This document discusses forward-looking and predictive metrics that can be used for recruiting. It begins by defining key terms like historical, real-time, and predictive metrics. It then discusses reasons for using traditional metrics, such as increased business results when data-driven decision making is used. Examples of predictive recruiting metrics are also provided, such as predicting changing source effectiveness and upcoming talent availability. The document concludes by outlining elements that make a predictive metric actionable, such as listing revenue impact and recommended actions.
15 High Value Action Steps… To Elevate Your Employee Referral Program To The ...Dr. John Sullivan
What does “the next level up” look like for Employee Referrals
- Volume > 50% of all hires
- ERP produces highest quality hires
- The highest retention rate
- The shortest time to fill
- Over 30% of top performers participate in the ERP
- < 10% low-quality referrals
- Below average cost per hire
How to use People Analytics to Shape Employee ExperienceTareef Jafferi
From PMAT HR Day 2019, Bangkok Thailand by Tareef Jafferi
Key Takeaways:
1. Key moments in your Employee Experience
2. Getting started with People Analytics
3. Learnings from 4 Case Studies
4. Quick Wins
5. Can Happily.ai help you?
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Methodology
A total of 4,622 workers who find work opportunities via the platforms provided by the participating partner companies completed an online survey between September 11 and October 1, 2015. The results were weighted to reflect the proportion of workers in each of the following segments: Drivers/Delivery, Online Talent Marketplaces and Field Service/Onsite Talent. The weights were developed using earlier survey work that sized the on-demand economy. The largest weighted share of on-demand worker respondents from any single company is 16%, with most partner companies providing less than 10% of the respondents.
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Webinar: How to Create the Ultimate Employee ExperienceYouEarnedIt
Is your company getting the most from its employee experience efforts?
Join us for a 45-minute webinar on building employee experiences that deliver business results.
The term "employee experience" is everywhere today, and its importance goes beyond mere buzzword status and HR circles. Employee experience programs are driving bottom-line results — one recent study found companies that invest in the employee experience are four times as profitable than those that don't.
Join YouEarnedIt's CEO and Director of Employee Experience for this 45-minute webinar guiding you through our most important discoveries from hundreds of research pages and thousands of employee surveys.
Watch for this webinar, and you will see:
The employee experience defined — learn exactly what the employee experience is, and how it can be tailored to your culture.
The employee experience quantified — get research-backed stats revealing how the employee experience boosts your bottom line, helping you build a business case for it.
The employee experience optimized — tips, tactics, and best practices based on survey data and successful companies for building a best-in-class employee experience.
Copy of a presentation delivered at the 3rd HR Analytics, Metrics and Measurement Conference, sharing some of the key lessons, tips and mistakes I have learned during two decades managing Human Resources, Workforce Planning and HR Analytics programs.
15 High Value Action Steps… To Elevate Your Employee Referral Program To The ...Dr. John Sullivan
What does “the next level up” look like for Employee Referrals
- Volume > 50% of all hires
- ERP produces highest quality hires
- The highest retention rate
- The shortest time to fill
- Over 30% of top performers participate in the ERP
- < 10% low-quality referrals
- Below average cost per hire
How to use People Analytics to Shape Employee ExperienceTareef Jafferi
From PMAT HR Day 2019, Bangkok Thailand by Tareef Jafferi
Key Takeaways:
1. Key moments in your Employee Experience
2. Getting started with People Analytics
3. Learnings from 4 Case Studies
4. Quick Wins
5. Can Happily.ai help you?
Dispatches From The New Economy: The On-Demand Economy And The Future Of WorkIntuit Inc.
From delivery, transportation and household errands, to professional services and consulting, the on-demand economy is changing the way people consume goods and services. It is also changing the way people work. Intuit and Emergent Research forecast that the number of people working on-demand jobs will grow from 3.2 million Americans to 7.6 million by 2020. This is a once in a generation opportunity to empower the future of work and a new face of entrepreneurship.
