Over the last decade, there’s been a great deal of excitement about the possibilities of technology in training. All the “cool” HR professionals have been reciting the e-learning mantra.
In the mad rush to improve training through technology, the potential of technology to improve selection is often overlooked. The thing is, to truly maximize the quality of the workforce, employers need to make good selection decisions, as well as train. Just as e-learning has helped organizations train better, e-selection also offers companies tremendous value.
According to the forecasters, the Canadian economy is about to turn around, and companies will again embark on hiring sprees. The stakes are high. The difference among employees in terms of job performance is quite large. In the case of managerial and professional employees, a good rule of thumb is that the difference in performance between a top and a bottom employee is equivalent to an annual salary.
The challenge is to accurately identify the most promising candidates. This is not an easy task, particularly given that there is an abundance of displaced employees to choose from, and the most popular selection tool, a traditional interview, is extremely time consuming and a poor predictor of performance.
Luckily, many interesting technologies have emerged in recent years that can make selection more efficient and more accurate.
Screening
Selection processes are becoming more automated, and resumes can now be posted and screened online. Companies use this to effectively narrow down the list of applicants. Here’s how it works. Job candidates simply complete an electronic application to apply for a position. Responses are immediately transmitted to a database for processing and applicants are automatically screened for core requirements, such as minimum level of education or relevant experience.
Resumes can also be automatically evaluated in terms of typos and misspellings or “job hopping.” This is a good filter for weeding out those 15 per cent of candidates who are clearly unqualified, but have applied anyway because, “Hey, you just never know.”
Some of the latest technologies can automatically “look through” electronically-submitted cover letters and resumes and appropriately categorize applicants. This type of software examines certain aspects of writing, such as word patterns, frequency of word usage and choice of words. Such software can flag applicants that appear to exaggerate the truth, present misleading information, or seem otherwise suspicious. For example, building on its 25 years in statistical software, SAS is shortly releasing text-mining software capable of analyzing unstructured text and identifying meaningful trends. Although such software is relatively pricey, it can be valuable for larger companies.
Other companies offer software that helps screen out dishonest applicants by conducting a background check.
Some of these online screening tools are supplemented with personality profiles, and even tests of “general mental ability (GMA).” A well-designed personality profile can properly measure and match the right personality dimensions to the requirements of the job. For example, research has shown that personality dimensions such as extroversion and conscientiousness can predict performance of salespeople quite well, and demonstration of an agreeable disposition can be a useful predictor pf managerial performance.
GMA testing has also been shown to predict performance for certain types of jobs, particularly when hiring employees without previous experience in the position. GMA can also predict an applicant’s learning ability and trainability.
The use of this technology is currently popular in the United States, particularly in industries relying on entry-level positions and experiencing large rates of turnover. For several years now, companies, such as Blockbuster, Home Depot and Target, have been using technology to automatically screen large numbers of candidates and generate a shortlist.
Aside from a dramatic increase in the number of job applications being processed and a reduction in hiring time, these systems can generate other benefits. Some companies claim screening technology has helped decrease employee turnover by between 10 to 30 per cent by helping to establish a better fit between the candidate and the job.
Assessment
But what do you do if you need more precision in distinguishing between promising candidates and others? The situation is particularly difficult when it comes to assessing soft skills.
It is difficult to accurately measure the competencies that underlie these types of skills without actually seeing the person in action. An extensive study of various selection methods published in Psychological Bulletin, a well-respected academic journal, concludes work sample tests are among the best predictors of job performance. Thus, it is not surprising that some interesting developments are taking place in this area.
Video-based simulations have evolved, partly, from situational interviews, which have been shown to be valid predictors of performance, but are cumbersome to administer and to score. Simulations place job applicants in situations akin to those that they may face on the job. The computer automatically evaluates the level of each applicant’s skill from the choices the candidate makes, and generates an assessment report.
Just as a flight simulator is used to evaluate a pilot’s skill at flying in different weather conditions, computer-based simulations are being used to evaluate applicants’ soft skills, ranging from sales to managing a group of subordinates.
One such simulation assesses the selling skills of applicants in a B2B environment. Applicants are required to respond to a variety of situations that take place at different stages of the sales cycle. (For an example, see screen capture below.)
From an accuracy perspective, this assessment approach is as good as, or better than, any other including employment interviews or comparing previous work experience. Several independent studies that have examined the validity of video-based tests for predicting performance in a variety of jobs (including nursing assistants, dietary assistants and customer service workers) have recommended their use.
Computer simulations are also easier and less expensive to administer than comparable assessments. For example, a number of candidates can be assessed at one time, and the administrator doesn’t even have to be present during the assessment. The data is automatically processed and stored in a database.
Job applicants like simulations because the video-based tests have inherent face-validity when compared with other types of pre-employment tests that often appear to have little relevance to the job.
Finally, video simulations can provide a realistic job preview by exposing the candidates to the types of activities they will encounter on the job. This may speed up a new employee’s orientation to the job.
Not surprisingly, leading companies like UPS, First Union and Dow Chemical are among those using simulations to make hiring decisions.
Nothing is perfect, of course. The drawback of computer-based selection tools is that they typically require high speed computers with Internet access. Currently, some Canadian industries, such as retail, are not well equipped to handle this technology.
For those companies that do have the capability to accommodate this technology, the payoff from e-selection can be considerable. How considerable?
Researchers estimate that a typical increase in the output per hire from using better assessment tools is approximately $27,500 per year for a job of medium complexity. An HR manager who hires 35 people or so a year using a better selection tool improves the bottom line by $1 million. (What a perfect opportunity to ask for a raise, don’t you think?) And this does not even include the savings of streamlining the selection process.
Igor Kotlyar and Kim Ades are with Upward Motion Inc. Their company provides clients with technologies for assessment and training. Please address comments to [email protected].
