Delivering Better Customer Service with Predictive Hiring


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Providing customers with the best possible experience begins with hiring the right employees to represent the brand. Naturally, if an individual is in a position in which they either are not or cannot excel, there will be derivatives of such internal dissatisfaction that inhibit a positive interaction with external stakeholders. And there’s apparently plenty of dissatisfaction to go around—two-thirds of 2011 Consumer Reports respondents indicated that they’d left a store due to poor service and 65% of those individuals did so because of rude salespeople.

Consider your most recent negative experience as a customer. Did you feel that that employee enjoyed their job or, more precisely, was a good fit for the position and/or organization? While there are certainly anomalous situations in which the employee may have been having a particularly bad day or you were a particularly frustrating customer, the likelihood is that they were in a position that wasn’t right for their personality, skillset or values. The consequence? They, the customer and the employer are all losing out.

Aberdeen’s Human Capital Management Trends 2013 report indicates that 71% of organizations see alignments between HR initiatives and strategic business objectives as the most critical skill of HR leaders. So, if your firm’s overarching goal is to better fulfill customer needs, HR needs to hone in their talent selection to focus on that goal. Below are my thoughts on doing so through the development of a structured, job-relevant hiring process.

Construct a Structured Job Profile

In order to find the right candidates, you’ve got to know what you’re looking for. With the overarching question of “What makes a good customer service representative in our organization?” set out to determine the traits, knowledge and competencies that allow someone to excel under the requirements and environment of the job.

If your firm’s overarching goal is to better fulfill customer needs, HR needs to hone in their talent selection to focus on that goal.

When possible, move beyond merely anecdotal information to gather substantive qualitative and quantitative performance data. Although considerably more challenging to acquire both in terms of time and validity, performance data offers deeper insight into what is currently working with your hiring process and who the right client-facing hires really are. Here are a few straightforward tips for doing so:

  • Survey a number of internal stakeholders who have various proximities to the position—managers, executives, subordinates and those in similar positions—to account for the differentiation in perspective.
  • Ensure the data collected is within the employee’s scope of influence.
  • Account for common rating errors, including the Central Tendency Error (consistently using a middle-of-the-road rating) and the Halo Error (falsely attributing personality traits like kindness to one’s competency).
  • Align the raters’ incentives with the objective. A manager’s bonus should not be based on how they rate subordinate’s performance. (This happens more often than you’d think!)

In my book, Hire, Fire and the Walking Dead, I relate recruiting to sales, reminding that you can’t sell a product if you don’t even know what it is. Use the information you gather about the job to figure out what it’s really all about so that you can market to and qualify your leads correctly.

Screen with Job-Relevant Assessment Technology

Once adequate performance data has been synthesized into a job profile, hiring managers have a benchmark against which they can assess applicants. However, it’s important that this benchmark be incorporated in multiple structured candidate filters, in order to gain deep, accurate candidate insight. This is essential as findings published in our most recent research report reveal that one of the three root causes of poor hiring is confusion about which selection tools to use.

An objective method for implementing a structured profile is to leverage automated behavioral science technologies. More traditional selection methods, such as resume scans and phone-based reference checking, can introduce bias, pushing poor fit candidates further into the process and potentially weeding out top performers early on. Data released in 1998, mapped the predictive validity of assessments, and found that cognitive ability and personality assessments were dramatically more predictive.1 A more recent study from 2004 demonstrated that automated solutions further eliminated subjectivity by mitigating scoring errors.2

Although seemingly common sense, many are surprised to find that common interviewer questions like “What color would you be and why?” don’t actually offer any insight into how the candidate will actually perform because (a) the question is erroneous to the requirements of the job and (b) the subsequent rating of the answer is also subjective. However, those questions that investigate a candidate’s relevant traits and competencies in the context of their previous behaviors and are rated on a standard scale shed light on their performance track record. This New York Times article discusses how this evolution from subjective to objective methods took place at Google.

Simply put, with automated assessments, hiring managers cut out their gut instinct and rely predominantly on the objectivity and job-relevance of the structured profile. No more hiring based on resume buzzword bingo or candidate narcissism.

