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'Big Data' TARGETjobs Breakfast News 28 November 2013

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BIG DATA Avenue Thursday 28 November OUR 30 TH EVENT
Transcript
Page 1: 'Big Data' TARGETjobs Breakfast News 28 November 2013

BIG DATA

AvenueThursday 28 November

OUR 30TH

EVENT

Page 2: 'Big Data' TARGETjobs Breakfast News 28 November 2013

AGENDA FOR TODAYWelcome and GTI update – Simon Rogers

THE ECONOMIC FORECASTDennis will (in keeping with the theme of the day) note a shift in the way that (Big) Data is used

in economic forecasting; with economists moving away from big econometric models and adopting a more behavioural approach.

THE ERA OF BIG DATALord Daniel Finkelstein OBE, Executive Editor and Chief Leader Writer, The Times believes that

communication and manipulation of data has driven social and political history. His view is that the era of ‘Big Data’ is just the latest stage in this development.

DATA, DATA EVERYWHEREStephen will share his plans for using data to support members’ recruitment strategies and will draw from a number of recruiter examples to demonstrate how data and research is currently

being used to plan recruitment campaigns and evaluate their impact.“AND OUR SURVEY SAYS...”

Marcus thinks there’s a big problem with the way graduate research is used: even if we’ve got the data, we don’t know what to do with it. He’ll talk through the way he evaluates research,

and suggest ways to turn pages of data into pragmatic conclusions.

Page 3: 'Big Data' TARGETjobs Breakfast News 28 November 2013

WE WANT TO SEE YOUR TWEETS!

• #MrToast

Page 4: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GTI acquires Inside Buzz

• Inside Buzz.co.uk offers students, graduates and young professionals an inside look at companies and careers based on interviews with 1000s of employees at the UK’s top companies

• Existing employer content will be incorporated into the TARGETjobs ‘employer hubs’ alongside the existing employer profiles and our own company insights, helping provide the most comprehensive overview of an organisation

• Opportunity for employers to enhance their existing profile and promote by surveying their recent graduate intake on matters as diverse as culture, hours, interview process, training and career prospects

Page 5: 'Big Data' TARGETjobs Breakfast News 28 November 2013

TARGETjobs Premium Employer Hub

• Allows employers to explain exactly why the best graduates should apply to them

• Help shape your graduate recruitment programme via feedback from your recent graduate intake using an Inside Buzz questionnaire

• Benchmark your organisation in up to 20 categories against the competition

• In 2014 we are launching an internship/placement questionnaire

Page 6: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Our launch offer

• Intro cost of £500 • Survey set up • Survey promotion help• Data collection• Employer collaboration• Key content & reviews published on TARGETjobs• Key findings / data available for employers

Page 7: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Record traffic – TARGETjobs

NOW over 1 million

Page 8: 'Big Data' TARGETjobs Breakfast News 28 November 2013

trendence UK Graduate Barometer

• Brand new London-based research centre• Dedicated UK research team• 25,000 students will take part over next 6 months• 400 employers• A NEW diversity focus for 2014 – covering ethnicity,

nationality, social mobility, gender…

As well as…..uniquely surveying students in a way that generates insights by year group, Russell Group vs non-Russell Group and by individual campuses, offering a bespoke competitor analysis and much more….

Bespoke reports

Workshop

Online tool

Page 9: 'Big Data' TARGETjobs Breakfast News 28 November 2013

NEW trendence Law Student Barometer

• 50+ key STEM course campuses

• 4000+ responses• STEM female students only,

cut by year groupCompetitor AnalysisA NEW! Diversity focus Line your firm up against the

top 10 firms that STEM females most want to work for – and find out why!

