Success-Based Matching

I N S I G HT R E P O RT

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Fact: as baby boomers retire there are far fewer people moving in to take their place - it’s projected that between 2000 and 2050, the number will only increase to 192 million, or a 36% growth rate.

T H E WA R F O R TA L E N T I S H E AT I N G U P

D O YO U ACTUALLY HAVE WHAT YO U N E E D TO WI N?

Organizations are loading up on HR technology to try to separate themselves from the pack. Many claim that advanced technology like Artificial Intelligence is going to completely transform how HR is done, and for the better – but how true is that? Let’s explore.

By Jamie Schneiderman - CEO and Founder of Career Spark

Based on numbers from the Bureau of Labor Statistics, from 1950 to 2000 the labor force grew by 127%, from 62 million to 141 million. However, as baby boomers retire there are far fewer people moving in to take their place - it’s projected that between 2000 and 2050, the number will only increase to 192 million, or a 36% growth rate.

Although the talent shortage is a real issue, it turns out that it’s not the biggest issue facing companies. Despite billions of dollars invested, there has been NO improvement in tenure or turnover in over 30 years.

At the very core of that issue is one simple fact: 70% of people are in the wrong jobs! Yes, you read that right. Just one example of the research that supports this is from a recent Gallup study that found that 70% of Americans and 85% of global workers are disengaged with their job. This problem affects over 125M people in North America alone and causes nearly $2 trillion in drag on the economy every year! Needless to say, what we’re talking about is an epidemic that amounts to the greatest business problem that exists today. So this begs the questions – what’s being done about it and why haven’t we fixed it yet?

With the decline in the growth of the labor force it has become more and more difficult to find talent. So, companies have invested significantly in online search capabilities to access pools of global talent as well as on internal tools to manage the flood of volume that comes with it. While the focus on accessing more talent continues to deliver incremental returns, the key issue we should be asking is whether it’s about finding MORE talent or finding the RIGHT talent?

More talent or the RIGHT talent?

The real problem is that we aren’t getting the RIGHT talent.

36%

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Before we get into how we got here and what’s being done (or not) about it, let’s pause and look at the extent of the carnage created by this issue. $2 trillion of inefficiency that directly impacts 125 million people in the wrong jobs (plus their families and their companies) is almost too large a number for most to comprehend.

However, the realities that make up that number are happening every day in every organization. The symptoms of this epidemic reveal themselves in a variety of very real pain points for both employers and their people, making people planning difficult at best and, at worst, a disastrous waste of time and money:

The Bureau of Labor Statistics reported that 45% of new college graduates stayed with a company for less than two years, and by the age of 35, 25% of Millennials will have worked at least five different jobs.

Talent Management and HR reports that to replace entry-level employees it costs 30% to 50% of their salary, to replace mid-level employees it costs 150% of their salary, and to replace high-level or specialized employees it costs 400% of their salary.

Often, people in the wrong jobs at your company eventually leave or are let go. As costly as this turnover can be for a company, we’ve all seen that sometimes having the wrong people stay in a job that isn’t right for them is even worse. The toxic effects of even one negative employee can be far-reaching and even more costly.

A 2013 CareerBuilder survey done on 6,000 hiring managers and HR professionals discovered that 27% of U.S. employers, who had employed a ‘bad apple’, claimed that one bad hire eventually cost their business more than $50,000. Without a doubt the majority of businesses have more than just one bad employee in their ranks.

H I G H T U R N OV E R R AT E S

A D E C R E A S E I N P R O D U C T I V I T Y

Wait, the issue is how big?

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Glassdoor reports that there is a significant lack of diversity in the hiring process. In fact, 57% of workers feel their company needs to do more to increase diversity, 41% don’t feel their executive team is diverse enough, and 48% do not know of any initiatives their company has in place to increase diversity. Why such a lack of diversity? One answer is that companies often depend too much on flawed human judgment during the hiring process. Despite the access to a wide range of technology targeted at removing bias from the decision making process, human-resources departments still have not changed much from the analog days. This tendency to rely on human judgement (i.e. opinions and bias) can be particularly pernicious when it comes to race, as a landmark 2003 study showed.

