ReQue is an advanced analytics platform built by Untitled Research. It is designed for recruitment optimization and utilizes AI/ML technology to learn from customer outcomes and automatically predicts outcomes for new leads.

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ReQue
Using AI to disrupt and optimize the Recruitment Process
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Presents

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THE MACHINE REVOLUTION
IN BUSINESS
61% of businesses said they implemented AI in
2017, up from just 38% in 2016 (Narrative Science, 2018)
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AI/ML

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Initiatives, have invested in infrastructure to support its scale, and
have clear business goals - achieve 3 to 15% percentage point
higher profit margin. Of the over 3,000 business leaders who were
interviewed as part of the survey, the majority expect margins to
increase by up to 5% points in the next year.
(Source: McKinsey Global Institute, Artificial Intelligence, The Next Digital Frontier)
Higher Profits
McKinsey found that companies
who benefit from senior
management support for AI3-15%
BUSINESSES ARE ADOPTING AI/ML
WHY
A transformative shift from manual tasks performed by
humans to automated processes powered by machines.
EFFORT SHIFT
The most powerful paradigm is a combination of deep
subject matter expertise and data informed decisions.
AUGMENTED INTELLIGENCE
The process of developing and employing advanced analytics
has strategic insight benefits beyond day-to-day ops.
DEEP INSIGHTS
“AI is going to be … as important to companies as cash flow is,” Marc Cuban said. “You have to be good at it or you
won’t be able to compete.”

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RECRUITMENT PROCESS
TYPICAL
Client Needs
Open Requisition
(Lead)
Assessment,
Prioritization &
Assignment
Closure &
Feedback
Leads Fulfillment
Candidate
Sourcing &
Matching
Submission,
Interview,
Selection &
Evaluation
Organizational Effort
80%20%

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© 2018 Untitled Research. All Rights Reserved.
Client Needs
Open Requisition
(Lead/ Opportunity)
Assessment,
Prioritization &
Assignment
Closure &
Feedback
Leads Fulfillment
Candidate
Sourcing &
Matching
Submission,
Interview,
Selection &
Evaluation
Which leads should we invest our fulfillment efforts in?
Which leads give us the best chance to win?

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© 2018 Untitled Research. All Rights Reserved.
Client Needs
Open Requisition
(Lead/ Opportunity)
Assessment,
Prioritization &
Assignment
Closure &
Feedback
Leads Fulfillment
Candidate
Sourcing &
Matching
Submission,
Interview,
Selection &
Evaluation
PIPELINE
EFFORT
TEAM
SEASONALITY
ASSESSMENT
MARGIN
COMPETITION STRATEGY
CAPACITY
CANDIDAT
E
POOL
RISK
PROCESS
ECONOMY
REVENUE
Which leads should we invest our fulfillment efforts in?
INDUSTRY
Which leads give us the best chance to win?

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CASE IN POINT
PRIORITIZATION CHALLENGE
If fulfilment resources are limited, which of these positions
should we work on filling first, second and third?
Client Position Title Industry Date Ordered Contract Rate
Verizon Analyst IT 3/14 6 Months $67
Jefferson Registered Nurse HEALTHCARE 3/1 12 Months $45
StrongSoft Application Developer IT 3/8 3 Months+ $90

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THE RECRUITMENT PROCESS
REIMAGINED
We can systematically learn from the history of
our fulfillment activities and outcomes to help us
make prioritization decisions in the future.
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RECRUITMENT PROCESS
ReQue Feedback Loop Enabled
Client Needs
Open Requisition
(Lead/ Opportunity)
Assessment,
Prioritization &
Assignment
Closure &
Feedback
Candidate
Sourcing &
Matching
Submission,
Interview,
Selection &
Evaluation
1. Learn from historical fulfillment activity and outcomes using advanced analytic
2. Provide predictive insights for Prioritization of new incoming leads

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© 2018 Untitled Research. All Rights Reserved.
CASE IN POINT – ReQue Aided
PRIORITIZATION CHALLENGE
If fulfilment resources are limited, which of these positions
should we work on filling first, second and third?
Client Position Title Industry
Date
Ordered
Contract Rate Placement
Verizon Analyst IT 3/14 6 Months $67 54%
Jefferson Registered Nurse
HEALTHCAR
E
3/1 12 Months $45 79%
StrongSoft Application Developer IT 3/8 3 Months+ $90 12%
ReQue predicting Placement Likelihoo

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RECRUITMENT LEAD
SCORING
Lead scoring is a shared recruitment and
business development process for identifying
the hottest leads for placement-readiness. It is
an invaluable tactic that many companies are
struggling with.
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INCREASE REVENUE
SHORTEN RECRUITMENT CYCLE REDUCE EFFORT & AMPLIFY SUCCESS
PREDICTIVE LEAD SCORING
APPLIED AI
Score recruitment leads in real time to determine their potential value and
optimize effort by focusing on opportunities that are most likely to result in
desired outcomes. All based on your own data and history.
CONVERT MORE LEADS FASTER
Spend less time chasing positions that score very
low in terms of placement likelihood.
Focus on filling positions with the highest
likelihood to place and revenue potential.
IMPROVE CONVERSION RATE
By continuously focusing on placements with highest chance of
success, key clients and business drivers get the attention they deserve.
Understand impact of certain staff, clients and conditions
on placement rate and employ strategies to optimize.

