Purpose

To enable recruiters and hiring managers to evaluate the efficiency of the recruitment process, assess their past and current performance, benchmark against targets or organizational goals, and leverage actionable insights to improve performance and track the outcomes.

Audience

This document is created considering its use by recruiters, recruiting and Hiring managers to monitor the efficiency of the recruitment process, identify areas for improvement, and make data-driven decisions to optimize the recruitment process.

The basics

The Recruitment Effectiveness Dashboard offers talent acquisition professionals clear insights into the recruitment process and its effectiveness.

Users can access and log out of the dashboard by taking the following steps.

Accessing the dashboard:

• Open a supported browser, and go to https://app.eightfold.ai.
• Enter the email address and password for your EF account.
• Click Sign In.
• Go to the Dashboards tab, and select Recruitment effectiveness dashboard.

For the first time users:

If you are a first-time user of the Recruitment effectiveness dashboard, you will need to provision to view it in the 'Insights' (or) 'Dashboards' tab. The user should have the permission ‘perm_manage_rectruitmentanalytics_dashboard’ as well as ‘perm_manage_talent_reports‘ mapped to their role to view this dashboard.

Steps to provision the dashboard

• After signing in, go to More > Admin Console > Data Warehouse > Provision Dashboards.
• In the Recruitment effectiveness dashboard row, select the actions icon.
• Select Create and then Submit. Once you’ve provisioned the dashboard, it will appear as an option in the Dashboards (or) Insights tab (based on how you have named it).

Once provisioned, the dashboard will appear on the Dashboards (or) Insights tab.

Logging out

To log out of https://app.eightfold.ai, select your user icon at the top-right of the page and then select Logout.

Data Refresh Frequency

The information on this dashboard is updated every 2 hours.

Dashboard features

When you access the Recruitment effectiveness dashboard, you’ll see a controls section/row and then several tabs, graphs, and tables.

The dashboard contains the following features along with the controls section on the top of every tab:

• Closed positions
• Open positions
• Tabular view
• Improvement opportunities

The following sections describe the dashboard features in detail.

Controls

Controls are attributes used for customizing the Recruitment effectiveness dashboard based on different fields (such as Position function, Position location, recruiter, hiring manager).

To better understand the dashboard tiles, it's important to first understand the Controls section.

To open the Controls section, click anywhere in the section. This will expand the Controls section and show the fields mentioned above.

In the Controls section, you’ll be using the fields as filters to show the relevant data that you want to see in the dashboard:

Select the relevant fields as per your requirement for all the tabs under the controls.

• Position function: This is inferred based on the Job Function mapped to the Position.
• Position location: The location of the position could be different from the location of the career site visitor.
• Recruiter: The name of the Recruiter of the position. If there is no recruiter mapped to a position, the value displayed will be ‘Recruiter Not Assigned’.
• Hiring Manager: The name of the Hiring Manager of the position. If there is no recruiter mapped to a position, the value displayed will be ‘Hiring Manager Not Assigned’.
• Date granularity (Only on closed positions): This can control the granularity of the data by Month, Quarter, Year in all the time series charts.
• Date Range Controls across Tabs (From, To):
  • Standalone Metrics: For metrics specific to a particular stage, this control adjusts the date range for that stage. For example:
    • Hires: Counts hires made between the selected "From" and "To" dates based on their hiring date.
    • Offer Conversion Rate: This rate takes into account offers made within the selected date range.

  • Multi-stage Metrics: For metrics or visuals encompassing several stages or processes, the control sets the date range based on application dates. For instance:
    
    • Recruitment Funnel: Demonstrates the funnel progression based on application dates falling between the selected "From" and "To" dates.
    • Overall Conversion Rate: This rate captures the transition from applications to hires within the specified date range.

Note: Relevant timestamps (such as application or hiring dates) utilized in metric calculations are highlighted within the visuals.

Dashboard walkthrough

Closed positions

All the metrics in this section are only related to the positions that are closed.

Section 1: Overview

This section provides a snapshot of critical recruitment metrics for the selected time period. It offers a quick glance at the efficiency and outcomes of the recruitment process, showcasing both current figures and a comparison to the previous quarter (QoQ).

KPI and formula

• Total positions closed: Unique number of positions with position_is_open flag equal to 0.

  Calculation: distinct_count({position_id})

  Filters used: [position_is_open = 0]

• Total hires: The count of unique applications with a confirmed hiring timestamp.