All the aforementioned items impact a company’s reputation and culture. It can be difficult to attract and hire the right new recruits when the word on the street about a company is negative. The Internet age has given everyone the ability to share their thoughts, opinions and feedback about the companies they work for, as well as their experiences throughout the interviewing and hiring stages, instantly and to a massive online audience. Glassdoor, for example founded in 2007 quickly became “Yelp” for employers, giving job seekers an easy and informative way to check out a business when considering applying to or accepting an offer from a company. A recent Glassdoor site survey found that 96% of today’s candidates look for reviews before accepting a job offer and 95% are influenced by reviews and ratings from internal employees. Unfortunately, as we all know, online reviews often skew negative, leaving businesses in an even more critical position of constantly finding ways to manage and improve the reputation of their brand internally and online.

The result is a vicious cycle of managing the symptoms instead of addressing the cause. Bringing in the wrong people in the first place creates significant harm to the business itself, as employees who are mismatched to jobs, vent their frustrations live or online to their peers, ultimately affecting the reputation of the employer brand, limiting the ability to recruit the right new talent, and the domino effect continues.

As mentioned above, 70% of American workers and 85% of global workers are not engaged in their job. Although engagement has become such a major priority for businesses who recognize how important it is for the success of their business - according to Gallup, employee engagement on an international level is only at 13% and 32% in the US and that number hasn’t budged in years! These numbers haven’t improved because at the core of the issue is the fact that 70% of people are still in jobs that they are not suited for, and the engagement crisis has become a major consequence that can’t be easily aided.

L AC K O F D I V E R S I T Y

N E G AT I V E E M P L OY E R B R A N D

L O W E R E M P L OY E E E N G AG E M E N T

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When a position needs to be filled, HR professionals are expected to find the perfect person to fill it. Ideally, this is the best person in terms of experience, education, how they fit with company culture, and their potential and passion and willingness to learn. The 3 main tools most HR professionals have available to them to accomplish this task are: i) A job description; ii) a resume; and iii) interview(s). The question regarding all of them is how do we know if we’re doing it right? Do we have the right description? What are we looking for in a resume? How do we use an interview to focus on the right things?

Unfortunately, there are problems with the current hiring process that get in the way of recruiting the RIGHT candidate or recognizing the RIGHT talent already working for you. Unlike other business decisions, people decisions are typically made based on guesswork, opinions and unfortunately, bias. Even when data is used objectively, it’s usually the wrong data or at least an incomplete picture. This is true for every part of the employee lifecycle from reviewing resumes, to conducting the interview process to making decisions for career path and building teams.

When an employer is facing a stack of resumes, they have to narrow down the choices. Glassdoor reports that corporate jobs received an average of 250 applicants per job posting. It’s no surprise that HR professionals continually struggle with finding ways to accurately narrow down internal and external candidates in an objective, fact based way, without working insane hours to keep up. Skimming a resume and having to decide whether someone does or does not get shortlisted is not only time consuming, but also potentially discriminatory. The filtering criteria used by employers, particularly with resume parsing technology, is, at best random and ineffective most of the time.

Today, job boards are the source of about 20% of new hires, according to research from HR consulting firm CareerXroads. This is good news for the job boards, however much of the resume filtering technology available is still very young and inaccurate. Human-resources departments continue to be inundated with too many resumes, and job seekers feel that applying online is a waste of their time, knowing that their resume is being compared against parsing criteria that may never even get it into the right hands.

• The problems begin at the job description. Job descriptions are typically created by getting a number of managers to agree on what’s needed to succeed in a job. While those managers may be knowledgeable, each is sharing their opinion about what drives success – they rarely, if ever, have access to facts about the drivers of success.