Dispatches from the New Economy: The On-Demand Workforce provides a detailed analysis of the demographics, motivations and challenges of workers pursuing on-demand jobs. The data comes from a study from Intuit and Emergent Research that examined people working via eleven on-demand economy and online talent marketplace companies. Study participants included: Deliv, Field Nation, HourlyNerd, MBO Partners, OnForce, Uber, Upwork (formerly Elance-oDesk), Visually, Wonolo, and Work Market.
Methodology
A total of 4,622 workers who find work opportunities via the platforms provided by the participating partner companies completed an online survey between September 11 and October 1, 2015. The results were weighted to reflect the proportion of workers in each of the following segments: Drivers/Delivery, Online Talent Marketplaces and Field Service/Onsite Talent. The weights were developed using earlier survey work that sized the on-demand economy. The largest weighted share of on-demand worker respondents from any single company is 16%, with most partner companies providing less than 10% of the respondents.
PWC Report on the Future of Work: Disruptive innovations are creating new industries and business models, and destroying old ones. New technologies, data analytics and social networks are having a huge impact on how people communicate, collaborate and work. As generations collide, workforces become more diverse and people work longer; traditional career models may soon be a thing of the past. Many of the roles and job titles of tomorrow will be ones we’ve not even thought of yet.
This report, conducted by an independent research firm and commissioned by Upwork, uses data from two surveys of U.S. hiring managers: one fielded in November 2019 prior to the COVID-19 crisis, and the other fielded during the crisis in April 2020. The surveys polled a combined 1,500 U.S. hiring managers to provide a holistic picture of workforce trends impacting business organizations. Find out how companies are building for the future.
Webinar: How to Create the Ultimate Employee ExperienceYouEarnedIt
Is your company getting the most from its employee experience efforts?
Join us for a 45-minute webinar on building employee experiences that deliver business results.
The term "employee experience" is everywhere today, and its importance goes beyond mere buzzword status and HR circles. Employee experience programs are driving bottom-line results — one recent study found companies that invest in the employee experience are four times as profitable than those that don't.
Join YouEarnedIt's CEO and Director of Employee Experience for this 45-minute webinar guiding you through our most important discoveries from hundreds of research pages and thousands of employee surveys.
Watch for this webinar, and you will see:
The employee experience defined — learn exactly what the employee experience is, and how it can be tailored to your culture.
The employee experience quantified — get research-backed stats revealing how the employee experience boosts your bottom line, helping you build a business case for it.
The employee experience optimized — tips, tactics, and best practices based on survey data and successful companies for building a best-in-class employee experience.
Copy of a presentation delivered at the 3rd HR Analytics, Metrics and Measurement Conference, sharing some of the key lessons, tips and mistakes I have learned during two decades managing Human Resources, Workforce Planning and HR Analytics programs.
50 HR & Recruiting Stats Talent Acquisition Pros Need to Know Recruiting Webi...RecruitingDaily.com LLC
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But sourcing the latest and greatest metrics in each category to make the business case for recruiting initiatives and strategies is a chore.
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Your Glassdoor Profile: How to Use It To Your AdvantageGlassdoor
Your Glassdoor Profile: How to Use It To Your Advantage
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Big Data = Big Headache? Using People Analytics to Fuel ROItalent.imperative
• Interpret trend information to understand the business case for Big Data in HR.
• Examine your fears and assumptions about Big Data.
• Learn from best practice case studies how to demonstrate HR’s contributions to ROI.
• Understand how to engage key stakeholders as part of your organization’s people analytics journey.
Enabling Success With Big Data - Driven Talent AcquisitionDavid Bernstein
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Workforce Insight And Change Making Comms V4 AaAladam
These slides provide an overview of how to do Workforce Planning & Analytics so leaders can make better, more informed decisions. Hope you like it!
Workforce analytics, also called HR analytics or people analytics is getting much attention lately. And rightly so! Research has shown that companies using data to drive their decisions and actions are more succesfull than others. With (predictive) analytics an accurate view of the future requires predictions based on data rather than personal hunches or speculation.