With automated assessments, hiring managers cut out their gut instinct and rely predominantly on the objectivity and job-relevance of the structured profile

Aspen Dental found an instant improvement in their quality of hire after instituting an automated behavioral assessment in 2011. Facing the unprecedented growth of 55 new locations a year for three consecutive years, Aspen Dental’s managers were overwhelmed by an enormous pipeline of candidates and an unstructured hiring process. Poor hiring decisions were having a negative impact on the business, primarily through low employee retention.

However, with the implementation of automated personality trait and reference checking solutions, they were able to filter candidates in accordance with job-relevant metrics. In addition to reducing time to hire, Aspen Dental’s subsequent turnover was reduced by 45% (See the complete case study in Talent Management Magazine, February 2013, page 55).

While using one form of automated assessment is a huge step in the right direction, multiple data points derived from layering such job-relevant assessments throughout the funnel provides HR practitioners incremental predictability (read: the Holy Grail of hiring). For instance, as was the case with Aspen Dental, some firms are leveraging personality assessments at the top of the funnel as a means for quickly weeding out the tire kickers and following up with a structured interview and automated reference checking to gain deeper insight into the candidate’s performance potential. This succession of relevant, objective assessments exposes a crystal ball that tells us exactly what kind of employee they candidate will actually be.

Yet, despite 2012 Towers Watson findings that 92% of large firms and 77% of midsize companies are utilizing technology in their hiring process, it’s only the progressive minority that are leveraging multiple behavioral science-based technologies throughout the entirety of their screening process. To put it simply, these select few are gaining direct access to the best and brightest of the candidate pool, leaving the scraps for their competitors.

Optimize Through Feedback

A strong talent selection process doesn’t end when the hire is made; there’s always opportunity for further refinement Yet, despite this ongoing opportunity, many firms fail to adequately audit their process through a documented feedback mechanism. Consider the following questions when auditing your process:

  • Does each step have a strong value-add?
  • Does the time required for the candidate to engage the screen match the level of the position?
  • Is the process designed to seek a mutually good fit?
  • Are the post-hire results supporting the position’s business objective?

The answers to these questions, supported by post-hire performance data, determine how the process can be further improved.

Enhance Employee Success with Coaching

While finding great staff depends on a successful talent selection process, sustaining new hires’ success will require maintenance in the form of coaching. According to Aberdeen Group’s Human Capital Management Trends 2013 report, “learning and development” is among the top three most pressing human capital management priorities for organizations. That said, effective talent management is a lost art—and, too often, just altogether lost.

However, with a structured hiring process that provides real insight into the candidate, managers can access certain components of the screening results to create a tailored development plan. They can deliberately work to their strengths and help them manage their weaknesses, all in pursuit of delivering an improved customer experience. After all, even the candidate with the best fit for the position can be further developed – and will certainly need to be if the organization is dynamic or undergoing rapid change.

Talent Selection Round Up

Giving customers the best experience possible comes down to finding the right people for them to interact with – and in that regard, the weight of the world lies on hiring manager’s shoulders. To alleviate the pressure, collaborate with stakeholders to create an action plan for implementing the steps I’ve outlined above. Take advantage of the pre-hire assessment technology available to create a more impactful hiring process from start to finish.

End Notes:

  1. Schmidt, F. and Hunter, J. (1998). The Validity and Utility of Selection Methods In Personally Psychology: Practical and theoretical implications of 85 years of research findings. American Psychological Association.
  2. Naglieri, J.A., Drasgow, F., Schmit, H., Handler, L., Prifitera, A., Marglis, A., & Velasquez, R. (2004). Psychological testing on the internet. American Psychologist.
Greg Moran
Greg Moran is the founder and CEO of, the leading provider of cloud-based predictive talent selection™ solutions. In addition to authoring two books, Greg has contributed his thought leadership regarding human capital management and pre hire testing to national publications including BusinessWeek, INC Magazine and Wall Street Journal.


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