• So now everything that happens from that point forward is based on a job description that’s been created based on opinion. We’re starting with a shaky foundation. Then comes the comparisons of the resume to the job description.

Ok, so now we know it hurts but what’s being done about it and why aren’t things getting better?

R E S U M E F I LT E R I N G

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As Liz Ryan, CEO of Human Workplace explains “As a job-seeker, you’re wasting your time and energy applying for jobs online. After the keyword-searching algorithm narrows the huge stack of applications down to a smaller stack of them, there are still way too many applications for a human being to look at -- so they don’t.”

While some solutions are striving to alleviate the issues caused by the infamous ATS black hole by implementing detailed profile systems rather than simple resume parsing, the end result remains the same: resumes are dismantled and sorted into searchable elements. Recruiters and hiring managers must still comb through lists of criteria before deciding to view an individual applicant’s details. The trick, says human-resources-technology consultant Elaine Orler of Talent Function Group, is building software that can predict a good fit between candidate and employer. “Cultural and behavioral fit is a stronger indicator of success and business performance [than keywords],” she says.

Cultural and behavioral fit is a stronger indicator of success and business performance [than keywords.]

It’s easy for someone to try to look good on a resume. Word choice can make a huge difference. In addition, applicants can hire a professional to write their resume, presenting the perfect image.

R E S U M E B I A S

• The average correlation between what’s on someone’s resume and their likelihood to succeed in a job is only 14%

• There are obvious issues in using a resume alone to narrow down the choices of who to conduct interviews with. Then, the next set of issues arise during the interview process.

I N T E R V I E W B I A S

During an interview, biases can come up in a number of ways:

Unconscious bias training is a step in the right direction, but unfortunately when people decisions are made purely on someone’s opinion, bias will always seep in.

• Confirmation bias: Evaluating the candidate based on a preconceived belief about that person. The employer will look for information to support this belief.

• Affective heuristic: The use of superficial evaluations when interviewing a candidate. These evaluations can be related to a candidate’s personal background, race, gender, attractiveness, weight, or other similar traits.

• Anchoring: An arbitrary expectation that is placed on the candidate and affects the evaluation of that candidate.

• Intuition: The use of non-objective means to evaluate a candidate, such as emotion, memory, or a “gut feeling.”

• Unconscious Bias: Often allows a first impression, certain characteristics, comparisons, physical cues, and non-job-related information to sway the interviewer’s decision. Even something as simple as how impressive a candidate is at interviewing can sway a decision regarding whether to hire them or not, regardless of their actual fit for the job.

Elaine Orler of Talent Function Group

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The use of tests such as IQ tests, skills tests, and aptitude tests provide data that can be used to help give guidance in determining whether someone is right for a job, without the chance of personal bias getting in the way. That being said, as a stand-alone, assessments only provide a limited and fractured view of a person and is also typically role-specific, which causes them to be used at the wrong point in the process, thereby, limiting their effectiveness.

Job boards were created to increase the flow of talent. Applicant Tracking Systems were then created to deal with the volume to help recruiting teams manage the process. Most companies are employing both. Where companies are now headed is toward superior analytics to improve the quality of match and focus in on the right people.

Not exactly.

An increasing number of companies claim that Artificial Intelligence (AI) will finally be the solution and businesses across the world are jumping on board in a big way. PricewaterhouseCoopers reports that a full 40% of the HR functions in global companies are driven by AI applications. In addition, Montage reports that 51% of talent recruiters say they are confident using AI in their hiring process. For obvious reasons it is easy to be attracted to the flashy AI solutions that are flooding the HR market, however it is imperative to remember there are very few players out there right now who can actually implement AI properly.

The science behind how the tools are designed and their level of accuracy can have serious implications for all parties involved. AI is only as smart as the information it is given, and, as described above, that information is lacking. So goes the saying “Garbage in, garbage out.”

What about tests and assessments? Don’t those help with eliminating bias?