Machine Learning for Business - Eight Best Practices for Getting StartedBhupesh Chaurasia
Though the term machine learning has become very visible in
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Predictive Hiring: Find Candidates Who Will Succeed in Your OrganizationHuman Capital Media
The facts are clear: Most companies today need to do a better job selecting talent. Recent survey data collected by the Corporate Executive Board indicates that nearly a quarter of all new hires leave their companies within a year, and that hiring managers wish they never extended an offer to one of every five members of their team. And a recent Gallup survey found that 52 percent of American workers were “not engaged” with their work.
Can you afford to miss an opportunity to learn how best-in-class organizations are using new technologies to scientifically assess talent before hiring, resulting in lower turnover, higher job performance and greater employee engagement?
In this presentation, you will:
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Discover how best-in-class organizations are incorporating these new solutions into their hiring process.
See the bottom-line results realized by these best-in-class practitioners.
Technology has given birth to the latest disruption of Human Resources. Artificial intelligence. Virtual Reality. Data analytics. The list goes on.
Embrace The Tech Disruption explores:
- The use of Artificial Intelligence
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- The impact of the tech disruption on company budgets
- Technology solutions to day-to-day HR activities
Data has changed the way we work and live, and the way HR acquires data has changed. But data alone isn't enough - it needs to be compelling. Here's how PeopleTree used meaningful data to help clients navigate succession management, digital transformation, predictive performance, and talent loss.
Predicting Your Employees. Digitalize, DIGITALIZE, even your ‘Human Workforce’! Predict your employees in 4 ‘clicks’. Make decisions based on data. Accurate people management decisions are based on data. Why should yo do it? How to do it ? Do it now.
Living in a data economy: Transforming the role of HRMartin Sutherland
In a data economy, wealth is defined by extracting value from good quality data. The challenge is how to ensure a sustainable source of good quality HR data and how to turn that data into a compelling story that engages business leaders and creates a competitive advantage through talent.
Better Living Through Analytics - Strategies for Data DecisionsProduct School
Data is king! Get ready to understand how a successful analytics team can empower managers from product, marketing, and other areas to make effective, data-driven decisions.
Louis Cialdella, a data scientist at ZipRecruiter, shared some case studies and successful strategies that he has used at ZipRecruiter as well as previous experiences. The purpose of this data talk was to enlighten people on how to make sure that analysts can successfully partner with other departments and get them the information they need to do great things.
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7. 2
I’m from the Silicon Valley…
So they asked me to highlight the most advanced
predictive metric practices in the world
Obviously you can’t adopt all of the leading-edge
metrics, but you should still be aware of them
So pick, choose and adapt whatever elements that
you find are best for your firm
8. 3
Topics we will cover today…
1. Introduction a nd some definitions
2. Reasons for using traditional metrics
3. Reasons for using predictive metrics
4. Examples of predictive metrics in
recruiting
5. Implementing predictive metrics
9. Part I
An introduction and some quick metric
4
related definitions
10. 5
Everyone else already “lives” metrics
“In God we trust, everything else we measure”
--VP of HR, UPS
11. 6
Some quick simplified definitions
1. Historical metrics – measures that focus on
reporting things that have already occurred
2. Workforce Analytics – a set of integrated
capabilities to measure, analyze, identify trends
and to improve workforce performance
3. Real-time metrics – reporting or monitoring
metrics that cover what is happening now
4. Predictive metrics – using past and current data to
forecast trends and upcoming problems/opportunities
5. “Why” analysis – a process for identifying what
causes things to happen (the root causes)
6. A scorecard – results listed on 1 sheet (Balanced)
12. 7
Some quick simplified definitions
7. A dashboard – an array of metrics, that in a single
view, covers all of the key functional measures
8. An index – numerous metrics converted to a single
number for ease of comparison (i.e. Dow Jones)
