5 Hidden

Sales Forecast

Killers

#1 Staffing Analytics

Contents

Introduction

Sales Forecasting 101: Getting Started

Beware of These 5 Forecast Killers

Job Order Age

Job Order Value

Momentum

Stage

Client

The Next Level of Forecasting and Analysis

3

5

7

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9

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11

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5 Hidden Sales Forecast Killers // 2

Introduction

Staffing and recruiting executives know that the lifeblood of their business lies in their firm’s ability

to source and place candidates as efficiently as possible. When it comes to hitting their goals and

impacting the bottom-line, staffing executives must be able to project a consistent and accurate

forecast of how much business they will close during a given selling period.

Though the most competitive staffing and recruiting firms use Applicant Tracking Systems

(ATS) to collect data and manage their daily sales processes, less than five percent of all

businesses are taking advantage of data to make better decisions1. Most staffing and recruiting

firms are missing the mark on a critical competitive advantage when it comes to using data to plan

for the future.

Staffing firms that want to grow and deliver predictable revenue need to move beyond a model

that simply tallies previously closed business, and must instead use their historical and current

ATS data to create a more accurate sales forecast that estimates how much business they will

close each selling period.

This Guidebook covers where to get started with sales forecasting for staffing and

recruiting and some common forecast killers to beware of when implementing a data-

driven sales forecast.

5 Hidden Sales Forecast Killers // 3 1 Competing on Analytics: The New Science of Winning, 2007, Thomas H.

Davenport, Jeanne G. Harris, Harvard Business School Press

Chapter 1

Sales Forecasting 101:

Getting Started

Sales Forecasting 101: Getting Started

When it comes to forecasting, the best firms do not rely on their sales reps to tell them how they

“feel” about their open job orders. Traditional forecasting methods like this rely too heavily on the

subjectivity of the rep doing the analysis. Instead, staffing executives and sales coaches should

rely on data to tell the story.

There are some basic variables to consider when building out a forecast that relies on data

already stored in your ATS. The first elements to consider and calculate when getting started are:

• How much new business do we anticipate we will generate this selling period (generally this

week, month, or quarter)?

• What do we currently have in our pipeline that is expected to close?

• What have we already booked this sales period?

Begin your initial data-driven forecast by developing simple benchmarks around win rates and

opportunity age, and start to apply a formula to your open job orders on a weekly or monthly

basis. Compare this forecast to your sales reps’ predictions about what business they will close,

and you should begin to see that this basic data-driven forecast delivers a more consistent and

accurate prediction than your sales reps can estimate based on their “gut.”

If you’re interested in learning more about the steps to creating a data-driven sales forecast, read

this guide.

5 Hidden Sales Forecast Killers // 5

Chapter 2

Beware of These 5

Forecast Killers

Beware of These 5 Forecast Killers

Once you are forecasting regularly (and meeting with sales reps each week to stress-test their

personal forecasts) you can take your forecasting accuracy to the next level by considering some

key elements that affect almost every open job order:

5 Hidden Sales Forecast Killers // 7

Client Stage

Momentum Value Age

Forecast Killer #1 – Job Order Age

Unless your staffing and recruiting firm focuses on longer-term executive searches, chances are

that, like most sales cycles, the longer a job order stays open in your system, the less likely it is to

close.

When analyzing whether a job order will close this sales period, consider how long the job

order has been open and compare it to the average age of job orders that you win. In the

2013 Fill Ratios and Time-to-Fill Benchmarking Report co-produced by Staffing Industry

Analysts and InsightSquared, the average time-to-fill for contract placements was 46 days and 75

days for permanent placements.

For a contract hire firm, for example, a job order that is currently 110 days old (almost 3x the

average) and is forecasted to close during this selling period should be closely examined by the

sales rep and their manager to tell if it is really a “winnable” opportunity. When the data suggests

otherwise, an open, unwinnable job order like this puts your sales forecast (and your business) at

risk for the month or quarter.

Action Plan: Set business-specific benchmarks around average job order age (bonus:

understand if specific industries you service have shorter or longer time-to-fill cycles) and

pressure-test reps on outlying job orders that are forecasted to close in a given selling period.

5 Hidden Sales Forecast Killers // 8

Forecast Killer #2 – Job Order Value

When forecasting properly, consider a job order’s value when assessing how likely it is to close.

