In this case study, a team strives to improve the recruiting process in a large, fast-moving consumer goods company. Part 1 focused on reducing the recruiting cycle time. Part 2 focuses on decreasing the effort required to fill a job opening.
The case described here uses total quality management (TQM) to address the problem of rising attrition in a large, fast-moving consumer goods company in India. Specifically, the HR team sought to reduce the time and effort involved in finding good candidates for open positions. (Note: The details of the process have been condensed and modified for the sake of confidentiality and easy of storytelling.)
As in Part 1 of this article, which addressed the cycle time to fill open positions, Part 2 approaches the issue of reducing the effort required for each recruitment through the seven steps of problem solving:
- Define the problem
- Research the causes
- Generate countermeasure ideas
- Test and modify the ideas
- Implement ideas
- Standardize procedures
- Compile quality improvement story
Step 1: Define the Problem
The 22-step recruitment process as developed in Part 1 of this case study is shown in Table 1.
|Table 1: 22-step Recruitment Process|
|1||Send resignation message to HR with request to initiate recruitment|
|2||HR manager directs hiring team to start the recruitment process|
|3||Log into employment website/contact recruiter|
|4||Identify/collect candidate resumes|
|8||Send shortlisted resumes to department manager|
|9||Agree to interview date|
|10||Call candidate for interview|
|12||Interviewers complete feedback form|
|13||Send feedback form to HR|
|14||Call candidate for interview 2|
|15||Confirm interview date|
|17||Interviewers complete feedback form|
|18||Compensation offer determined|
|19||Compensation offer sent for approval|
|21||Send offer letter|
To improve any problem, it must be measurable (problem = desired state – current state).
Table 1 reveals two easily measurable inputs: 1) the number of resumes reviewed and 2) the number of interviews held. The overall output is the number of successfully filled open positions.
Two metrics to measure the improvement were agreed upon by the project team:
- Resumes scanned per candidate selected (R/C) and
- Interviews conducted per candidate selected (I/C).
Data from past recruitments was collected and is summarized in Table 2.
|Table 2: Resume Selection|
|Process Step||Number of Resumes
||Number of Resumes Selected|
|Resumes scanned – initially||100||95|
|Resumes scanned – interview 1||95||47|
|Resumes scanned – interview 2||47||21|
|Resumes scanned – interview 3||21||16|
R/C = 100 / 16 = 6.25
I/C = (95+47+21) / 16 = 10.2
The goal of the team was to reduce these measurements by 30 percent.
Step 2: Research the Causes
Why #1: Why were there so many interviews for each candidate selected? As Table 2 shows, only 5 percent of the resumes were rejected in the first selection step. In each of the subsequent two interviews, the rejection rate increased to 50 percent. It was clear that if the resume review process could be improved such that the number of candidates rejected could be increased earlier in the candidate selection process, the process would be more efficient.
Why #2: Why was the resume screening so ineffective? A test was done to expose the causes. There were three staff members who did the screening. A sampling from past selections was prepared, consisting of 10 resumes from which three candidates had been selected.
The three staff members were given the 10 selected resumes and asked to select which they would shortlist for interviews. The results are shown in Table 3 below.
|Table 3: Resume Selection Test|
|Reviewer||Resumes Provided||Resumes Selected||Successful Selections*|
*The staff member selected the resume of a candidate who had received a job offer.
Reviewer 1 had a much more efficient process of shortlisting than his colleagues as his ratio of shortlisted candidates was 3/7 (42 percent) compared to 1/4 (25 percent) and 1/6 (15 percent) of Reviewers 2 and 3.
Why #3: Why do the employees have varying degrees of efficiency at scanning the resumes? The criteria each staff member used to review resumes was clearly different as shown by the varied results. To learn more, the staff members were asked to list the criteria by which they selected or rejected the candidates. Predictably, the number and type of criteria used by each staff member differed. These results were tabulated as shown in Table 4 below.
|Table 4: Tabulation of Selection Criteria Used|
|Criteria||Reviewer 1||Reviewer 2||Reviewer 3|
Step 3: Generate Countermeasure Ideas
A means for standardizing the basis for candidate selection was required. The first shortlisting of relevant criteria listed in Table 4 was reviewed with the following categories:
- Criteria listed by all three (e.g., 1 and 4)
- Criteria listed by at least two staffers (e.g., 2 and 6)
- Criteria used by Reviewer 1 since his selection was most accurate
- All others
Each criteria was discussed before coming to a final consensus on whether it would be included in the evaluation moving forward. The results of these discussions are shown in Table 5.
|Table 5: Selection Criteria – Standardized|
|Criteria||Reviewer 1||Reviewer 2||Reviewer 3||Criteria to Keep|
The list of shortlisted criteria was reviewed by department heads requesting recruitment efforts; additional criteria suggested by them were incorporated into the new criteria.
The list of criteria (10 items in the end) to be applied in selecting resumes was determined. To further refine the process, a weighted average table was used to develop the numerical weight for each criteria relative to the others with a total possible score of 100 for each resume reviewed against the selection criteria. The resume selection model was now ready for testing.
Step 4: Test and Modify the Ideas
The list of criteria was tested with three batches of past selections and proved effective.
Step 5: Implement Ideas
The process was implemented for all future recruitment.
Step 6: Standardize Procedures
The specific improvements are shown in Tables 6 and 7.
|Table 6: Improvements in Recruitment Efficiency|
|Table 7: Improvements in Recruitment Efficiency|
The changes to the process resulted in a 40-percent reduction in the average number of interviews conducted per candidate selected and a 34-percent reduction in the average number of resumes reviewed per candidate selected. The process was standardized and adopted for regular use.