• 25 key law course campuses

• 3000+ responses• Law & non-law students,

cut by year groupCompetitor AnalysisA NEW! Diversity focus Collecting 25% more

responses from Law Students @ target group campuses and courses

NEW trendence STEM female Student Barometer

Bespoke reports

Workshop

Online tool

Page 10: 'Big Data' TARGETjobs Breakfast News 28 November 2013

National Graduate Employability Conference• The only employability

conference in the UK to bring together 600–800 multi-disciplinary undergraduates with recruiters and universities

• Keynote speaker announced shortly

• Facilitated by Radio 1’s Aled Haydn-Jones

• Presentations, cross-sector panel debates, interactive mixed-table discussions and networking sessions

• Sponsorship opportunities available including hosting your own table of students from your target course area

New 22 April

at Wembley Stadium

Main event sponsors

Page 11: 'Big Data' TARGETjobs Breakfast News 28 November 2013

THE ECONOMIC FORECAST

Dennis Turner, former chief economist, HSBC Bank plc

Page 12: 'Big Data' TARGETjobs Breakfast News 28 November 2013

OSBORNE’S MISSED TARGETS

Page 13: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The growth shortfall

0

1

2

3

4

201520142013201220112010

%

2013 Budget

2012 Budget

2011 Budget

2010Budget

Annual GDP growth forecasts in each Budget

Page 14: 'Big Data' TARGETjobs Breakfast News 28 November 2013

…means more borrowing

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

2010 2011 2012 2013 2014 2015 2016

2010 Budget

2011Budget

2012 Budget

2013 Budget

Public sector net borrowing (£bn)

Page 15: 'Big Data' TARGETjobs Breakfast News 28 November 2013

…and higher debt levels

50

55

60

65

70

75

80

85

90

2009/10 2011/12 2013/14 2015/16

% o

f G

DP

50

55

60

65

70

75

80

85

90

% o

f GD

P

2010 Budget 2013 Budget

2011 Budget 2012 Budget

Public sector net debt:

Page 16: 'Big Data' TARGETjobs Breakfast News 28 November 2013

THE FAILURE OF FORECASTING

Page 17: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GDP Forecasts 2013

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

% a

nn

ua

l g

row

th

Highest

Median

Lowest

Page 18: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Fixed investment forecasts, 2013

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

7

NovSepJulMayMarJan

Lowest

Median

Highest

Page 19: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Export forecasts, 2013

-4

-3

-2

-1

0

1

2

3

4

5

6

7

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

-4

-3

-2

-1

0

1

2

3

4

5

6

7

An

nu

al %

ch

an

ge

Highest

Median

Lowest

Page 20: 'Big Data' TARGETjobs Breakfast News 28 November 2013

WHERE TO IN 2014 – THE CONSENSUS

Page 21: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 - GDP

0

1

2

3

GDP

%

Highest Lowest

Page 22: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 – Consumer spending

0

1

2

3

4

5

Cons ExpGDP

%

Highest Lowest

Page 23: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 - Investment

0

3

6

9

12

InvestCons ExpGDP

%

Highest Lowest

Page 24: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 - Exports

0

3

6

9

12

ExportsInvestCons ExpGDP

%

Highest Lowest

Page 25: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 - Inflation

0

3

6

9

12

InflationExportsInvestCons ExpGDP

%

Highest Lowest

Page 26: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Forecasts for 2014 - Unemployment

0

3

6

9

12

Unemploy.InflationExportsInvestCons ExpGDP

%

Highest Lowest

Page 27: 'Big Data' TARGETjobs Breakfast News 28 November 2013

WHERE TO IN 2014 – MY VIEW

Page 28: 'Big Data' TARGETjobs Breakfast News 28 November 2013

but now likely to ease

-2

-1

0

1

2

3

4

5

6

2009 2010 2011 2012 2013 2014

% c

han

ge m

on

th o

n m

on

th

CPI RPI

Forecast

Target

Range

Page 29: 'Big Data' TARGETjobs Breakfast News 28 November 2013

So interest rates to stay low

0

1

2

3

4

5

6

7

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

%

Forecast

Page 30: 'Big Data' TARGETjobs Breakfast News 28 November 2013

and sterling to remain competitive

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2005 2006 2007 2008 2009 2010 2011 2012 2013

$/£

1.0

1.1

1.2

1.3

1.4

1.5

€/£

Sterling weaker

US$ / £ (L axis)

euro / £ (R axis)

Forecast

Page 31: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GDP (100%) = Consumer spending (64%)

Where is growth coming from?

