-employment assessment
Behavior/Competency Evaluation data – supervisor ratings
Productivity Evaluation data – objective metrics of on-the-job performance

Recruiting professionals working at the leading edge of candidate evaluation capture 200 to 300 data points from candidate evaluation. The data encompasses work history, work style and work samples.

Similarly, job performance, as defined by 100 to 200 data points from ratings and metrics for each individual provides a robust description of the complexity inherent in any job and the company culture in which it occurs.

When a recruiting professional embarks on capturing this level of data on their staffing process and its outcome as job performance they have the raw goods for the algorithm that predicts the future and answers the essential question – which candidates are more likely to be successful on the job. Working with this type of information delviers a very powerful recruiter experience, adding both efficiency and effectiveness.

Differentiated Workforce

And, that ability to differentiate among candidates is competitive advantage. Michael Porter the strategy guru at Harvard states competitive advantage comes from business processes which are difficult to replicate. In their book The Differentiated Workforce, authors Beatty, Becker and Huselid assert competitive differentiation comes from efforts that align jobs with strategic capabilities. (see page 10).

Using an off-the-shelf assessment, and generalized validity is defined as a ‘Me Too” strategy, one that is easy to replicate. An algorithm which predicts candidate performance in your organization is impossible to replicate. Call us to explore what it might take to transform your candidate experience into competitive advantage and a strategic business driver.

It’s not alchemy, it’s algorithms. And they really do turn raw goods into gold. Employees who perform at gold star levels.

February 10, 2011

Do You Have A Talent-matician?

Kevin Wheeler wrote a great article on ERE asking about selection science and measurement. His is suggesting staffing professionals adopt better methods for candidate evaluation or assessment and make more effective use of HR analytics to link candidate evaluation data to business outcomes.

Here are a few questions around measurement discipline, the answers to which may be revealing.

Ask your CFO – “How much has been invested in the data capture and analysis system you use to report EBITA?”
Ask your EVP of Sales – “How much has been invested in the data capture and analysis system you use to report daily sales performance?”
Ask your EVP of Manufacturing ; “How much has been invested in the data capture and analysis system you use to calculate process yield?”
Then ask your EVP of HR (self) – “How much has been invested in the data capture and analysis system you use to create a differentiated work force?”

In every case, for Fortune 1000 companies, the answer to the first three will be hundreds of thousands and in some cases millions of dollars. Unfortunately the answer to #4 typically pales by comparison. Why?

I have never sat with an executive who stated their organization was just like their competition. In fact, great pride is expressed in how their people, their products, their services are different than others. The work that true talent-maticians (I just invented that) do is using HR analyitics in quantifying, to the degree possible, the human variables that contribute to those differences. That requires, rigor, discipline, experiment design, and time.

Michael Porter of Harvard suggests competitive advantage comes from business processes which are difficult to copy. Authors Becker, Beatty, Huselid, in The Differentiated Workforce present a similar framework for evaluating HR practices that put forth a ‘Me Too’ or a Differentiated outcome. An example of this is the use of off-the-shelf assessments without local validation. By default the user states, we are willing to use a measurement tool developed for and by someone else and calibrated by another organization to provide data on our talent decisions. Sounds like a Me Too tactic. One path to a differentiated workforce is at least conducting a validation analysis on how the measurement tool (pre-employment test) is adding value to your decision process. The underlying premise is that a good assessment provides a degree of better data and therefore, better decisions. With in-house validation, you document the relationship between assessment results and business outcomes.

Without an in-house validation, the test is not calibrated to performance in your organization and outcomes are anecdotal. The practice that gives assessment a poor reputation is poor implementation.

In an earlier work by the three authors above The Workforce Scorecard, they document those organization hiring a higher percentage of employees with validated evaluation methods achieve higher levels of financial performance. Aon and SHRM conducted a significant piece of research in the mid 1990s that included a glimpse at staffing process outcome (out of print but avaiable from the research dept). Survey participants stated the most lacking qualities in new hires were defined as work style, and basic reasoning. Those traits or attributes can be objectively evaluated with a variety of pre-employment tests. Companies stating they were most satisfied with staffing process outcomes were using the most comprehensive candidate evaluation methods.