  Calculation: distinct_countIf({application_id},isNotNull({hired_ts}))

  Filters used: [position_is_open = 0]

• Average days to hire: The average number of days between the application submission and the confirmed hiring date

  Calculation: dateDiff({application_ts},{application_hired_ts},'DD')

  Filters used: [position_is_open = 0]

• Overall conversion rate: The ratio of candidates who were successfully hired to those who reached the phone screen stage

  Calculation: distinct_countIf({application_id},{stage_group}='hired')/distinct_countIf({application_id},{stage_group}='phonescreen')

  Filters used: [position_is_open = 0]

• Offer acceptance rate: The ratio of candidates who were successfully hired to those who were extended an offer

  Calculation: distinct_countIf({application_id},{stage_group}='hired')/distinct_countIf({application_id},{stage_group}='offer')

  Filters used: [position_is_open = 0]

Section 2: Effectiveness

This section visualizes the recruitment funnel, detailing the progression of candidates through various stages of the hiring process within the selected time period. It highlights the volume and conversion rates at each stage, allowing for insights into the efficiency of the recruitment pipeline. Additionally, the "Average Days to Advance" metric offers a perspective on the timeline and speed of candidate progression from one stage to the next.

KPI and formula

Stage conversion rates

• New applicant to phonescreen: The ratio of new applicants to those who progressed to the phone screen stage

  Calculation: distinct_countIf({application_id},{stage_group}='new_applicant')/distinct_countIf({application_id},{stage_group}='phonescreen')

  Filters used: [position_is_open = 0]

• Phonescreen to onsite/interview: The ratio of candidates who underwent a phone screen stage to those who progressed to onsite/interview stage

  Calculation:distinct_countIf({application_id},{stage_group}='phonescreen')/(distinct_countIf({application_id},locate{stage_group}='onsite' OR locate{stage_group}='interview'))

  Filters used: [position_is_open = 0]

• Onsite/interview to offer: The ratio of candidates who attended onsite/interview stage to those who were subsequently extended a job offer

  Calculation: (distinct_countIf({application_id},locate{stage_group}='onsite' OR locate{stage_group}='interview'))/distinct_countIf({application_id},{stage_group}='offer')

  Filters used: [position_is_open = 0]

• Offer to hired: The ratio of candidates who were extended an offer to those who were successfully hired

  Calculation:distinct_countIf({application_id},{stage_group}='offer')/distinct_countIf({application_id},{stage_group}='hired')

  Filters used: [position_is_open = 0]

Avg days to advance:

• New applicant to phonescreen: Average time taken in days for the candidates to move from application stage to phonescreen stage.

  Calculation: dateDiff({new_applicant_ts}, {phonescreen_ts},'DD')

  Filters used: [position_is_open = 0]

• Phonescreen to onsite/interview: Average time taken in days for the candidates to move from phonescreen stage to onsite/interview stage.

  Calculation: dateDiff({phonescreen_ts}, {onsite_ts},'DD')

  Filters used:[position_is_open = 0]

• Onsite/interview to offer: Average time taken in days for the candidates to move from onsite/interview stage to offer stage.

  Calculation: dateDiff({onsite_ts}, {offer_ts},'DD')

  Filters used:[position_is_open = 0]

• Offer to hired: Average time taken in days for the candidates to move from offer stage to hired stage.

  Calculation: dateDiff({offer_ts}, {hire_ts},'DD')

  Filters used:[position_is_open = 0]

For all the metrics in the overview section, the effectiveness section has a deepdive trend analysis, break-down by job function, hiring manager, and recruiter. This helps in identifying patterns & anomalies, optimize team performance and allocate resources.

Section 3: Application quality

This section assists hiring teams in understanding the quality of applications received, evaluating the efficacy of different recruitment sources, and monitoring any fluctuations in application quality over time

KPI and formula

• Average match score of hires: Average match score of all the hired candidates

  Calculation: avgIf({application_match_score},{stage_group}='hired')

  Filters used:[position_is_open = 0]

Section 4: Diversity

This section presents the "Diversity" metrics focused on gender:

• Gender distribution among all applicants for a specified period.
• Gender distribution among those who were successfully hired during that period.
• A 12-month trend detailing gender diversity, tracking both female applications and female hires.

