During the Fall Semester of 2021, I conducted a needs assessment with three of my Organizational Performance and Workplace Learning (OPWL) classmates (Sarah Jaramillo, Jennifer Zavala, Zac Faughn) for Aesthetic Day Spa (pseudonym). Over a five-month period, our team employed a systematic approach that used a series of tools to collect and analyze data. The approach was evidence-based and data-driven, enabling us to provide our client with a series of performance interventions that would help close the identified gap between the current and desired performance.
Below is an overview of the methodology used for this project, and some lessons learned from this effort. The full 59 page report in PDF format can be reviewed by expanding the image to the right.
H&B, Inc. (hereinafter H&B, pseudonym) is one of the largest health and wellness companies in the United States. As a franchisor, H&B manages multiple franchise brands, including Aesthetic Day Spa (pseudonym), which was our primary client for this analysis. In 2021, the company was working to rebound from the effects of the economic downturn and the Aesthetic Day Spa leaders had identified two strategic business initiatives:
Increase service providers.
Recover from the COVID-19 pandemic.
However, Aesthetic Day Spa identified a problem that was inhibiting them from achieving their desired performance. Our project team partnered with Aesthetic Day Spa to conduct a needs assessment and provide recommendations that would help the organization achieve their desired performance.
The goal for our needs assessment was to identify potential interventions that would improve the Membership Sales Consultant (MSC) role and improve Aesthetic Day Spa’s ability to achieve its desired performance. In collaboration with our client, our team identified the problem statement to be:
Aesthetic Day Spa owners/managers struggle to hire, quickly onboard, and retain adequately skilled employees to fill the MSC role which, when fully staffed, ensures that spas drive revenue through membership sales.
At Aesthetic Day Spa the MSC role was critical for the organization and could not go unfilled for long before the daily operation at each spa would begin to suffer. Having the MSC role go vacant would create unsustainable workloads for owners/managers, a decrease in customer satisfaction, and a decrease in spa revenue.
Table 1:
Desired Performance and Actual Performance
Our project team spent five weeks reviewing extant data and conducting semi-structured interviews with subject-matter experts and owners/managers. The team used Thomas Gilbert’s Behavior Engineering Model (BEM), updated by Chevalier in 2003, and the Ishikawa Fishbone Diagram as the primary tools/frameworks for the cause analysis. These tools were implemented using a three-step approach which is summarized below.
Open-Source Data:
The team reviewed a publicly available MSC job post to gain a better understanding of the job tasks.
Semi-Structured Interviews:
The team chose to use Thomas Gilbert’s Behavior Engineering Model (BEM), updated by Chevalier in 2003, to create targeted interview questions for semi-structured interviews to focus on factors contributing to the performance. Specifically, this model was chosen so the team could distinguish environmental factors from individual factors. This helped drive the intervention selection as it “provided a structure to troubleshoot performance problems” (Chevalier, 2008, p.10).
Analyzing Data:
The team chose to use Ishikawa's Fishbone Diagram as a model to organize the data collected during the interviews and show potential causes for each BEM factor (Rothwell, et. al, 2018).
The infographic to the right highlights the approach that was used for this assessment, and the documents below show the results of the BEM and Fishbone Diagram.
The Performance Improvement/ HPT Model (Van Tiem, Moseley, Dessinger, 2012, Figure 9.1, pg. 196) was used as an overall guide for the Needs Assessment.
Interview questions were developed using the BEM framework to create targeted interview questions focused on identifying the multiple factors that were contributing to the performance problem.
Interview data was first organized in the Fishbone Diagram to show potential causes for each BEM factor. The color-coded boxes indicate the BEM categories, while the smaller branched text indicates various causal factors. The overall problem is stated at the far right of the diagram.
Then interview data was further categorized to ensure a systematic approach was being leveraged to analyze the performance issue across an array of factors.
Through our systematic process, we identified several causes of the stated problem:
Owners/managers do not always follow the prescribed training program.
The MindBody system (an online scheduling and client management software) is both difficult to learn and is not addressed in current training programs.
The online onboarding training is focused on sales and does not cover all aspects of the MSC role.
The sequence of topics covered in the online onboarding training does not support an ideal order of learning the job tasks and can be overwhelming; this is a reason some MSCs leave during the training process.
Some owners/managers do not know how to effectively onboard MSCs; i.e., no train-the-trainer is available.
Standards of excellence for the role aren’t available.
Performance evaluations are, in some cases, only given annually, and performance expectations may be unclear.
MCSs do not get embedded quickly into the culture; another reason that some MSC's decide to leave.
After completing the data collection and causal analysis, our team used a four-step intervention selection process to produce a list of interventions for the client that would likely improve the client's stated problem.
The team used the following models for the intervention selection:
Ease/Impact Analysis to evaluate interventions based on their ease of implementation and impact.
Performance Factors Addressees by Proposed Interventions to identify factors that would be impacted if implemented (enabling factors, inhibiting factors, and interventions required to eliminate the inhibiting change if implemented).
Prioritization Criteria Matrix to rank the interventions using multiple criteria (impact, franchise laws, feasibility/willingness to develop, feasibility/willingness to implement) to produce a total score, which was used to determine the priority of each intervention.
Completed models can be found on pages 20-28 of the full report.
The team used the four-step intervention selection process to identify the top recommended interventions and present them to the client:
Restructure the LMS Onboarding Training Program
Develop an Onboarding Schedule
Develop a Train-the-Trainer Program
Develop an MSC Evaluation Program
Foster Positive Spa Cultures
Fold New MSCs into Spa Culture Immediately
Develop an Interviewing Skills Training Program
With each recommendation our team provided the client supporting information for implementation. This information included a description of the intervention, the problem it solved, supporting factors, restraining factors, as well as key steps for successful implementation.
The final report and infographic were submitted to our client in December of 2021. The client was very pleased and impressed with the report and provided positive feedback regarding the findings/recommendations.
In summary, our project was a successful learning experience and we met our OPWL Learning Goals. Our team was a exceptionally collaborative both internally and with our client. We maintained open communications, respectfully shared ideas and feedback, and all project team members equally contributed.
While most of the project went as planned, some areas were revised during the analysis as our team learned more about the needs assessments. To reflect our changes, the project plan was refined and we kept the client informed of all changes. Changes made to the project plan included:
As a team we decided there would be more benefit from using the BEM than the Strength, Weakness, Opportunities, Threats Framework.
The team also determined we would get more participation and collect more valuable data from individual interviews, so we changed the data collection from focus groups to semi-structured interviews.
We also decided we would not interview the MSCs due to the small pool of participants and the likelihood they would only provide positive responses, skewing our data.
Photo by corelens from Canva
Chevalier, R. (2008). The evolution of a performance analysis job aid. Performance Improvement, 47(10), 9–18. https://doi.org.libproxy.boisestate.edu/10.1002/pfi.20034
Gilbert, T. (2007). The behavior engineering model. In Human competence: Engineering worthy performance (tribute edition) (pp. 73-107). Pfeiffer.
Rothwell, W. J., Hohne, C. K., & King, S. B. (2018). Human performance improvement: Building practitioner performance (3rd ed.). New York, NY: Routledge.
Van Tiem, D., Moseley, J., & Dessinger, J. (2012). Fundamentals of Performance Improvement: Optimizing results through people, processes and organizations (3rd ed.). John Wiley & Sons.