Page 32: 'Big Data' TARGETjobs Breakfast News 28 November 2013

A slow consumer recovery

-3.5

-2.5

-1.5

-0.5

0.5

1.5

2.5

3.5

4.5

5.5

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

% C

HA

NG

E

Consumer spending growth (%)

Forecast

Page 33: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GDP (100%) = Consumer spending (64%) +

Investment (15%)

Where is growth coming from?

Page 34: 'Big Data' TARGETjobs Breakfast News 28 November 2013

…but not spending

50

60

70

80

90

100

110

120

2001 2003 2005 2007 2009 2011

%

40

50

60

70

80

90

100

110

120

130

140

£ b

illion

Investment relative to post-tax surplus(L axis)

Level of investment (R axis)

Investment by Private Non-financial Corporations

Page 35: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Investment to pick up……at last

-16

-12

-8

-4

0

4

8

12

16

20

24

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

% a

nn

ua

l g

row

th

Business Investment

Forecast – OBR 2013

Page 36: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GDP (100%) = Consumer spending (64%) +

Investment (15%) +

Government spending (23%)

Where is growth coming from?

Page 37: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Government continues in deficit

0

30

60

90

120

150

180

2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016-17 2017-18

£ bn

0

2

4

6

8

10

12

%

Net borrowing (L axis)

% of GDP* (R axis)

Page 38: 'Big Data' TARGETjobs Breakfast News 28 November 2013

GDP (100%) = Consumer spending (64%) +

Govt consumption (23%) +

Investment (15%) +

Net trade (-2%) (Exports 30% – Imports 32%)

Where is growth coming from?

Page 39: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Trade becomes a plus for growth

-5

-4

-3

-2

-1

0

1

2

3

4

5

2009 2011 2013 2015 2017

% o

f G

DP

-12

-9

-6

-3

0

3

6

9

An

nu

al %

ch

an

ge

BALANCE OF PAYMENTS DEFICIT (LHS)

Annual export growth (% RHS)

Annual import growth (% RHS)

Page 40: 'Big Data' TARGETjobs Breakfast News 28 November 2013

TURNING THE CORNER

Page 41: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Sluggish growth as good as it gets

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

2007 2008 2009 2010 2011 2012 2013 2014

%

QUARTERLY

ANNUAL

Long-term average

Forecast

Page 42: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Thank you

Page 43: 'Big Data' TARGETjobs Breakfast News 28 November 2013

THE ERA OF BIG DATA

Lord Daniel Finkelstein OBE, Executive Editor and Chief Leader Writer, The Times

Page 44: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Data, Data Everywhere

Stephen Isherwood, CEO, Association of Graduate Recruiters

Page 45: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Data, Data Everywhere

• UK Graduate market is not short on data points– Salaries and vacancies: AGR 22,000 vacancies– Student market research: trendence 400

employers– Destinations: HECSU 243, graduates– HE sector: HESSA 2,496,645 HE students– Application data: UCAS 653,600 university

applicants

Page 46: 'Big Data' TARGETjobs Breakfast News 28 November 2013

What external data can tell a recruiter

• Gender split by subject studied• UCAS tariff by institution and course• Race profile by university• The career preferences of graduates• What jobs graduates end up doing

Page 47: 'Big Data' TARGETjobs Breakfast News 28 November 2013

What internal data can tell a recruiter• Are relevant or non-relevant students more or less successful in

your business?• Does a UCAS tariff really predict success in your organisation?• Is your selection process efficient, biased, cost effective?• Drive business engagement• Link strategy to business needs• Help set level of investment• Set benchmarks to measure your team’s performance• Allows you to reward success• Enables you to map the candidate experience• Helps drive efficiency improvements• Measures competitiveness

Page 48: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The business case for more budget

Why spend money on graduate recruitment when there are

360,000 students and 83 applicants per vacancy?

