Master of Machines

39
Clive Longbottom, Service Director, Quocirca Ltd Masters of Machines C Business insight from IT operational intelligence Bob Tarzey Analyst and Director Quocirca Ltd. April 3 rd 2014

Transcript of Master of Machines

Page 1: Master of Machines

Clive Longbottom,

Service Director, Quocirca Ltd

Masters of Machines C

Business insight from IT operational intelligence

Bob Tarzey

Analyst and Director

Quocirca Ltd.

April 3rd 2014

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© Quocirca 2014

Overview

Background

Metrics

Infrastructure

Operational intelligence

Machine data

Tooling-up

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© Quocirca 2014

Background

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Research background: 5 countries, 6 sectors

14

8

21

22

20

85

6

15

22

20

22

85

13

9

18

22

23

85

10

12

22

21

20

85

2

7

5

5

20

1

3

7

9

20

0% 20% 40% 60% 80% 100%

Netherlands

Sweden

UK

Germany

France

Overall

Finance Manufacturing Other commercial

RDT Telco Gaming

RDT = retail, distribution and transport

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Business sizes by sector

6

6

8

6

51

30

34

22

151

4

4

23

49

29

37

146

2

10

11

6

22

26

77

0% 20% 40% 60% 80% 100%

Gaming

Telco

RDT

Other commercial

Manufacturing

Finance

Overall

200 to 1,000 1,000 to 3,000 3,000 to 5,000 Over 5,000

Job roles of respondents:

Senior IT or e-commerce

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To what extent do you agree with this statement: "Our organisation could benefit from the use of operational

intelligence by collecting, storing and analysing real-time and historical machine data to gain insights that would not

otherwise be available."

29%

24%

20%

36%

42%

40%

33%

46%

54%

60%

47%

46%

50%

49%

0% 20% 40% 60% 80% 100%

Manufacturing

RDT

Gaming

Other commercial

Finance

Telco

Overall

Strongly agree Somewhat agree

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Metrics

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Transactiveness

Operational

intelligence

maturity

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25,560

27,125

27,316

29,603

65,824

111,050

13,083

28,519

31,820

82,320

40,445

0 40,000 80,000 120,000

Other commercial

Gaming

Manufacturing

RDT

Finance

Telco

200 to 1,000

1,000 to 3,000

3,000 to 5,000

Over 5,000

OverallSe

cto

rSi

ze. N

o. o

fem

plo

yees

TRANSACTIVENESS: volume of daily commercial transactions driven by IT systems

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Types of business transactions considered essential OVERALL

20%

36%

38%

47%

69%

0% 20% 40% 60% 80%

Digital assets

M2M

B2P

B2C

B2BO

vera

ll

See report for

data by

industry

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Transaction volume ranges

21%

30% 26%

23% Very high (< 50K)

High (20K-50K)

Medium (5K to20K)

Low (< 5000)

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The 4 stages of operational intelligence maturity

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The 4 stages of operational intelligence maturity

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Please rate your organisation’s ability to do the following OVERALL

25%

28%

25%

24%

24%

28%

26%

33%

28%

27%

29%

46%

42%

44%

39%

43%

48%

49%

43%

44%

40%

43%

47%

36%

23%

21%

23%

23%

17%

17%

24%

19%

23%

24%

20%

14%

10%

8%

12%

9%

11%

6%

7%

5%

9%

6%

4%

4%

0% 20% 40% 60% 80% 100%

4C

4B

4A

3C

3B

3A

2C

2B

2A

1C

1B

1AR

eal

-tim

eb

usi

ne

ssin

sigh

tsO

pe

rati

on

alvi

sib

ility

Pro

acti

vem

on

ito

rin

gSe

arch

an

din

vest

igat

e

Already strong Would like to improve Poor None

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Operational intelligence index by sector

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Operational intelligence index by size

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Infrastructure

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What role do the following play in the way IT is deployed by your organisation?

