🚇 On this page: Instructions on how to configure and test different headcount growth scenarios.
Related pages:
Overview
Are you looking to meet your headcount growth expectations in the upcoming months? People Analytics Headcount Scenario Planning tool can help you achieve your goals by allowing you to play with different parameters that affect headcount growth. By simulating future outcomes, you'll be able to identify the steps you need to take to meet your growth expectations.
Headcount Scenario planning basics
The Headcount Scenario Planning tool extends your Headcount Growth Rate graph into the future, showing you two distinct projections:
a baseline prediction extrapolated from existing trends in your data
a customized projection you create by specifying parameters that simulate a different scenario
Access Headcount Scenario Planning tools
Your starting point is in the Headcount chapter:
From the Headcount chapter, navigate to the Headcount metric:
Click the Targets label at the bottom of the graph:
The Target-setting and Scenario-planning tools will be revealed below.
Create Headcount Growth scenarios
The Scenario Planning Tool consists of a set of input fields and sliders to set targets and simulate future scenarios.
The elements are grouped into three sections:
Targets
Current trends
Inputs
Targets
This is where you set your desired target headcount growth rate.
The target you set will be shown on the graph as a horizontal dashed line. When you change the target value, the target line on the chart will reflect the change.
🚉 If you need help with setting, monitoring, editing or deleting targets, see:
Current trends
This is where you set the scope of your projection: how many months ahead your scenario will consider.
When you set the value of this parameter, it creates a baseline prediction. The Headcount Growth Rate bar chart will extend into the future, based on the assumption that the trends in the underlying data will continue to hold.
The projected values will appear as a sequence of transparent green bars, to distinguish them from your actual data.
Inputs
The Inputs section is the heart of the Scenario Planning tool. It is a set of four input fields and sliders that represent parameters you can play with, to simulate how different values will affect your future headcount growth rate.
Available Inputs:
Number of recruiters - number of employees who will be actively spending time on recruiting for open positions,
Number of open positions - number of new positions that need to be filled or cut (can be positive or negative),
Monthly turnover - a percentage of existing employees who will leave each month,
Time to start - number of days it’ll take our new employees on average to start,
Recruiter productivity - number of hires per month per recruiter.
By default, the input fields are populated with actual current values for your organizations.
By changing the preloaded inputs (orange rectangle area on the image below) the projected outcome will be visualized on the chart as a a sequence of pink transparent bars right alongside the baseline prediction.
How People Analytics calculates projections
The Headcount Calculation Algorithm shows you two different projections of the future: a baseline prediction based on current trends in your data, and a customizable projection based on parameters you set, to simulate an alternative scenario.
Baseline prediction (”Show me the future for X months”)
The baseline prediction is created when you set the Show me future parameter, which specifies how far ahead into the future you want to project your current data.
Each subsequent month’s headcount value is calculated by multiplying the previous month’s headcount by turnover (”Inputs → Monthly Turnover” which has a default value that can be read from scenario_defaults API call) and rounding to the closest integer.
Baseline prediction pseudocode
# Convert monthly turnover into a turnover percentage turnover_percentage = monthly_turnover / 100
# Run turnover calculation for the number of months we’re doing forecasting for for i in show_me_the_future_for_X_months: headcount [end_month + (i + 1)] = headcount [end_month + i] * (1 - turnover_percentage)
Scenario prediction
This Scenario projection is extrapolated from the variety of Input parameters you enter, showing you how different values would affect future outcomes.
Scenario prediction pseudocode
# Convert monthly turnover into a turnover percentage turnover_percentage = monthly_turnover / 100
# Run turnover calculation for the number of months we’re doing forecasting for # on existing employees only turnover_percentage = monthly_turnover / 100
# Run turnover calculation for the number of months we’re doing forecasting for # on existing employees only for i in show_me_the_future_for_X_months: old_headcount [end_month + (i + 1)] = old_headcount [end_month + i] * (1 - turnover_percentage)
# Calculate when will open positions be filled present = now()
dates_new_headcount = empty_array
total_monthly_recruiter_capacity = number_of_recruiters * recruiter_capacity
while number_of_open_positions > 0: new_headcount_for_the_month = min( number_of_open_positions, total_monthly_recruiter_capacity)
present = present + time_to_start
dates_new_headcount.append([present] * new_headcount_for_the_month)`
number_of_open_positions = number_of_open_positions - new_headcount_for_the_month
# Calculate the number of new employees for each month for i in show_me_the_future_for_X_months: new_headcount [end_month + (i + 1)] = Hey, take_same_month_head(dates_new_headcount)
# Calculate total headcount for i in show_me_the_future_for_X_months: headcount [end_month + (i + 1)] = old_headcount [end_month + (i + 1)] + new_headcount [end_month + (i + 1)]
Examples
Example with a positive Number of Open Positions
Inputs:
Number of Recruiters: 3
Number of Open Positions: 20
Monthly Turnover: 6%
Time to Start: 100 days
Recruiter Capacity: 2
Headcount for February: 110
Running scenario planning on March 1st.
Baseline prediction for the next 6 months (headcount):
March: 110 * (1 - 0.06) = 110 * 0.94 = 103.4, rounded to 103
April: 103.4 * 0.94 = 97.2, rounded to 97
May: 97.2 * 0.94 = 91.36, rounded to 91
June: 91.36 * 0.94 = 85.88, rounded to 86
July: 85.88 * 0.94 = 80.73, rounded to 81
August: 80.73 * 0.94 = 75.89, rounded to 76
So, current trends, ie. pink prediction bars in scenario planning mode would be: 103, 97, 91, 86, 81, 76.
Scenario prediction for the next 6 months (headcount):
Total monthly recruiter capacity = 3 (number of recruiters) * 2 (recruiter capacity) = 6, ie. 6 new employees each month.
In March: 6 new employees, which will start March, 1st + 100 days = June, 9th
In April: 6 new employees, which will start April, 1st + 100 days = July, 10th
In May: 6 new employees, which will start May, 1st + 100 days = August, 9th
In June: just 2 new employees (20 - 3 * 6), which will start June, 1st + 100 days = September, 9th
Adding new employees with baseline prediction, ie. old employees:
March: 103 + 0 = 103
April: 97 + 0 = 97
May: 91 + 0 = 91
June: 86 + 6 = 92
July: 81 + 6 = 87
August: 76 + 6 = 82
So, scenario prediction, ie. green prediction bars in scenario planning mode would be: 103, 97, 91, 92, 87, 82.
🚇 Additional resources and next steps
🚑 Data Health 101 (to ensure the data in your insights is valid)
📖 Stories and Chapters 101 (for an overview of available metrics for your reports)
💬 Need further help? Just reply with "Ask a Person" in a Support Conversation to speak with a Product Support Specialist.