So, what about all the technology out there?

But if we use Artificial Intelligence, we can avoid all the problems above, right?

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Consider bias for example. There are many job matching technology solutions that claim their AI is the answer to taking bias out of the equation, but is that really true? AI can only be as neutral as the data it is given. As Harvard Business Review puts it, algorithms are “our opinions embedded in code.” If the information AI is based on is bias, so is the output.

• AI can adapt and parse a resume by learning and estimating the signals for different sections of the resume, such as names, dates, and different words and word sequences. However, the signals AI must watch out for are manually written into the programming, meaning they might not be all-encompassing and are based on someone’s opinion of what should be mined. Essentially, a human is choosing how and where to train the AI to read those signals. So, if the human directs AI down the wrong path, everything it does going forward will be misguided.

• The amount of data required for AI to adequately learn is astounding. These systems need hundreds of times the amount of data a human being needs to get to the level of deep learning that is required to operate efficiently and accurately. AI is learning from patterns in information. Humans do the same but we’ve learned over our lifetimes what certain cues mean and the connections between different things. AI is like a newborn – it has all the capacity to learn but it is essentially learning everything for the first time and parents play a major role in that learning.

• A company’s infrastructure needs to be scalable enough to deal with the AI workflows the company requires. Again, data is key and so access to all of that data up front is critical to train the AI. Keeping in mind however that, much like a newborn, learning is a lifelong process and must continue after the initial training. The right organizations will structure their data and infrastructure to ensure a continuous learning loop where the information from outcomes is continuously passed back into the AI system to learn and grow.

• Many companies struggle to incorporate insights gleaned from their data into the day-to-day business process, because these insights are not at their fingertips and can’t be easily understood or executed.

The use of tests such as IQ tests, skills tests, and aptitude tests provide data that can be used to help give guidance in determining whether someone is right for a job, without the chance of personal bias getting in the way. That being said, as a stand-alone, assessments only provide a limited and fractured view of a person and is also typically role-specific, which causes them to be used at the wrong point in the process, thereby, limiting their effectiveness.

Results

Skills

Experience

360 Feedback

Strengths & Weaknesses

Preferences

Motivation

Culture

BY combining both WHAT data and WHO data. This unique approach is called Success-Based

What the person has done: This includes skill sets, past experience, and education.

Who the person is: Psychometrics and behavioral science.

This sounds pretty bleak, is there any hope?

How do we understand what the true drivers of success are?

This can provide insight into the qualities of their personality, such as their strengths and weaknesses, preferences, aptitude, work ethic, communication skills, and ability to work as part of a team.

+WHOWHAT

WHAT RE ALLY DEF INES SUCCESS?

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Success-Based Matching provides leaders with the equation and the answer to understanding what makes someone right for a particular role. Like any equation, the steps are important. Once we are able to understand what truly makes someone tick, how do we take what we know about a person and accurately match that person to their right role? What’s a reliable benchmark of success? The exciting thing for business leaders is that they don’t have to hire expensive consultants, or go through cumbersome data mining to figure it out. Hint hint… the answers exist in the people that are already working for them! A company’s top performers already possess the WHO and the WHAT to be successful in their roles, businesses just need to be able to implement a system that can uncover what precisely those factors are, and then use those insights to replicate them.

• Internal mobility capabilities

• Faster more efficient and streamlined recruitment process

• In depth insights that can be used throughout the employee life cycle

• Reduction or removal of biases

• The ability to scale as required

• Increased diversity within the company

• Improved understanding for leaders internal mobility

• Reduced hiring costs

• Avoid bad hires

• Reduce turnover rates

• Easily manage a high volume of applicants

• Improve employee engagement

• Improve college recruitment

The benefits of using Success-Based Matching in combination with machine learning.