28%

30%

31%

47%

64%

38%

45%

45%

42%

26%

0% 20% 40% 60% 80% 100%

Infrastructure/platform-as-a-service (IaaS/PaaS)

Software-as-a-service (SaaS)

Our own systems in a third partydata centre

Virtualisation

Our own systems in our owndata centre

Primary Secondary

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Transactiveness and use of flexible infrastructure

35,450

34,751

46,617

35,404

44,185

40,808

40,445

0 20,000 40,000 60,000

We do not deploy in this way

A secondary way we deploy

A primary way we deploy

We do not deploy in this way

A secondary way we deploy

A primary way we deploy

OverallU

sevi

rtu

alis

atio

nU

se S

aaS/

Paa

S

Average daily transaction volume

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Percentage of infrastructure managed in-house and by service providers

58%

63%

64%

66%

67%

72%

65%

42%

37%

36%

34%

33%

29%

35%

0% 20% 40% 60% 80% 100%

Gaming

Manufacturing

Finance

Other commercial

RDT

Telco

Overall

In-house Outsourced

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Operational intelligence

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Operational intelligence in action

Call centre monitoring

Monitoring usage of online services

Fraud prevention

Payment card controls

Physical access control

Access authentication

Service personalisation

IT management controls

KPI measurement and monitoring

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Operational intelligence maturity By use of FLEXIBLE INFRASTRUCTURE

1.69

1.89

2.02

1.56

1.98

2.27

1.92

0 1 2 3

We do not deploy in this way

A secondary way we deploy

A primary way we deploy

We do not deploy in this way

A secondary way we deploy

A primary way we deploy

Overall

Use

of

virt

ual

isat

ion

Use

of

Paa

S/Ia

aS

OI index

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Job roles with a comprehensive view of operational intelligence

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17%

22%

27%

28%

35%

36%

56%

28%

22%

38%

41%

27%

36%

29%

19%

21%

22%

18%

22%

12%

36%

34%

13%

13%

16%

16%

9%

0% 20% 40% 60% 80% 100%

Service providers

Partners

Product managers

Marketing managers

Board level executives

Application developers

IT managers

Comprehensive Would like to improve

Would like to, not able to No need/don't know/no OI

What roles in the organisation have access to operational intelligence?

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Board level view of operational intelligence By OI INDEX

27%

33%

48%

82%

35%

16%

21%

28%

35%

9%

27%

34%

37%

23%

11%

22%

47%

15%

16%

6%

9%

16%

0% 20% 40% 60% 80% 100%

Very low

Low

Medium

High

Maximum

Overall

Comprehensive view Would like to improve view

Would like to provide a view No need/don't know/no OI

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View of operational intelligence provided to service providers By HOW IT IS MANAGED

18%

20%

16%

17%

38%

41%

22%

28%

25%

13%

18%

19%

18%

26%

44%

36%

0% 20% 40% 60% 80% 100%

Mainly by service provider

Equal

Mainly in-house

Overall

Ho

w IT

infr

astr

uct

ure

is

man

age

d

Already comprehensive Would like to improve

Would like to, not able to No need/no OI capabilty/don't know

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Machine data

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Sources of machine data

System and network data

User data

Application data

Web data

Other sources

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How necessary is machine data for delivering operational intelligence?

20%

35%

34%

42%

48%

30%

38%

45%

34%

41%

44%

39%

60%

41%

0% 20% 40% 60% 80% 100%

Gaming

Manufacturing

RDT

Other commercial

Finance

Telco

Overall

Very Somewhat

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How much of a challenge are the following issues for your organisation? OVERALL

18%

20%

19%

21%

23%

26%

33%

33%

37%

37%

37%

38%

0% 10% 20% 30% 40% 50% 60% 70%

Integrate and analyse machine datafrom both on-premise and on-…

Delivering value to your businessfrom machine generated 'big data'

Ability to add new data sources toexisting data stores

Correlate historical machine datawith new machine data collected…

Integration of multiple data stores

Collecting, searching and analysinglarge volumes of historic machine…

A big challenge Somewhat of a challenge

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Percentage of IT infrastructure machine data is gathered from By OI INDEX

15%

39%

45%

49%

65%

0% 10% 20% 30% 40% 50% 60% 70%

Very low

Low

Medium

High

Maximum

% of infrastructure machine data gathered from

OI I

nd

ex

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Tooling up

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How does your organisation currently capture operational intelligence?

4%

27%

45%

46%

54%

57%

64%

0% 20% 40% 60% 80%

We do not currently capture

Purpose built tool

Custom scripts

Relational database system

Data warehouse

Spreadsheets

Business intelligence tools

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Machine data collected by tool used

43%

44%

44%

44%

45%

52%

43%

20% 30% 40% 50%

Spreadsheets

Data warehouse

Custom scripts

Business intelligence tools

Relational database system

Purpose built tool

Overall

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© Quocirca 2014

Quocirca’s report is freely available here:

http://www.splunk.com/goto/masters_of_machines_whitepaper

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© Quocirca 2014

THANK YOU

www.quocirca.com

[email protected]