Richard Turner , CEO, Innovantage - The Key V’s of Data - The Approach on Data Acquisition - The Gen Z Expectation

1. www.innovantage.co.uk
+44 (0)2921 432 125
Sales@innovantage.co.uk

2. Importance of Data
Interpretation of Analytics
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How Analytics can help you succeed in
Today’s War for Talent

3. GB TB PB EB
Variety
Velocity
VolumeZB
Big Data
Defined as the Three Vs
3
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4. 360,000Tweets
are sent on Twitter
300 hours of video are
uploaded to YouTube
Every minute…
293,000Facebook
statuses are updated
571new
websites are created
16,700customer transactions
are processed by Walmart
200,000,000
emails are sent
30,000 images
are uploaded on Flickr
Velocity
Speed of Data Processing
4
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5. 2009 2013 2020
1 Zettabyte
4.4 Zettabytes
44 Zettabytes
Popularity of internet Shift from using sample data to analyze
trends to using overall data to analyze
trends
Increase in data acquisition
capacity
Global data production is growing at an astonishing pace
Volume
Amount of Data
5
Source: IDC
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6. Structures
Formats
Sources
Types
Context
Interpretation
Data
Variety
Structured
Unstructured
Semi-structured
Video
Photo
Audio
Sensors
Social
Mobile
External
Internal
Database
Primitive
Composite
Complex
Spatial and GPS
Social interaction
User click stream
Variety
Types of Data
6
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7. Big data is expanding on six different fronts at an increasing
rate
Variability
Value
Veracity
Variety
Velocity
Volume
Three Additional Vs
7
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8. User 1
Twitter User 1 @TwitterUser1 · 3m
Just had drinks at the Hoof Cocktail Bar. Had such a
great time!
User 2
Twitter User 2 @TwitterUser2 · 28m
Just spent two hours in line at the Hoof Cocktail Bar.
Great, there goes half my night!
User 3
Twitter User 3 @TwitterUser3 · 57m
Greatly disappointed that the Hoof Cocktail Bar doesn’t
serve complete meal…
Variability: Meaning of Data
Consider these three example Tweets:
8
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9. • Data is messy and
requires an enormous
amount of upfront work
to produce an accurate
dataset
• Considering volume,
velocity and variety of big
data, organizations can
no longer commit time to
cleanup data and make it
certain before conducting
analysis
…Removing duplicates…
…Fixing partial entries…
…Eliminating null/blank entries…
…Concatenating data…
…Collapsing/splitting columns…
…Aggregating results into buckets…
Data cleansing is overly complex…
Veracity
Data Accuracy
9
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10. • Additionally,
unstructured data
contains a significant
amount of uncertain and
imprecise data
• Thus, organizations must
now analyze imprecise
data and must factor in a
level of uncertainty to
the results
• Data inconsistency
• Incompleteness
• Ambiguities
• Latency
• Deception
• Model approximations
Uncertainty due to…
Veracity
Data Accuracy
10
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11. 47%
say data integration
complexity is an
obstacle
34%
lack skills
necessary to
derive value
29%
say the data set
sizes limit their
ability to analyze
28%
say it takes too
long to analyze
the data
Machine
Learning
Artificial
Intelligence
Data Mining
Many enterprises are moving quickly to implement big data analytics and
technologies
Value: Data Extraction
Big data is worthless without the ability to turn it into value, but that is not easy
11
Source: ESG
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12. Variability
Value
Veracity
Variety
Velocity
Volume
• Predictive
Analytics
• Talent Pool
• Planning
• Parsing
• Normalisation
• Duplication
• Occupations
• Industries
• Geography
• Skills
• Certifications
• Requirements
• Maintain database
of multibillion ads
• Cover multiple
countries
• Collect from
hundred thousands
sources
• Scrape every day sources
to update data base
• Normalization of millions
ads per day
• Job Boards - Newspaper
• Corporate website
• Social media
• Colleges, Universities
• Governments
• Stock market
Big Data and Recruitment
12
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13. Collected Online Job Vacancies
1st Challenge
Collect all Jobs
13
Velocity
Volume
15,513,218
21,805,282
28,222,509
32,289,419
52,138,524
43,281,827
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
Apr11 - Mar12 Apr12 - Mar13 Apr13 - Mar14 Apr14 - Mar15 Apr15 - Mar16 Apr16 - Oct17 (7 mths)
7MthsofData
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14. 2nd Challenge
Normalize the Data
• Location: locality, community, county, region,
country
• Advertiser: name, industry
• Job Type: Full-time / Part-time
• Job Hours: Permanent, Contractual, Temporary,
Internship
• Salary: £/hour, £/week, £/month, £/year
• Title: Classifier
14
Variability
Veracity
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15. 3000
Granular STC Occupations
12000
Level-based STC Occupations
3rd Challenge
Classify all Jobs
15
Variability
Veracity
13116100043 – Senior Digital Analyst
Inno UTT Code 13 1 161 00 04 3
Occupational SOC2 SOC3 SOC6 SOC8 UTT10 UTT11
Category
Description
Business and
Financial
Operations
Occupations
Business
Operations
Specialists
Market
Research
Analysts and
Marketing
Specialists
Market
Research
Analysts and
Marketing
Specialists
Digital
Analyst
Senior
Digital
Analyst
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16. How…by creating an intelligent robot
• Scrapes job boards and corporate sites
• Learns how a website looks and acts, without a specific
robot being created for that website
• Should a website change (design or functionality), it can
reconfigure itself without the need for human
intervention
• Crawlers run every day, some multiple times/day
16
Velocity
Volume
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17. The Attributes
•A list of granular occupations
•Title cleaner before classification
•Extraction of level of experience
•Extraction of soft and hard skills
•Machine-Learning based classification of jobs
using skills
•Remove duplicates
17
Variability
Veracity
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18. Data Accuracy
Primary Normalisers
18
Variability
Veracity
90.00%
91.00%
92.00%
93.00%
94.00%
95.00%
96.00%
97.00%
98.00%
99.00%
100.00%
Discipline Job Title Location Job Type Salary Hours
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19. The Result:
How Can We Use all of This
• Send recruiting leads to staffing agencies
• Inform recruiters about the Job market
- Predict trending skills from job descriptions for a specific industry
- Identify which skills are paying a premium
- Report on market share
• Campaigning using intent data
- Find out when a passive seeker is on the verge or becoming an active
one
• Enhance the job seeker experience by showing search results
using their intent data
19
Variability
Value
Veracity
Variety
Velocity
Volume
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20. Analytics
How is it delivered
20
Recruitment & Jobboards HR Companies
+
Insight – real time vacancy
data for recruiter, lead generati
on and candidate placement
Analytics – Delivering historical,
current and future data surrounding
your particular industry
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21. UK Opportunity
Job Market in the UK
• More than 60+ million vacancies in the UK posted every year
- 300+ Job boards
- 200,000+ company URLs
• About 750,000 unique open vacancies at any time
• More than 18,000 staffing agencies, employing about 100,000 recruiter
• About 32.1M in the workforce, with 4.3% unemployment rate (Aug ‘17)
21
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22. Recruitment Intelligence | Creating Business Advantage
But a shift towards more prescriptive rules of worker engagement feels
counterintuitive:
Data, AI & robotics are changing employers’ need for labour
The UK is behind the curve, choosing to utilise flexible labour over investment in data &
automation
22Recruitment Intelligence | Creating Business Advantage