Companies hire engineers to solve complex measurement problems.
Companies hire actuaries to solve complex measurement problems.
Companies hire statisticians to solve complex measurement problems.
Companies that know their competitive advantage comes from their people hire industrial organizational psychologist to solve complex measurement problems in staffing. These folks are the talent-maticians.

Even if you do not measure variables that provide insight to performance potential, performance variation exists. In fact you hired your best performer and your worst performer with the same evaluation process. In manufacturing terms that is known as performance variation and is marked by upper and lower limits. You see, staffing is a business process with a yield to measure and manage. To do that requires data capture and analysis.

However, enter another piece of data. It has been known for some time that a structured interview extracts better candidate evaluation data than an unstructured interview. In a survey on Use of Objective Candidate Evaluation Methods I conducted with SHRM (write for a copy), very fascinating evidence of interview practices emerged. Only 55% of respondents stated they use behavioral interviews with questions written in advance (an intentional discovery process). When asked if the interviews were supported with behaviorally anchored rating scales (a method to discern an effective response from an ineffective response), only 24% of respondents stated this practice was used. Staffing practitioners are largely ignoring known practices which at the simplest level produce better outcomes. Implementing assessments requires the same rigor the CFO expects from data capture and analysis in financial matters.

In some jobs, learning more about what factors contribute to retention can add signnficant value. However,most companies do not even measure and track the cost of early turnover. In a survey on Staffing Waste I conducted with SHRM (write for a summary), only 8% of 636 respondents stated they track and report the costs of what I call False Starts – new hire turnover that occurs in less than 120 days. The analogy would be a head of manufacturing that does not measure defects and scrap rates. Manufacturing is held accountable for managing the yield of that process. In my paper Staffing Waste: Identify it, Measure it, Reduce it, a range of examples for applying measuremen- based process improvement to staffing is offered. You can read it here

Yes Kevin, the future of staffing practices will include more measurement, more science, more accountability for understanding and managing process yield. There are exceptional methods to evaluate candidate-job fit. It can be measured, it can be analyzed and it can contribute to the bottom line. However, the practice leaders are already out there, doing the work right now.

For one example kook at the 2010 ERE Award winner KeyBank. They reduced staffing waste in one position by over $1.7 million in one year by bringing science and measurement rigor into their staffing process. They were able to add objective candidate evaluation in a manner that measured candidate-job fit. The retention and gains in a range of job performance metrics are impressive.

We have many more examples of how talent-maticians drive economic impact from staffing process improvement. To explore the scope of opportunity you might have, see our ROI calculators.Call me. We can discuss your opportunity.

Posted by: Joseph P. Murphy | February 10th, 2011
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, Tags: assessment employee selection HR Analytics pre-employment assessment pre-employment testing selection science staffing waste | Posted in General, HR Analytics, I/O Psychology, Surveys

January 30, 2011

Do We Need Internal Recruiting? Ask the CFO.

Kevin Wheeler posted an article on ERE that got the recruiting community fired up. He asked, “Do we need Internal Recruting at all?” His premise seems to rest with effectiveness, accountability and differentiation that a recruiting function may or may not deliver.

With 32 comments as of this post, it ranks near the top of the charts for getting folks riled up.

Here are my two cents, with a few more details than what I posted on ERE.

The dialogue is all good. It may be like the question about cars, is it better to buy or lease? And the answer is: It depends.

Kevin’s main point may really be rooted in economics. When an internal team has the same mandate to measure, track and report economic impact that an external provider does, there is most likely performance parity.

Unfortunately, the issue lies with the fact that many CFOs and CEOs do not hold internal recruiting teams accountable to document contribution and deliver continuous staffing process improvement. And without a mandate for economic accountability, the accounting infrastructure to document contribution is often lacking. A vice president of sales or manufacturing would never be allowed to operate with the poor economic reporting and accounting infrastructure that is deployed for the business process of recruiting. As such, it is common for internal recruiting teams to use ATS based reporting, thus relying on activity based measures instead of economic measures.