9. Business Intelligence (BI) – the executive term for
information for improving business decisions
10. Showing revenue impact – converting standard
HR metrics to their dollar impact on revenue
11. Big data – huge, changing and complex data
sets that can’t be easily analyzed using traditional
software
13. 8
Predictive analytics
Predictive analytics are more common outside of HR
Ø Weather forecasting – government and private
weather services predict weather patterns that will
create problems and provide business opportunities
Ø Predictive policing – many modern departments now
have algorithms and models that can predict where
and when crimes are likely to occur
Ø Insurance algorithms – all major insurance firms
have predictive models that forecast health problems
for segments of the population
Ø Supply chain/consumer functions - within the
business, these functions excel at predictive analytics
Ø Politics – Nate Silver proved their value here
14. Illustrations of data based recruiting
compared with traditional recruiting
TRADITIONAL TA
DATA DRIVEN TA
I know
Real-time/ predictive metrics
I test new ways with data
I have data/ analysis to prove it
Our firm’s data shows it works
Data / facts speak the loudest
Informed people decide
Failure analysis stops repeating
Productivity/bus goal advocate
9
I think, I believe or I feel
Use only historical metrics
I rely on past practices
My gut / heart tells me
I once saw this program fail
Political power triumphs
A consensus decides
We accept failure
An employee advocate
15. 10
Part II
Let’s highlight…
Reasons for using traditional metrics
16. #1 - The use of analytics increases business results
11
(source: Harvard Business Review)
A dvanced user firms that most effectively managed
their workforce… using analytics… produced
higher business performance %’s in these key areas
% increase in performance by advanced users
17. 12
#2 – Most business functions have already shifted
to data-based decision-making
% that are advanced users % that are non-users
Finance 58% 7%
Executive team 51% 11%
Operations 48% 9%
R&D 44% 23%
Marketing 41% 16%
Sales 34% 20%
HR 27% 23%
Learning: compared to HR, Finance has 2X the
advanced users and 3x fewer nonusers
Source: AMA/i4cp 2013
18. #3 – Much TA gut decision-making may be wrong
Google… is the benchmark data-based firm
Ø “We want people management decisions to reach
the level of engineering decisions” (People analytics group)
Ø “Part of the challenge with leadership is that it’s
very driven by gut instinct…
and even worse, everyone thinks they’re really
good at it” (hiring)
Ø Google used data to eliminate any “gut instinct”
decisions… on the hiring criteria that best
predict success on-the-job
13
19. These Google data points…
might change what you think you know about hiring
Ø “GPA’s
Ø “Test scores
Ø “Brainteasers
Ø Interviews – “many managers, recruiters, and HR
staffers think they have a special ability to sniff
out talent. They’re wrong”
“it’s a complete random mess”… “we found a
zero relationship” (between interview scores and on-the-job performance)
No value is added “after 4 interviews”
Ø College –“the proportion of people at Google
without any college education… has increased over time”
Ø What predicts across all jobs? – “learning ability”
14
are worthless as a criteria for hiring”
are worthless”
are a complete waste of time”
Laszlo Bock, Senior VP of people operations at Google The New York Times
20. Reason #4 - Metrics influence managers to change
Ø “The best thing about using data to influence
managers is… it’s hard for them to contest it.
For most people, just knowing that information…
causes them to change their conduct” (Google)
15
Ø Analytics are a must at an engineering-focused
company…
“appealing to emotions instead of logic "is not
going to work –
You need data" (Tesla)
21. #5 -Metrics reveal which programs have the
highest business impacts (BCG)
Which TM functions have the highest business impact?
Source: BCG/WFPMA - From Capability to Profitability: Realizing the Value of People Management, 2012 16
22. #6 – Metrics reveal what is working / not working
What source produces the best applicants / hires?
Ø Although only 7% of applicants come from
referrals, they produce 40% of all hires
Ø Between 14% to 25% of referrals are hired…vs.
1% from among all sources combined
Ø Referrals have the highest interview to hire ratio
(17% of referrals are interviewed)
Hiring speed - they have the fastest “time to fill” of
all sources, a 48 % lower time to fill (29 compared to 45 days)
Hiring cost – 58 % lower than other sources
Quality of hire – referrals are ranked #1
17
23. #7 - Realize that HR is not very good at analytics
What % of CEO’s are confident in the quality
of Human Capital metrics?