Page 49: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The business case for more budget

Graduated with a 1st or 2:1 240,000 (HESA)

24% have AAB+ 57,600 (UCAS)

Minus 14% going to further study 49,600 (DLHE)

7% want accounting/financial services3,472 (trendence)

Professional services vacancies 5,300 (AGR)

Shortfall 1,828

Page 50: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The business case for better interviewers

Applications 100 100Testing 60 601st IV 30 30Assessment centre 12 17Offer 7 7Offer accepts 6 5

Page 51: 'Big Data' TARGETjobs Breakfast News 28 November 2013

“In God we trust, everyone else bring data”

Michael Bloomberg

Page 52: 'Big Data' TARGETjobs Breakfast News 28 November 2013

“AND OUR SURVEY SAYS...”

Marcus Body, Head of Research, Work Group

Page 53: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Research in the War for Talent…

“A great part of the information obtained in war is contradictory, a still greater part is false, and by far the greatest part is of a doubtful character.”

Page 54: 'Big Data' TARGETjobs Breakfast News 28 November 2013

An imperfect storm.

We have more reliable data……so we rely more on data

We have more unreliable data too…and sometimes we’re relying on that.

Critical analysis is more important than ever.

Page 55: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The critical eye:

• Who did the research?

• What is their commercial/political interest?

• Do you trust their integrity?

• Do you trust their competence?

• Have they shared the source data?

• Have they shared the method?

Page 56: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong researcher

Survey reveals a flawless red carpet look can be yours for just £323

20% of men self-conscious about beach body on holiday

Single men change bedsheets only 4 times per year

Boring Facebook statuses named as number one annoying internet habit

Page 57: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong researcher – the tell-tale signs

Have they stated:

•Why they did the research?And is there an obvious answer, with an obvious outcome they set out

to find?

•The number of participants?If not, keep your eyes peeled for suspiciously small-number

percentages (e.g. 16.6%, 12.5%)

•When the survey was conducted?Is this recycled “old news” and is it still relevant?

•What format the survey took?Face-to-face/online. When? How?

Page 58: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The critical eye:

Who EXACTLY did they ask?

How did they source this group?

What incentives were offered?

Are this group relevant to your interests?

If partially, what proportion?

Page 59: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong sample

1) The very big…

“43% of students at UK Universities…”

2) The very small…

“A focus group of 12 economists at Nottingham…”

3) The “not actually students any more”…

“67% of last year’s intake now say…”

Page 60: 'Big Data' TARGETjobs Breakfast News 28 November 2013

A few simple questions…

1) Does this sample contain my ideal candidates? If yes, how large a

proportion are they of it?

2) Are they likely to be consistent with this group? Am I looking for

exceptional individuals, or typical ones?

3) Could I do something better? Or something that will “check” the

validity of this sample?

Page 61: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong source/audience

Page 62: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The critical eye:

What EXACTLY did they ask?

Is this really what you wanted to know?

If partially, to what extent?

What answer options were given?

Have they released ALL answers?

Page 63: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong question1) The “no alternative”…

“Is a company’s environmental record important to you?”

2) The “ridiculous specificity”…

“On a scale of one to ten, how important is training?”

3) The “unreasonable expectations”…

“Which FMCG employer are you most likely to apply to?”

4) The “Where’s my answer option?”…

“Which of the following do you use to…?”

Page 64: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Open vs closed questions

Closed questions (e.g. rankings/scores/options) are quick and easy

to answer, and quick and easy to analyse. But you sacrifice

understanding exactly what people thought.