This data aids organizations in monitoring their gender diversity metrics in recruitment, ensuring inclusivity in hiring practices, and tracking their progress towards set diversity and inclusion goal

KPI and formula

• % Female hires: Proportion of females (based on application inferred gender) among the total hires

  Calculation: distinct_countIf({application_id},{application_inferred_gender}='female' AND {stage_group}='hired') /

  distinct_countIf({application_id}, {stage_group}='hired')

  Filters used:[position_is_open = 0]

• % Female applications: Proportion of females (based on application inferred gender) among the total applicants

  Calculation: distinct_countIf({application_id},{application_inferred_gender}='female')/distinct_count({application_id})

  Filters used:[position_is_open = 0]

Open positions

All the metrics in this section are only related to the positions that are open.

Section 1: Overview

This section provides a snapshot of critical recruitment metrics for the selected time period. It offers a quick glance at the efficiency and outcomes of the recruitment process

KPI and formula

• Open positions: Unique count job positions that are currently open for recruitment.

  Calculation: distinct_count({position_id})

  Filters used: [position_is_open = 1]

• Active applicants: Total number of unique applicants who are still active in the process for open positions

  Calculation: distinct_count({application_id})

  Filters used: [position_is_open = 1] AND [application_status = 'active']

• Average days since creation: For all 'open' positions, the average number of days since their respective creation date.

  Calculation: avg(dateDiff({position_creation_ts},now(),'DD')

  Filters used: [position_is_open = 1]

• % Offered positions: The percentage of positions where an offer has been made out of all open positions

  Calculation: distinct_countIf({postion_id},{stage_group}='offer') / distinct_countIf({position_id})

  Filters used: [position_is_open = 1]

Section 2: Effectiveness

This section showcases the "Effectiveness" of the recruitment process by illustrating the recruitment funnel. It delineates the journey of candidates from application to hire during the chosen time frame. Alongside the volume of candidates at each stage, the "Stage Conversion Rate" provides a percentage of applicants progressing from one phase to the next. Furthermore, the "Stalled Applicants" metric highlights those candidates who remain stagnant in a particular stage for over 30 days, giving insights into potential bottlenecks or delays in the recruitment process

KPI and formula

Stage conversion rate:

• New applicant to phonescreen: The ratio of new applicants to those who progressed to the phone screen stage

  Calculation: distinct_countIf({application_id},{stage_group}='new_applicant')/distinct_countIf({application_id},{stage_group}='phonescreen')

  Filters used: [position_is_open = 1]

• Phonescreen to onsite/interview: The ratio of candidates who underwent a phone screen stage to those who progressed to onsite/interview stage

  Calculation: distinct_countIf({application_id}, {stage_group}='phonescreen')/(distinct_countIf({application_id},locate{stage_group}='onsite' OR locate{stage_group}='interview'))

  Filters used: [position_is_open = 1]

• Onsite/interivew to offer: The ratio of candidates who attended onsite/interview stage to those who were subsequently extended a job offer

  Calculation: (distinct_countIf({application_id},locate{stage_group}='onsite' OR locate{stage_group}='interview'))/distinct_countIf({application_id},{stage_group}='offer')

  Filters used: [position_is_open = 1]

• Offer to hired: The ratio of candidates who were extended an offer to those who were successfully hired

  Calculation: distinct_countIf({application_id},{stage_group}='offer')/distinct_countIf({application_id},{stage_group}='hired')

  Filters used: [position_is_open = 1]

Stalled applicants: Active applicants that remained in the stage for 30+ days without progressing

• Stagnant applications after phonescreen: Active applicants who cleared the phone screen stage but haven't progressed to the onsite/interview stage for at least 30 days

  Calculation: distinct_countIf({application_id},isNotNull({phonescreen_ts}) AND isNull({onsite_interview_ts}) AND dateDiff({phonescreen_ts},now(),'DD')>${StagnationDays})

  Filters used: [position_is_open = 1] AND [application_status = 'active']

• Stagnant applications after Onsite/Interview: Active applicants who cleared the onsite/interview stage but haven't progressed to the offer stage for at least 30 days

  Calculation: distinct_countIf({profile_id},isNotNull({onsite_interview_ts}) AND isNull({offer_ts}) AND dateDiff({onsite_interview_ts},now(),'DD')>${StagnationDays})

  Filters used: [position_is_open = 1] AND [application_status = 'active']