18
What would be an ugly%?
Source: AICPA survey 12%
24. Of the 13 major areas of HR performance…
19
where do metrics rank? (KPMG)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10
.
11
.
#12 & #13
25. 20
Part III
Now let’s shift to…
The reasons for using
predictive HR metrics
26. 21
What’s wrong with HR metrics?
Unfortunately, reporting “yesterday’s results”
adds little value
Almost all HR metrics report history, because they
tell you what happened last quarter or even last
year… which may be irrelevant in a fast-moving
world
Examples
Ø Last year’s most effective source
Ø Last year’s quality of hire
Ø Last year’s time to fill
27. 22
10 reasons why you need predictive metrics
1. Today TA is reactive – requisitions open up with
little warning and we mostly source for current
openings
In the future we will need a talent pipeline – in
the future we will begin sourcing in key jobs long
before an opening occurs. “Pre-need” sourcing
will give us more time to find and sell prospects
and to make offers whenever “not-looking
prospects” become available
28. Reasons to utilize actionable predictive metrics
An illustration – a turnover “alert” for recruiting
Ø Our turnover prediction metric suggests that Ms.
X, the head of sales has a 87% chance of quitting
within three months
Ø Because his new sales project was just rejected
Ø Because he recently updated his social media
profile and his resume/ CV was just posted on a
job board
Recommended recruiting actions
Ø Start sourcing now… so that we will have a pool
of qualified and interested candidates if he leaves
23
29. 24
More reasons to utilize predictive metrics
2. Predictive metrics make you aware of shifts in
historical patterns (where existing practices will no longer work)
3. Predictive metrics make you aware of upcoming
recruiting problems when they can still be
mitigated or prevented
4. Predictive metrics alert you to upcoming changes
in environmental and business factors
5. Your “time to act” may be reduced
6. An opportunity to be strategic & forward-looking
7. Increasing the odds that decision-makers will act
because they get “an alert”
30. 25
Reasons to utilize actionable predictive metrics
More reasons to utilize Predictive Analytics
8. Predictive metrics can provide time to “model”
different actions
9. Predictive metrics can provide your firm with a
competitive advantage
10. Predictive metrics will improve both the
accuracy and the impact of recruiting decisions
31. 26
Part IV
What do forward-looking recruiting
metrics look like?
32. Imagine the future of recruiting… when you can
27
predict these things:
1. Changing source effectiveness – predicting
where and when source effectiveness will shift, so
that using those newly powerful sources will make
us more effective in attracting “not-looking” and
active prospects
2. Skill needs – when and how will the future skill
and experience requirements for the firm change
3. Internal position openings – which current and
newly created jobs will need to be filled as a result
of corporate growth and employee turnover (when
and where)
33. Imagine the future of recruiting… when you can
28
predict these things:
4. General talent availability – predicting upcoming
talent shortages and surpluses in the marketplace is
important. This would include the local
unemployment rate… because it impacts the
availability of talent
5. Talent availability in specific fields – predicting
upcoming talent shortages & surpluses in key
fields, utilizing college grad. rates in those fields
and upcoming turnover rates in target firms
6. Individual talent opportunities – predicting when
individual top talent will be available Example >
34. An example… of a Talent Opportunity Alert
Why recruit Ms. Z away from DCX?
Ø Invited & spoke at DCX top managers award conference
Ø 2 hires from DCX said she was forced ranked #1 & her
group has a rev per employee of $489,000
Ø DCX manager hires have a 98% success rate at our firm
Why recruit her now during December?
Ø Her bonus is paid on Dec 20
Ø She updated her LinkedIn profile on Dec 10th
Ø She gets her night MBA on Dec 1
Ø Her boss is retiring 12/31, & she is not the replacement
Ø Dec. is the worst weather month where she works in SD
Ø She visited our LinkedIn site 5 times in Dec.