Open questions (typed answers) give you a much fuller insight into

what people really thought, but are much more time-consuming and

complex to process and analyse.

Page 65: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong question – an example

A survey of 14-15 year olds:

Page 66: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The critical eye:

Does the data ‘prove’ the conclusions?

Does the data support the conclusions?

Are there other interpretations?

What about those prior interests?

Can you find supporting results elsewhere?

Can you find alternative analysis elsewhere?

Page 67: 'Big Data' TARGETjobs Breakfast News 28 November 2013

The wrong conclusion

1) The hyperbolic imperative

“SOMETHING MUST BE DONE…!”

2) The wild extrapolation

“50% of my survey, so 50% of everyone…”

3) The iffily corroborated

“This backs the significant body of opinion that says…”

4) The downright dishonest

“My survey says you should buy my product/service”

Page 68: 'Big Data' TARGETjobs Breakfast News 28 November 2013

An example of selective analysis…

Page 69: 'Big Data' TARGETjobs Breakfast News 28 November 2013

“…most people think public services are as good or better”

Page 70: 'Big Data' TARGETjobs Breakfast News 28 November 2013

A quick regraph of the data…

Page 71: 'Big Data' TARGETjobs Breakfast News 28 November 2013

“BBC austerity survey: why the public is wrong this time”“Every now and again, an opinion poll will be published which appears to show that most people don't know what they're talking about. A fairly typical headline in this spirit is "British public wrong about nearly everything, survey shows". In that case, the public's ignorance on issues such as welfare, crime and immigration favoured the government.

And the latest poll from the BBC about public services under the Tories could represent something similar. Most people when asked about the state of hospitals, schools, colleges, GP surgeries, and so on either think they have stayed the same, or are getting better.”

“The majority of people would not directly experience those cuts, and their effects are unlikely to be detected when the poll asks mainly about the consumption of key infrastructure.”

Page 72: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Actually, the Guardian are wrong too…

Page 73: 'Big Data' TARGETjobs Breakfast News 28 November 2013

A general word on charts…

Page 74: 'Big Data' TARGETjobs Breakfast News 28 November 2013

A matter of perspective

3D is for the cinema, not for good data representation.Watch out for colour and data labels too…

Page 75: 'Big Data' TARGETjobs Breakfast News 28 November 2013

We love straight lines…

Page 76: 'Big Data' TARGETjobs Breakfast News 28 November 2013

xkcd.com/1007

Page 77: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Correlation and causation

Correlation is a measure of relationship between two mathematical variables or measured data values and is a mathematical property.

Causation is the relation between an event (the cause) and a second event (the effect), where the second event is understood as a consequence of the first, and is a philosophical concept explored at length by Aristotle.

Page 78: 'Big Data' TARGETjobs Breakfast News 28 November 2013

xkcd.com/552

Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'.

Page 79: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Be careful of assuming an answer

“Interns don’t join us as graduates, so they must not enjoy the internships. Can we survey what they don’t like?”

Page 80: 'Big Data' TARGETjobs Breakfast News 28 November 2013

AND OUR SURVEY SAYS…WHO DID THE RESEARCH?. . . . . 38

WHO WAS ASKED? . . . . . . . . 27

WHAT WERE THEY ASKED?. . . . . 20

HOW WAS IT ANALYSED? . . . . . 15

Page 81: 'Big Data' TARGETjobs Breakfast News 28 November 2013

One final warning…

Confirmation bias:

•Ignoring evidence which doesn’t fit your view.•Over-rating evidence that says you’re right.

“When I find new information, I change my mind. What do you do?”Keynes (possibly)

“Intelligence is the ability to adapt to change”Hawking

Page 82: 'Big Data' TARGETjobs Breakfast News 28 November 2013

Get in touch

[email protected] 7492 0057

Page 83: 'Big Data' TARGETjobs Breakfast News 28 November 2013

2014

Dates for TARGETjobs Breakfast News 2014 will be available soon.See you next year!


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