• Stagnant applications after offer: Active applicants who have been made an offer but not moved to hired stage for at least 30 days

  Calculation: distinct_countIf({profile_id},isNotNull({offer_ts}) AND isNull({hired_ts}) AND toLower({application_status})='active' AND dateDiff({offer_ts},now(),'DD')>${StagnationDays})

  Filters used: [position_is_open = 1] AND [application_status = 'active']

This section also presents a detailed breakdown of job positions based on the number of days since their creation, offering insights into the lifespan and responsiveness of recruitment efforts for specific roles. The chart to the left showcases the volume of job positions according to their age, allowing teams to prioritize or reassess older positions. On the right, a detailed table enumerates specific roles, their corresponding recruiters, and key metrics such as applications in the pipeline, average days per stage, and average days from application to recruiter screen. These metrics provide an in-depth understanding of recruitment efficiency and bottlenecks for each role

KPI and formula

• Average days from application to recruiter screen: Average number of days taken for the applicants to move from new applicant stage to phonescreen stage

  Calculation: avg(dateDiff({new_applicant_ts}, {phonescreen_ts},'DD'))

  Filters used: [position_is_open = 1]

• Average days from screening to interview: Average number of days taken for the applicants to move from phonescreen stage to onsite/interview stage

  Calculation: avg(dateDiff({phonescreen_ts},{onsite_interview_ts},'DD'))

  Filters used: [position_is_open = 1]

• Average days from interview to offer: Average number of days taken for the applicants to move from new onsite/interview stage to interview stage

  Calculation: avg(dateDiff({onsite_interview_ts},{offer_ts},'DD'))

  Filters used: [position_is_open = 1]

• Average days from offer to hired: Average number of days taken for the applicants to move from offer stage to hired stage

  Calculation: avg(dateDiff({offer_ts},{hired_ts},'DD'))

  Filters used: [position_is_open = 1]

• Average days per stage: This represents the overall average of the following stages:
  • Time taken from new applicant to phone screen.
  • Time taken from phone screen to onsite/interview.
  • Time taken from onsite/interview to offer.
  • Time taken from offer to hire.

    Each of these durations is first averaged for its respective stage, and then an overall average is taken of these averages.

    Calculation: ( avg(ifelse(isNull({Time from application to phonescreen}),0,{Time from application to phonescreen}) ) + avg(ifelse(isNull({Time from phonescreen to interview}),0,{Time from phonescreen to interview}) ) + avg(ifelse(isNull({Time from interview to offer}),0,{Time from interview to offer}) )+ avg(ifelse(isNull({Time from offer to hired}),0,{Time from offer to hired}) ) ) / (ifelse(avg({Time from application to phonescreen})>0,1,0) + ifelse(avg({Time from phonescreen to interview})>0,1,0) + ifelse(avg({Time from interview to offer})>0,1,0) + ifelse(avg({Time from offer to hired})>0,1,0)`)

    Filters used: [position_is_open = 1]

The below graphs provide an analysis of applications based on their duration in the recruitment pipeline. The left chart delineates the volume of applications by the number of days they've been in the system, segmented by their current stage. This visualization aids in identifying potential bottlenecks or stages where applications tend to stall. On the right, the table offers a granular view of stalled applications, detailing the role, recruiter, last stage navigated, and the duration since the last movement.

KPI and formula

• No of days in pipeline: For all active applicants, the average number of days since they submitted applications for positions that remain open

  Calculation: avg(dateDiff({application_ts},now(),'DD')

  Filters used: [position_is_open = 1] AND [application_status=’active’]

• Days since last stage: Number of days since applicants cleared their most recent stage

  Calculation: dateDiff({application_last_stage_ts},now(),'DD')

  Filters used: [position_is_open = 1]

Section 3: Recruiter workload and performance

This section presents a dual perspective on recruiter workload and performance. On the left, we see the number of open positions assigned to each recruiter, providing a snapshot of their current workload. The table on the right dives deeper, showcasing each recruiter's activity details for the specified time period, including the roles they're hiring for, their communication efforts, and the outcomes of those efforts in terms of candidate responses and applications received.