Henry David Thoreau gives us words to ponder for this situation: “It is not enough to be busy, so are the ants. The question is, what are we busy about?”

One gauge we use to explore the economic accountability of a recruiting team is how literate they are about job-specific performance metrics and how quickly they can access data sets of performance metrics. Ask a staffing professional, internal or external, if they measure and report on the cost of time to proficiency (total investment from sourcing to self-sufficient performance) for the position with the highest hiring volume. Ask who owns the budget for staffing waste. The answers to those questions reveal a great deal about the accountability expectations set by the CFO and CEO for recruiting.

Reporting on days to fill, requisitions open, requisitions per recruiter, and opinion-based quality of hire while good to know are a bit like busy ant metrics. Recruiters with economic accountability use HR analytics to document and report reductions in staffing waste and rework, increased yield in new hire productivity, reduced time to proficiency, increases in job family average performance metrics and the like.

From my experience, corporate resources flow to those who build a good business case and then document return on investment. Outside providers have to do this to earn repeat business. The best internal providers do so as well. Here is an example of how Key Bank documented high ROI from using pre-employment testing as a form of measurement rigor to reduce staffing waste.

Posted by: Joseph P. Murphy | January 30th, 2011
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, Tags: HR Analytics pre-employment testing Quality of Hire recruiting ROI staffing process improvement | Posted in General, HR Analytics, Recruiter Experience

December 2, 2010

Are You a Passive or Active Recruiter?

So much digital dust has been sprinkled over the candidate side of this question. But, as a recruiter, where do you reside?

Candidates who are not engaged in looking for a career change, and who wait for an e-mail or phone call to consider a job are often called passive. Using that same logic, are recruiters who use post and hope, and wait for candidates to fill up their applicant tracking system passive recruiters? That might be considered an unfair or inappropriately simple definition for passive recruiters.

What criterion transforms a candidate into the active camp?

Applying for one job? Three or more jobs?
One job in the last five years. Five jobs in the last year?
How about those candidates who develop a spray and pray resume distribution machine, ah yes, those are truly active candidates.
How about creating a profile on LinkedIn or other social media? Does investing energy to be visible to digital detectives constitute active?
How about candidates who set up a job agent to alert them of the ideal opportunity? Does that count as active? Or is that really passive, waiting and hoping the ideal job miraculously shows up in their in-box?

I offer a few ideas for consideration on the topic of passive recruiters.

Passive recruiters:
Rely on resumes and social media profiles to screen candidates
Only use the demographic profile and contact information section of their ATS/CRM
Measure sourcing effectiveness by candidate volume/traffic
Begin an interview without written, competency based questions
Use fundamentally the same methods of candidate evaluation for high volume hiring and one-off searches
Worry about requisition load and back-log

On the other hand, active recruiters engage in very different activities when it comes to managing the business process called staffing. Active recruiters understand the staffing process is ripe with metrics that document yield, performance variation, and contribution to the business plan. Active recruiters partner with finance, accounting and database specialists to measure, monitor, and improve the yield or results from their business process. Active recruiters document the return on investment from their use of corporate resources – people and dollars.

Active recruiters:
Perform a Pareto Analysis of their current and future hiring requirements to appropriately allocate resources to the demand
Develop Realistic Job Previews for their highest volume jobs
Implement the weighted-scoring candidate screening questions in their ATS
Use objective candidate evaluation methods such as simulations and assessments to get better candidate data and quantify applicant qualifications
Deployed some form of objective pre-employment assessment for jobs with over 100 incumbents
Conducted in-house validation analysis for all jobs with more than 100 incumbents
Calculated (not estimated) the cost of on-boarding, or investment in time to proficiency for the one to three jobs with the highest volume of hiring in their company
Documented the cost of staffing waste and re-work from 90 day turnover for key positions with early retention challenges
Conducted a new hire performance variation analysis to document trends and outcomes in quality of hire measures
Developed written interview questions for each competency they evaluate
Deployed behaviorally anchored rating scales for evaluating candidate interview responses
Document quality of hire and yield by source from social media

The list goes on.