In the mad rush to improve training through technology, the potential of technology to improve selection is often overlooked. The thing is, to truly maximize the quality of the workforce, employers need to make good selection decisions, as well as train. Just as e-learning has helped organizations train better, e-selection also offers companies tremendous value.
According to the forecasters, the Canadian economy is about to turn around, and companies will again embark on hiring sprees. The stakes are high. The difference among employees in terms of job performance is quite large. In the case of managerial and professional employees, a good rule of thumb is that the difference in performance between a top and a bottom employee is equivalent to an annual salary.
The challenge is to accurately identify the most promising candidates. This is not an easy task, particularly given that there is an abundance of displaced employees to choose from, and the most popular selection tool, a traditional interview, is extremely time consuming and a poor predictor of performance.
Luckily, many interesting technologies have emerged in recent years that can make selection more efficient and more accurate.
Screening
Selection processes are becoming more automated, and resumes can now be posted and screened online. Companies use this to effectively narrow down the list of applicants. Here’s how it works. Job candidates simply complete an electronic application to apply for a position. Responses are immediately transmitted to a database for processing and applicants are automatically screened for core requirements, such as minimum level of education or relevant experience.
Resumes can also be automatically evaluated in terms of typos and misspellings or “job hopping.” This is a good filter for weeding out those 15 per cent of candidates who are clearly unqualified, but have applied anyway because, “Hey, you just never know.”
Some of the latest technologies can automatically “look through” electronically-submitted cover letters and resumes and appropriately categorize applicants. This type of software examines certain aspects of writing, such as word patterns, frequency of word usage and choice of words. Such software can flag applicants that appear to exaggerate the truth, present misleading information, or seem otherwise suspicious. For example, building on its 25 years in statistical software, SAS is shortly releasing text-mining software capable of analyzing unstructured text and identifying meaningful trends. Although such software is relatively pricey, it can be valuable for larger companies.
Other companies offer software that helps screen out dishonest applicants by conducting a background check.
Some of these online screening tools are supplemented with personality profiles, and even tests of “general mental ability (GMA).” A well-designed personality profile can properly measure and match the right personality dimensions to the requirements of the job. For example, research has shown that personality dimensions such as extroversion and conscientiousness can predict performance of salespeople quite well, and demonstration of an agreeable disposition can be a useful predictor pf managerial performance.
GMA testing has also been shown to predict performance for certain types of jobs, particularly when hiring employees without previous experience in the position. GMA can also predict an applicant’s learning ability and trainability.
The use of this technology is currently popular in the United States, particularly in industries relying on entry-level positions and experiencing large rates of turnover. For several years now, companies, such as Blockbuster, Home Depot and Target, have been using technology to automatically screen large numbers of candidates and generate a shortlist.
Aside from a dramatic increase in the number of job applications being processed and a reduction in hiring time, these systems can generate other benefits. Some companies claim screening technology has helped decrease employee turnover by between 10 to 30 per cent by helping to establish a better fit between the candidate and the job.
Assessment
But what do you do if you need more precision in distinguishing between promising candidates and others? The situation is particularly difficult when it comes to assessing soft skills.
It is difficult to accurately measure the competencies that underlie these types of skills without actually seeing the person in action. An extensive study of various selection methods published in Psychological Bulletin, a well-respected academic journal, concludes work sample tests are among the best predictors of job performance. Thus, it is not surprising that some interesting developments are taking place in this area.
Video-based simulations have evolved, partly, from situational interviews, which have been shown to be valid predictors of performance, but are cumbersome to administer and to score. Simulations place job applicants in situations akin to those that they may face on the job. The computer automatically evaluates the level of each applicant’s skill from the choices the candidate makes, and generates an assessment report.
Just as a flight simulator is used to evaluate a pilot’s skill at flying in different weather conditions, computer-based simulations are being used to evaluate applicants’ soft skills, ranging from sales to managing a group of subordinates.
One such simulation assesses the selling skills of applicants in a B2B environment. Applicants are required to respond to a variety of situations that take place at different stages of the sales cycle. (For an example, see screen capture below.)
From an accuracy perspective, this assessment approach is as good as, or better than, any other including employment interviews or comparing previous work experience. Several independent studies that have examined the validity of video-based tests for predicting performance in a variety of jobs (including nursing assistants, dietary assistants and customer service workers) have recommended their use.
Computer simulations are also easier and less expensive to administer than comparable assessments. For example, a number of candidates can be assessed at one time, and the administrator doesn’t even have to be present during the assessment. The data is automatically processed and stored in a database.
Job applicants like simulations because the video-based tests have inherent face-validity when compared with other types of pre-employment tests that often appear to have little relevance to the job.
Finally, video simulations can provide a realistic job preview by exposing the candidates to the types of activities they will encounter on the job. This may speed up a new employee’s orientation to the job.
Not surprisingly, leading companies like UPS, First Union and Dow Chemical are among those using simulations to make hiring decisions.
Nothing is perfect, of course. The drawback of computer-based selection tools is that they typically require high speed computers with Internet access. Currently, some Canadian industries, such as retail, are not well equipped to handle this technology.
For those companies that do have the capability to accommodate this technology, the payoff from e-selection can be considerable. How considerable?
Researchers estimate that a typical increase in the output per hire from using better assessment tools is approximately $27,500 per year for a job of medium complexity. An HR manager who hires 35 people or so a year using a better selection tool improves the bottom line by $1 million. (What a perfect opportunity to ask for a raise, don’t you think?) And this does not even include the savings of streamlining the selection process.
Igor Kotlyar and Kim Ades are with Upward Motion Inc. Their company provides clients with technologies for assessment and training. Please address comments to [email protected].