23. Recruitment Intelligence | Creating Business Advantage
…and Predictive Personalisation/Mass Customisation
Will further change employer needs
23Recruitment Intelligence | Creating Business Advantage

24. The supply side, Gen Z,
Forcing employers to change how they engage with workers
Gen Z are early starters – More 16-18 year olds are going straight into work
24
The new UK Apprenticeship Levy is likely to
accelerate this trend – notably if key employers,
such as Dyson, use it to offer higher level training.
Students are paid to work and learn at employer-
led university
The % of UK
school leavers
going to University
is declining
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25. The supply-side, Gen Z
Forcing employers to change how they engage with workers
25
0%
1%
2%
3%
4%
5%
6%
Oct-Dec2002
Oct-Dec2004
Oct-Dec2006
Oct-Dec2008
Oct-Dec2010
Oct-Dec2012
Oct-Dec2014
Oct-Dec2016
% of all working 18-24 year olds in self-
employment
Source: FCSA analysis of ONS data
Gen Z are entrepreneurially minded
72% of US schoolkids surveyed in
2016, stated that they wanted to
have their own business someday –
61% straight from school.
Gen Z have high expectations from work
If don’t feel appreciated will move on: will force
you to be loyal to them as a consequence
Gen Z are big on individuality
Will require bespoke work packages rather
than fitting into career hierarchy
Gen Z are globally minded
Will demand diversity in their work, and a
global outlook/influence rather than repetition
of (localised) tasks
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26. The conclusion:
All that we see, by way of demand data, highlights the continuation of traditional hiring practices, but
A paradigm shift in Data Analytics,
AI & Personalisation will disrupt the
workforce composition /
engagement - and the staffing
industry’s value proposition
26Recruitment Intelligence | Creating Business Advantage

27. Thank You
www.innovantage.co.uk
+44 (0)2921 432 125
Sales@innovantage.co.uk