Each of these items represents a effective practice for staffing process improvement, supported with research. Active recruiters go beyond opinion and anecdote, they want evidence, documentation of impact and favorable trends on their metrics dashboards.

And remember the words of Henry David Thoreau :
“It is not enough to be busy, so are the ants. The question is, what are we busy about?”

If you would like to learn more about optimizing your level of active recruiting, give us a call.

Posted by: Joseph P. Murphy | December 2nd, 2010
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, Tags: assessment Quality of Hire ROI Simulations staffing process improvement | Posted in HR Analytics, Recruiter Experience

November 15, 2010

All Referrals Are Not Created Equal – Quality of Hire = Quality of Referral

John Sullivan points out in his ERE post on referral programs that numbers are available for those who want to invest in measurement discipline and operate at the level of evidence versus opinion. There is plenty of data that suggests referrals work and make sound business sense. And, just like the issue of diversity, there are other dimensions of referral process effectiveness that can be quantified.

In a hiring environment using pre-employment assessment, it is possible to examine the relationship between quality of hire and quality of referral. In one client analysis, we were able to document that individuals scoring higher on the assessment tended to refer individuals who also performed well. And as one might also conclude, those who scored less well referred candidates with similar performance results. It is important to create referral behaviors from those more likely to generate high value candidates.

The anomaly, and there are always some, was the cluster of individuals with modest assessment results but with a high level of referring activity. There was no pattern to the quality of the candidates they put forth. We called these the ambassadors. They are just out piping a ‘follow me tune’ attracting all comers. Even a blind squirrel finds an acorn. It is important not to get referrals for referrals sake.

As such, using HR Analytics it is possible to target referral behaviors more selectively. But first, you need better candidate data.

Posted by: Joseph P. Murphy | November 15th, 2010
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, Tags: HR Analytics pre-employment assessment Quality of Hire | Posted in HR Analytics

November 9, 2010

Simulations and Selection Science: Interview with Mike Hudy, Ph.D. Part Two

In Part One of the Interview with Mike Hudy, he discussed the demands and opportunities I/O Psychologist face in developing simulation for pre-employment testing. In this conclusion, Mike offers a few suggestions on how to determine if a simulation may be appropriate for staffing process improvement in your organization.

What considerations should a company examine in deciding if a simulation would be appropriate for one of their jobs?

There are several factors to consider when examining if a simulation makes sense. If you have jobs with more than 100 incumbents, building a business case for simulations is typically pretty easy. Another factor is hiring volume. If you will hire more than 100 people into the same job in a year, simulations can make a significant contribution.

An additional factor would be the complexity of the job itself. This variable is often under-valued prior to a thorough job analysis. The more complex the job, the more complex the demands are on the pre-employment assessment.

The last and a very important factor to consider in the use of simulations is the candidate experience. As general rule, candidates find simulations engaging, a more valuable way of presenting their capabilities and companies who use simulations stand out in a positive way from other places the candidate may be applying.

In short, simulations such as the Virtual Job Tryout add selection science value across a range of factors that have a positive impact on staffing process improvement.

Part One

Posted by: Joseph P. Murphy | November 9th, 2010
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, Tags: HR Analytics ROI selection science Simulations staffing process improvement Virtual Job Tryout | Posted in HR Analytics, I/O Psychology

November 4, 2010

Simulations and Selection Science: Interview with Mike Hudy, Ph.D. Part One

Mike Hudy is an Industrial/Organizational (I/O) psychologist and principal of Shaker Consulting Group. He began designing custom simulations for pre-employment testing in 1997. His work is marked by innovation in developing high-fidelity, on-line work samples and interactive evaluation experiences that expand the science and art of the profession.

In what ways have simulations for pre-employment assessments changed the way I/O psychologists think about measurement science for the hiring process?

Psychologists have to apply traditional psychometrics to a more complex playing field. In developing a simulation you have to capture core elements of the job in a manner that is not overly complex yet still accounts for traditional psychometric principles. Now I/O psychologists have an opportunity and challenge to be better at balancing art with selection science.

Tell me more about the Art.