• Communications sent: No of messages sent by recruiters via Email, WhatsApp, SMS, Slack, Chatbot and campaign messages

  Calculation: sum({communications_sent})

  Filters used: [position_is_open = 1]

• Communication read by candidates: No of messages read the candidates that were sent by the recruiters

  Calculation: sum({communications_read})

  Filters used: [position_is_open = 1]

• Responses from candidates: No of messages, where a response has been sent by the applicant

  Calculation: sum({communications_responded})

  Filters used: [position_is_open = 1]

• Applications received: Unique applications received for all the open positions

  Calculation: distinct_count({application_id})

  Filters used: [position_is_open = 1]

Section 4: Diversity

The information in this section can be utilized to assess their current gender diversity in the applicant pool of currently open positions

KPI and formula

• % Female applicants: Proportion of females (based on application inferred gender) among the total applicants

  Calculation:distinct_countIf({application_id},{application_inferred_gender}='female')/distinct_count({application_id})

  Filters used: [position_is_open = 1]

Tabular view

This section provides summaries of recruitment performance, job positions, and feedback. Metrics are displayed in a table for easy export and further analysis.

The recruitment performance summary provides a comprehensive overview of recruitment metrics for each recruiter. It tracks the number of positions created, applications received, offers extended, and successful hires made. This data allows for an in-depth analysis of a recruiter's efficiency and effectiveness.

The "Positions Summary" table provides a detailed overview of various job positions

The "Feedback Summary" table offers an insight into the feedback dynamics within the recruitment process. It lists individual reviewers and quantifies their engagement with the feedback mechanism.

• Positions: Total no of positions created in the respective month that are tagged to the recruiter

  Calculation: distinct_count({position_id})

• Applications: No of applications received for the tagged positions above

  Calculation: distinct_count({application_id})

• Offers: No of offers extended for the tagged positions above

  Calculation: distinct_countIf({application_id},isNotNull({offer_ts}))

• Hires: No of hires for the tagged positions above

  Calculation: distinct_countIf({profile_id},isNotNull({hired_ts}))

• Offer acceptance rate: Ratio of hires to offers made for the positions tagged above

  Calculation: Hires/Offers

• Average time to hire: For the positions tagged above, the average time taken for the applicants to move from application stage to hire stage

  Calculation: avg(dateDiff({application_ts},{hired_ts},'DD'))

• Overall conversion rate: Ratio of hires to applicants for the positions tagged above

  Calculation: Hires/Applications

• Total feedback requested: The total number of feedback requests sent to reviewers/interviewers

  Calculation: distinct_countIf({feedback_id}

• Feedback response rate: The ratio of feedbacks responded to the total feedbacks requested, expressed as a percentage

  Calculation: distinct_countIf({feedback_id},isNotNull({responded_timestamp}))/distinct_count({feedback_id})

• Feedback response time:

  Calculation: dateDiff({requested_timestamp},{responded_timestamp},'DD')

• Feedback pending:

  Calculation: distinct_countIf({feedback_id},isNull({responded_timestamp}))

Improvement opportunities

The "Improvement Opportunities" tab provides an in-depth comparative analysis of essential recruitment metrics for both closed and open positions. This tab allows for a detailed breakdown by hiring manager, recruiter, job function, or business function.

It consolidates the following metrics, which are already available in previous tabs. Bringing them together in one location simplifies benchmarking and assessment. Below are the metrics it consists:

• Average days to hire
• Average conversion rate
• Average offer acceptance rate
• Number of communications sent out
• Average feedback response rate
• Average feedback response time.

Stage mapping

Things to know as you analyze the mapping:

• Default Stage mapping: If stage mapping configuration is left untouched, EF uses inbuilt logic to map your recruitment stages to the standard EF stage groups.

• About 'EF Missing stages’: Not every stage change is properly captured in the ATS. Eightfold Analytics infers these missing stages to enable proper funnel conversion analysis. These stages are named with the suffix 'EF_Missing' and generally the timestamp associated with these stages will be the same as the earliest available stage date in the application process. For example: If candidates are advanced from new_applicant to onsite without going through the ‘phonescreen’ stage, EF creates a ‘missing stage’ (example: EF Missing Phonescreen’) for these applications just to track the progression of the applicant through all stages and stage_groups.

• ‘hired_declined’ is a EF generated stage_group. This accounts for all candidates who decline their offers or are rejected after being advanced to the ‘hired’ stage and these candidates are excluded from the 'hired' stage group.
  • 'Stage group funnel': It's a calculated field which just formats the labels of the stage_groups.