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35. Imagine the future of recruiting… when you can
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predict these things:
7. When direct recruiting competition will
increase / decrease – predicting when ramped
up hiring by competitor firms will make it
more difficult for our firm to successively hire
top candidates.
Also predict talent opportunities when slow
hiring months at competitors… and when hiring
freezes, layoffs, M&A and slow corporate growth
will make hiring less competitive
Also forecast their anticipated reaction to your
TA plans
36. Imagine the future of recruiting… when you can
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predict these things:
8. Prospect visibility – predicting when (because of
social media and the Internet) previously “hidden
prospects” will become easier to find
9. Boomerangs – predicting when former top-performing
employees are likely to want to return
10. Identifying the factors that predict hiring
success – creating a hiring algorithm that can
successfully identify the factors that will predict
on-the-job performance. A different algorithm
may be needed for innovators / college students
Example >
37. 32
An example – where metrics identified
the root cause of a new hire failure
Gategourmet had extreme new hire turnover rates
Ø It used Q of H data to identify the most
important factors that predicted new hire
performance & low turnover
Ø Surprisingly they learned that the key factors were
commute distance & access to public transportation
Ø After changing its hiring criteria…
the firm achieved “fully staffed status” for the
first time
Ø And cut unwanted new hire turnover to just 27%
Source: Talent Management 11/22/13
38. 33
Possible predictive metrics to consider
Recruiting related predictive metrics
11. Changing candidate expectations – when and
how the expectations of our targets will shift
12. Referrals – identifying which new employees are
most likely to be able to make quality referrals
13. Acqui-hire targets – identifying which “talent
rich” firms will be available for purchase or
merger
14. Employer brand strength – predicting when and
why our employer brand strength will increase or
decrease, compared to others
39. Now let’s shift to how to
implement predictive analytics
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Part V
40. Elements of an individual predictive metric
An individual predictive metric should reveal…
1. What will likely happen
2. The probability that it will happen (in percentages)
3. When it will happen (month or quarter)
4. Where it will happen (region, facility or business unit)
5. To who will it happen (which executive will be
impacted the most)
6. The $ consequences when it happens (+ or -)
7. The cost of doing nothing or delaying
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41. How to convert ordinary predictive metrics
into actionable metrics
(Metrics that drive action)
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42. These 13 factors turn an ordinary predictive metric
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into an actionable one
1. A red, yellow or green light indicator
2. Predict the $ revenue impact of the problem/ opp.
3. List the corporate goals that it impacts
4. Include a visual trendline
5. Benchmark comparison numbers (average, best, worst)
6. Reveal the root cause of the problem (Why)
7. Highlight the recommended actions and their
success rate, costs and ease of implementation
8. Provide “drop-down” more detailed information
9. Include the cost of doing nothing or delaying
10. List the accountable individual (Problem owner)
43. - $4.1 million Corp goal: Time to Market
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An example of an actionable metric display
Yearly rev. impact from no action
HR metric – Time to fill (TTF)
This months' TTF = 80 days
Projected TTF = 99 days within 4 mths.
Last year’s TTF = 68 days TTF Trend (Up 22%)
Best in the industry = 29 days (We are 51 days behind)
Cause – Mgr.'s workload is slowing interview scheduling
Cost of doing nothing - $360,000 per month
Action required – Cut delays with after-hour remote video
interviews – $10,000 cost and a 87% success rate
Accountable individual – Pam Tyne, staffing manager
44. 39
Provide “drop-down” menus
Provide quick access to “in depth” information
Time to fill is up 22% (Rev impact $4.1.million)
Drop-down menu
• Formula for time to fill
• Definition
• TTM for your unit
• Impact on new hire quality
• Reasons for hiring delays
• Recommended action
steps
Run your cursor over the metric
45. 40
Elements of an actionable predictive metric
Do these things to make your metrics actionable
11. Prioritize your metrics by their level of
importance
12. Include them in standard business reports
13. Provide only a handful of metrics
46. What are the best ways to predict
upcoming Talent Acquisition events?