The art is the process through which we gain an understanding of a job and devise a way to represent or recreate aspects of the job in an internet delivered simulation. Simulations collect a work sample through an informative and interactive candidate experience. This method captures a level of data a traditional Likert scale or multiple-choice assessment can never achieve. The art is to capture some of the complexity without making it overly intricate. The candidate needs to be able to proceed with minimal instruction to complete the exercises. And the exercise needs to be clearly job relevant.

Is that where the power of face validity comes into play?

Yes, it is the goal is to invite the candidate to step into the role and perform elements of job which measure attributes critical for success and do job. We create and deliver candidate evaluation in a way that the individual does not feel like they are being tested. They know what is going on, however,the link to the job is so strong and clear. Feedback we get from candidates strongly suggests they appreciate being afforded the opportunity to complete the Virtual Job Tryout. They come away with a better understanding of the career opportunity they are considering. Exposure to the role through well balanced realistic job preview and concrete elements of job demands puts the candidate in better position to decide if the job is right for them. When we accomplish that, we know the art has achieved its purpose.

The psychometric challenge is to still get good reliable measurement of the construct you are trying to tap into without introducing too much noise into the exercise. What I mean by that is simulations can introduce many more moving parts into the measurement experience. With that the risk is the moving parts or elements of the simulation could have an unintended impact on what it is you are actually trying to measure.

Can you give me an example of this?

A good example is we developed simulations for two different call center jobs. One of them more closely resembled the actual problem solving on the job. It simulated searching for, finding and using information to solve problems by looking for information in a multi-layered data base.

The second problem solving simulation was much simpler. It eliminated the need to search for and find information and dealt exclusively with the ability to use technical information to address customer issue and resolve problems.

While the first simulation more closely resembled the actual job, we achieved better results predicting on-the-job performance with the simpler, second simulation.

By introducing the searching and identification task, it became a distracter and we limited our precision in assessing the actual problem solving ability.

How does that difference in complexity impact the way the candidate responds?

Candidates appreciate engaging, interesting and interactive exercises. Not all applicants appreciate increased complexity in their candidate experience. And, they let us know about it in the feedback.

So, how do you determine the level of complexity that is appropriate?

That is the intersection of Art and Science. The key is to constantly take off your I/O hat and view it from the candidate’s perspective, through the test takers eyes. At Shaker we do this through defined roles in our project teams. It includes peer review, end-user advocate review and then a significant population of incumbents during the validation phase. We learn more from each perspective and refine the exercises. In developing a Virtual Job Tryout, at least four I/O psychologists will critically evaluate the experience through the eyes of the candidate. Our programming team has over 20 years of experience designing graphically rich user interfaces and technology based training. Each layer of feedback impacts the design. Ultimately, the data from our HR analytics will tell us if we have it right or not.

In what ways do simulations increase the power of the selection science?

Human behavior is complex. What defines success in any given job is complex. Simulations allow us to measure a range of capabilities that do not lend themselves to be readily measured with traditional evaluation tools. For example, let’s consider multi-tasking. That is the ability to split attention between numerous competing tasks.

Measures such as personality, cognitive ability, and biodata are not able to accurately assess this construct. Thus we developed a multi-tasking simulation that places candidates into situations where they must divide their attention between a variety of tasks that simultaneously compete for their attention. Individuals who perform well in this exercise perform better in environments that truly demand those skills. In call center agents, proficiency in this construct correlates to more efficient after call work and better handle times.

With a simulation we are able to capture more robust work samples such as speed accuracy, latency of response, navigation accuracy, and learning from repetition in one exercise. Traditional and static measures such as personality and critical thinking are just not able to zero in on the subtle complexities of certain job performance domains.

Part Two

Posted by: Joseph P. Murphy | November 4th, 2010
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, Tags: pre-employment assessment realistic job preview selection science Simulations Virtual Job Tryout | Posted in HR Analytics, I/O Psychology

September 30, 2010

Social Media and Quality of Candidate | Candidate Competencies Vary by Source (Part 2)

A few months ago, I posted a blog on social media and quality of candidate. In the post, I suggested that we need to use HR analytics to evaluate this source of candidates not only by the volume of candidates generated but also by the quality of candidates produced. We conducted some preliminary analysis using assessment scores from the client’s Virtual Job Tryout and candidate conversion rate (what percentage of candidates that actually hired from a source) as quality of candidate measures. Results were somewhat mixed, but suggested that social media was generating a quality of candidate that was less than other sources used by the organization (e.g., referrals, job boards, etc.).