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LEAD SCORING IN RECRUITMENT
EXTERNAL
DATA
YOUR
DATA
LEARNING
SCORED
JOB
ORDER
SEGMENTATION
SORTING
PRIORITIZATION
NEW JOB
ORDERS
ACTION
LEAD SCORING
HOW DOES IT WORK - FLOW
MODELS

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Likelihood that this
opening will become
abandoned.
Abandonment Risk
Likelihood that this
opening will be filled by
a competitor first.
Competition Risk
Likelihood that this
opening will be canceled
by client.
Cancelation Risk
Likelihood client will be
satisfied with this
placement, or predicted
satisfaction rating.
Placement Satisfaction
Likelihood that candidate
will be placed.
Placement Likelihood
Percent of profit
generated by placement.
Profit %
Total revenue generated
by placement.
Revenue
Likelihood that interview
will be scheduled.
Interview Likelihood
OUTCOME METRICS
LEAD SCORING
ReQue can predict a variety of outcome metrics from the standpoint of a new incoming job order, based on existing user history of outcomes.
X
$ %

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© 2018 Untitled Research. All Rights Reserved.
CASE IN POINT – ReQue Aided
PRIORITIZATION CHALLENGE
If fulfilment resources are limited, which of these positions
should we work on filling first, second and third?
Client Position Title Industry
Date
Ordere
d
Contract Rate
Placemen
t
Profit Revenue
Verizon Analyst IT 3/14 6 Months $67 54% 38% $72K
Jefferson Registered Nurse
HEALTHCA
RE
3/1 12 Months $45 79% 24% $113K
StrongSof
t
Application
Developer
IT 3/8 3 Months+ $90 12% 42% $103K
ReQue predicting Placement Likelihood, Profit % and Total Reve

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BROAD BENEFITS OF AI/ML
In addition to in-line practical decision support,
there are broad benefits delivered by the ReQue
predictive models that transform business
strategy.
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LEAD SCORING IN RECRUITMENT
INSIGHTS – TYPICAL SIGNALS
ReQue lead scoring models provide insights into key driving factors of outcomes, their
strength relative to each other and relationship to outcomes. These insights enable deep
organizational understanding of the importance of these characteristics in a job order.
Remember the mess of concerns affecting our prioritization decision before? They are much
easier to think about when organized and sorted.
PIPELINE TEAM
SEASONALITY ASSESSMENT
MARGIN
COMPETITION STRATEGY
CAPACITY
CANDIDAT
E
POOL
RISK PROCESSECONOMY
INDUSTRY
24%
13%
31%
Lead Placement Rate: Industry
FINANCIAL HEALTH IT
54%
Predictive Signal Strength: Industry

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$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
Jan Feb Mar Apr May Jun Jul Sep Oct Nov Dec
Placements Earnings
1
8
23
39
29
0.5
5.0
12.0
30.0
50.0
1 2 3 4 5
Effort Applied (%)
Return on Effort (%)
Strategic Insights
Predicted Likelihood of Placement – by Category Rating
26%
22%
% of Jobs Not Worked
LEAD SCORING IN RECRUITMENT
ReQue strategic insights enable overview of recruitment activity in the context of the predictive assessment to enable understanding of efficiency gaps
and opportunities for effort re-allocation.

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© 2018 Untitled Research. All Rights Reserved.
FAQ
What is the most effective way to adopt predictive capability?
Predictive systems perform the best when paired with human expertise. So the two
biggest keys to successful adoption are (1) cross-organizational exposure and (2)
measured roll-out with clear goals and feedback loops.
PATH TO ADOPTION
What is the risk associated with employing a system like JEMS?
Part of the consideration has to be the possibility that any given prediction may be
incorrect, there is always an element of risk. The key is to understand and quantify the
risk with a controlled and measured rollout to collect real performance data which will
inform the long-term risk mitigation strategy: a thoughtful business process that
effectively pairs automated predicted intelligence with human expertise.
BUSINESS RISK
Can the models be trusted ?
Thousands of models were build during the project using various perspectives to
accommodate the breadth and complexity of the data. Over 700 data points were
tested. The current generation of models reflect a solid balance between fit and
generalization, and meaningfully tracks with key outcomes in testing.
MODEL EFFECTIVNES & ACCURACY
Can the solution scale and keep my data secure ?
Solution leverages the latest technologies available for packaging application
(containers) and is designed with scalability and security in mind. It can be
deployed on premise or on cloud for the ultimate scalability and flexibility.
SCALING & SECURITY
Will these models still be relevant as my business grows and
evolves?
The models can be refreshed periodically to adopt to latest data. This process can be
automated and the system can learn continuously. The scores generated by the
model can further be used to derive custom metrics weighted by optimization factors
to align with business goals.
ADOPTION TO CHANGE
How can I integrate the solution into existing IT infrastructure ?
APIs make it possible to easily infuse predictive intelligence directly into existing
IT systems. Real time scoring enables a job order to be automatically analyzed at
any time with new or changing information.
IT INTEGRATION

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CEO/FOUNDER
Anthony Leshinsky
Strategy + Data Science
ABOUT ANTHONY
Advanced analytics maven. Specializes in
practical application of advanced data science
techniques to help companies practically
employ data science to drive outcomes.
Content
Valuation
Data
Products
Data
Science
CTO/FOUNDER
Miroslav Maráz
Data + Technology
The Architect
ABOUT MIRO
Data technology and architecture expert.
Highly skilled and creative in designing high
performance/efficient systems for unique
business challenges.
Technology DataArchitecture
Meet the Team
Untitled Research, LLC.
The Scientist

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THANK YOU !
@UntitledResearch UR_Philly untitled-research.com