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47. 7 basic approaches to identify upcoming TA events
1) Extrapolate from a trendline
Ø Extrapolate from past data and events inside
your firm and at your competitors (Excel creates trend lines)
Ø Follow the firms that historically take talent
management actions first (i.e. first to begin hiring, first to layoff)
Ø Also track the TA actions of “lagging” firms as
an indication that you are falling behind
Ø Track “indicator firms” outside your industry
Ø A trendline example – turnover rates today are
10%... but they are increasing by 2% a month… so
in 6 months they will be… at a 5 year high at 22%
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48. 43
Identifying upcoming TA events
2) Identify seasonal or repeating events
Ø Identify trends that happen at a certain time
each year and alert managers about their impacts
based on past data…
and don’t be fooled into thinking this trend is
something new
Ø A seasonal example – in the past, application rates
have gone up 20% at the beginning of summer and
down to only 1% in December
49. 44
Identifying upcoming TA events
3) Identify precursors
Ø Identify things that occur immediately before a
business, economic or talent event and use them
as alerts about what is likely to happen
Ø A precursor example – when a major competitor
goes through a layoff or merger, they institute a
hiring freeze… Which means that we can hire
higher-quality talent without competition
50. 45
An example of talent surplus precursors
Precursors indicating a coming surplus of talent
1. An increase in the unemployment rate
2. Employee turnover rates are decreasing
3. “Leading firms” have massive layoffs and hiring
freezes
4. The number of applications is increasing
5. Offer acceptance rates are sky high
6. Open jobs stay open 25% longer
51. 46
Identifying upcoming TA events
4) Identify sudden shifts in internal data
Ø Watch your data closely and look for any shifts
above 5% that did not occur at the same time
last year
Ø A shift in data example – when offer acceptance
rates drop suddenly… you must conduct “a root
cause analysis” and alert managers if the trend is
expected to continue
52. 47
Identifying future TA events
5) Identify shifts in environmental factor data
Ø Utilize existing government and university data
on environmental factors to predict significant
changes up or down (interest rates, economic
growth rates, government spending etc.)
Ø An environmental shift example – when the
regions unemployment rate goes up 1%,
historically turnover rates have also gone up 1%
within two months
53. 48
Identifying future TA events
6) Identify shifts within your own business
Ø Utilize existing internal strategic planning,
budgets, sales / production forecasts as a guide
to what TA must do to meet those new goals
Examples
Ø Projected % revenue growth or shrinkage
Ø New product development plans and product
introduction dates (tells you type of skills)
Ø The purchasing of new technology
Ø Geographic expansion plans & remote work %
Ø M&A and divestitures
Ø The budget available for recruiting (CFO)
54. 49
Identifying future TA events
And finally
7) Identify shifts at your major bus. competitors
Ø Create Google alerts and read… the newspaper,
business magazines, online blogs, CEO speeches
and press releases to identify what your
competitors are doing
Ø A shift at your competitors example – social
media blogs in some industries accurately reveal
what your competitors are planning or what they
are about to do in products and recruiting (Apple)
55. Let’s end with…
Basic action steps for implementing
predictive metrics
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56. Action steps for implementing predictive metrics
1. Put together a team of TA professionals with a
knowledge of statistics and data
2. Talk to your CFO and get their support for your
metrics effort
3. Provide executives with a list of talent acquisition
problems/ opportunities and ask them which
“pain points” they would like to see predictive
metrics and alerts in
4. If they select Q of H, I recommend that you start
there (predict when the rate will go up / down
dramatically and “why”)
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57. More action steps for implementing predictive metrics
5. Benchmark with other firms and “big data”
experts to learn from their best practices in this
area
6. Run a pilot in a business function that’s easy to
measure (sales or customer service)
7. Invite some of your company’s finance and
business analytics experts to critically review
your first run of data and your approach
8. Roll out a broader predictive metrics effort but
continually monitor usage, manager satisfaction
and accuracy rates
9. Ask for a raise 52
58. Did I make you think?
Are there any more questions?
JohnS@sfsu.edu or www.drjohnsullivan.com
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