Candidate hiring rate varies by social media source

Well, we dug a little deeper into this data and a very interesting picture emerged. When we looked at the data by the various social media sites used by recruiters, two surfaced as being particularly effective: LinkedIn and Facebook. Candidates sourced via LinkedIn performed much better on the pre-employment assessment than candidates sourced through other channels. In addition, these candidates were hired at a higher rate than the typical candidate. This pattern held true for Facebook as well, but the results were not as impressive.

Candidate quality varies by social media source

We also compared pre-employment assessment results for candidates surfaced from LinkedIn versus Facebook and found some differences that at first glance seem to make sense. Candidates sourced through LinkedIn performed better on professionally oriented competencies such as Leads Courageously, Develops Others, and Achieves Results. Conversely, candidates sourced via Facebook performed better on more socially oriented competencies such as Customer Focus and Works Well with Others. Source can impact quality of hire.

While we have only scratched the surface here, these results from detailed HR analytics show that there is great promise and potential value to evaluating social media, as well as other recruiting sources, on the quality of its yield. Further, the data suggests that different social media channels generate different types of candidates with unique competencies and characteristics. Recruiters can use this kind of information to drive more strategic sourcing efforts by placing their bets on the channels that are best aligned with the type of candidate they’re looking to source.

Part 1

Posted by: Mike Hudy | September 30th, 2010
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, Tags: HR Analytics pre-employment assessment Quality of Hire social media Virtual Job Tryout | Posted in Client Case Studies, HR Analytics

September 29, 2010

Intuition or Intelligence: How Do You Hire?

Talent Intelligence was a big theme at TaleoWorld 2010. Taleo CEO Michael Gregoire, in his opening remarks stated 47% of new placements into management positions fail. I am not sure where that statistic came from, but it does not speak well about how companies are making decisions to hire or promote individuals. It makes me ask: Is the hiring decision based upon intuition or intelligence?

Where else in business would a 47% failure rate be tolerated? What Mr. Gregoire is referring to here is one form of staffing waste. This abysmal success rate seems to indicate a strong need for talent intelligence. Better candidate data for making more accurate hiring decisions.

Getting useful, meaningful data is the central challenge. Hiring managers and recruiters, while well intended, often place disproportionally high value on candidate data that is either not related to job performance or even worse, negatively related to job performance. And, one of the more common areas where we see this is the value placed on specific job experiences that while intuitively seemed to make sense, the evidence from HR analytics proved othewise. Here are a few examples. Previous cash handling experience negatively related to cash drawer accuracy, prior food service and hospitality experience negatively related to success in a food and beverage management position, previous sales experience with a competitor negatively related to sales success.

Thoughtful people in successful companies establish these screening criteria. However, in the majority of cases these criteria are assumptions. Assumptions that are never tested or proven. By not conducting the appropriate HR analytics, decisions get made based upon ego, not evidence. This is allowed because of the common and accepted assertion from recruiters and hiring managers: “I am a good judge of talent.” With a 47% failure rate, it would seem prudent to do some analysis. Just better than a coin toss does not seem like good odds for a critical and expensive business decision.

Employee selection is a process. The yield of the process can be measured and improved. Candidate evaluation with pre-employment assessments can be conducted in a manner that produces evidence in the form of data. This data can support HR analytics which in turn provides guidance to improve the objectivity and effectiveness of the hiring decision. If you are a Taleo user and want to make your ACE work better, we can help.

Check out a few of our case studies to see how HR analytics and pre-employment testing validation analysis have made a measurable difference in the yield of a business process called staffing. We can help you make the transition from ego to evidence, from talent intuition to talent intelligence.

Posted by: Joseph P. Murphy | September 29th, 2010
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, Tags: employee selection HR Analytics pre-employment assessment pre-employment testing staffing waste | Posted in Client Case Studies, Conferences, HR Analytics

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