Though there may be many reasons you excel in a filling job orders of a certain value range—your

team is great at filling reqs for particular positions or industries, for example—every staffing firm

has a core competency, and some job orders of similar composition and value will have higher

likelihoods of closing. Use your ATS data to determine what your optimal “strike zone” is for job

order value.

Group your job orders by value to understand where your “sweet spot” is. This way, when

sales reps report positively about a high value job order they’re hoping to fill this month, you will

know how likely you are based on historical data, to fill a job order like this.

Action Plan

Compare win rates by value for average value, larger and smaller value job orders to start to

understand how likely you are to close each value range based on historical data. Then, adjust

your forecast based on your past win rates by value to improve your accuracy.

5 Hidden Sales Forecast Killers // 9

Forecast Killer #3 – Momentum

One of the best indicators of how well a job order is progressing is the activity your team is

logging against it: how many internal submissions, sendouts, and interviews has it received? How

active are both recruiters and sales reps at logging activities against it? In an industry where 57%

of candidates who are actively placed are submitted within the first 24 hours of an open job order2,

having a stagnant job order is a huge red flag.

When reviewing job orders that are forecasted to close check to see when the last time an

employee logged an activity on this job order. If a job has stalled but you are still including it in

your monthly bookings forecast, you are likely putting your firm at risk for missing its numbers and

should consider removing it from your forecast.

Action Plan: Determine what a “stalled” job order looks like by knowing your average time-to-fill

by stage. Have reps quickly reach out to resuscitate these job orders or purge them from your

pipeline to remove these liabilities from your forecast.

5 Hidden Sales Forecast Killers // 10 2 “The Ultimate Revenue Roadmap,” Bullhorn, Inc., 2013

Forecast Killer #4 – Stage

Another major variable that you need to consider is the “stage” of the job order in your pipeline.

Accurate forecasts differentiate early-stage job orders (internal submission) from later-stage job

orders (interview) when predicting what business will close in a given selling period. Are you

assigning the same likelihood to close to both?

Look at historical data in your ATS to see what percentage of open job orders you fill by

stage, and make sure you weigh these stages accordingly when considering them in your

forecasts. An open job in an early stage is far less likely to close compared to a job order that has

sent out candidates to the client and received requests for interviews.

Action Plan: Determine your win rate by stage and assign win rate values to each stage in your

forecast. This way, you can rely on historical performance to weight your likelihood to close every

open job order.

5 Hidden Sales Forecast Killers // 11

Forecast Killer #5 – Client

The final forecast killer you should consider might be less obvious: your clients. Though you may

know who your top one or two clients are from a bookings perspective, do you know which of your

clients are the most efficient at accepting candidates?

In order to know whether a job order you are forecasting to close will do so during a given

selling period you should know how efficient the client you are working with is. How many

sendouts does this client usually request before they will take an interview? How long do their

searches generally take? Are they in an industry, like Healthcare & Life Sciences, that can take

between 40 to 100% longer to fill than average?3

Action Plan: Analyze your time-to-fill by individual client. If you are forecasting to close a job

order in 30 days but a particular client generally takes 90 days, update your forecast to reflect this

or ask your rep for a quantitative reason that this job order will be different than past data

suggests.

5 Hidden Sales Forecast Killers // 12 3Staffing “Recruitment Metrics” Data Analysis: Fill Ratios and Time-to-Fill

Statistics, Staffing Industry Analysts, 2013

The Next Level of Forecasting and Analysis

Now that you have a better understanding of which elements can impact a consistent and reliable

sales forecast, start small by choosing one to two of the biggest variables in your sales cycle and

including them in your weighted forecast.

All of the data you need to start making educated and accurate forecasts is already at your

fingertips in your ATS. Get started either by downloading and building metrics-based models in

spreadsheets or by considering an ATS analytics tool to pivot in and analyze data more easily.

After implementing and customizing your forecasts based on your own historical data, your firm

will begin to see the benefits of a data-driven forecast: fewer surprises, more consistent and

predictable results, and ultimately increased revenue from insightful forecast analysis.

5 Hidden Sales Forecast Killers // 13

#1 for Staffing Analytics

About InsightSquared

InsightSquared is the #1 Analytics product for Staffing & Recruiting firms. Unlike

legacy Business Intelligence platforms, InsightSquared can be deployed

affordably in less than a day and comes preloaded with reports that staffing and

recruiting firms need. Hundreds of companies and thousands of users around the

world use InsightSquared’s award-winning analytics to maximize sales

performance, increase team productivity and close more business.

10 Must-Ask Performance

Questions for Staffing and

Recruiting