YOUR PEOPLE COMPARE & MATCH CLOSE THE LOOP

SUCCESS PROFILES FILL THE GAPS

Success-Based Matching

Success-Based Matching Improves the Decision-Making Process

Profile the top performers at a company

Compare those benchmarks for success with the data collected from the job applicants, which will predict the success for hiring, career pathing, and team building

Close the loop by feeding insights gained back into the platform to optimize the machine learning and improve it for future people planning and decision-making

Build benchmarks for success based on what differentiates top performers from all others

Fill in the gaps by using training and development insights provided by the platform

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Implementing a Success-Based matching approach not only benefits the employer and business as a whole, but it greatly benefits the individual employee or candidate. Being able to help put someone in a role that is truly right for them, helps them live a more fulfilled work life, and lets them know that the employer or HR professional truly care about not only their current value, but also how they can grow and be positioned in the right roles in the future. ‘The in-depth, relevant and objective insights that can be gained from a Success-Based Matching approach will empower employers to provide a positive experience from the very first touch point in the application and interview process, all the way throughout their entire career.

No, not at all. Artificial Intelligence can dramatically improve a company’s people decisions and processes so long as it is properly trained to do so. The real opportunity here is to combine Success-Based Matching with AI to create a highly efficient and effective system that delivers results now as well as learns and continues to get better over time.

However, any company integrating Success-Based Matching into their HR must have complete and active buy-in from the top down. C-level executives need to influence and encourage behavioral change by embracing the technology and assigning champions within the company to help promote enthusiasm for this solution.

Once the platform is in place, front-line managers can take a more active role in the decision-making process and A/B testing can help companies streamline the performance of the platform to make it more efficient.

While investing in a success-based matching system at the offset might seem pricey, the financial benefits far outweigh the initial investment. Given the aforementioned costs and the fact that people represent the largest expense line for virtually all companies, the ROI from avoiding hiring mistakes, reducing the time to hire, lowering turnover and attracting better performing employees from a solution like this should pay off in mere months.

Success-Based Matching technology can be easily integrated into your company’s existing HR process. The provider should be able to be up and running in a matter of weeks vs. months or longer with other types of approaches and without the need for consulting support. Businesses need to be able to view insights and make decisions on the fly so a self-serve interface is vital to making it easy and accessible for usage across the organization.

Employee and Candidate Experience

Ok, so Success-Based Matching is great but does that mean AI is a waste?

Things to remember when selecting a Success-Based Matching provider:

• Be built to include every employee and every potential role within the company

• Be scalable and easily adjustable over time (change as your business needs/environment change)

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Finding and placing the right person in their right role is a crucial component of business success, and a thriving labor market. When successful job matching occurs, it’s no surprise that it results in happier, fulfilled employees, more productive organizations and increased economic profitability. The availability of AI has served to improve job matching processes to a certain extent, however AI on it’s own, provides only a limited answer to the HR issues facing modern businesses looking to keep up and beat out their competitors. Being able to find, hire and manage employees with the use of a predictive analytics platform with AI capability opens up access to a global talent pool and it has the potential to eliminate the biases of the traditional hiring process. However, the answers gained from AI are only as strong and unbiased as the technology used and the data it’s pulling its answers from.

The future of HR may well be AI, and serious pain points may be substantially reduced and even eliminated, however this will only ever be truly successful when businesses first lay the foundation of using the right data in combination with the right science which can be gained through a Success-Based Matching approach.

Jamie Schneiderman is the CEO and Founder of Career Spark, the leader in Success-Based Matching that helps organizations to understand what drives success and to easily and consistently select, develop, and promote top talent.

He believes job performance depends on people working in roles they are built to succeed in. He has long been an advocate of creating a world where the right people are in the right jobs, resulting in happier employees and more productive organizations.

Jamie has spent over 20 years building companies like Procter & Gamble, Coca-Cola and Rogers along with several technology start-ups.

Jamie has a Commerce Degree from the University of British Columbia and an MBA from Harvard. He lives in Toronto, Canada, with his wife and two children.

Conclusion

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