Before the PC, mobile phone and internet; HR, Accounting, Senior Management, IT and Security Depts could be almost disconnected from the fine detail of day-to-day operations. In that world everything moved at a leisurely pace in a non-networked mode where actions and outcomes were mostly linear and change was mostly predictable. That is no longer the case! Individuals and teams are now empowered by computers and communication, applications and tools, in ways that were unthinkable 20 years ago. But some people and organisations still fail to fully recognise that the transformation of business and life has occurred, whilst at the same time it all so very obvious to the young and anyone working at the leading edge. No one, no team, no organisation or country can operate in isolation anymore. The planet got connected, became complex and non-linear, and now demands new modes and new practices at all levels. Far from being disconnected; HR, Accounting, IT and Security find themselves being pushed to the front line aside Senior Management. Not understanding change, technology, the latest working practices, in the context of the organisations business and that of the competition makes people and groups an insider risk, and they can put the future of the whole enterprise on the line. For many modern organisations the era of IT Depts providing centralised device support, networking and security is drawing to a close in the same way that sitting in front of a static PC in an office all day is becoming unworkable.  People now work anywhere, on the road, at home, in hotels and coffee shops, as and when they can, completing tasks by any means possible. They also tend to migrate rapidly from one project to another, and in extremis their modus operandi becomes: “I don’t want employment I want to work on exciting projects” So, HR has to rethink what has to change in order to adapt to the growing BYOD (Bring Your Own Device) and BMOB (Be My Own Boss) cultures where individuals use non-company Clouds and Networks without the need of any official Infrastructure and/or Support. At the same time Management at all levels has to see a proactive anticipatory approach to meeting need and resource provision. In this respect, a responsive HR team is now critical to the bottom line in ways that were never anticipated 20 years ago. The first critical step in the transformation of HR is to get a grip of the technology of change and the employment trends it is creating.

1. The Changing Face of HR
Peter Cochrane
cochrane.org.uk
ca-global.biz

2. A C O N N E C T E D W O R L D
Unexpected behaviours and outcomes

3. ManAgement Struggle
G e n e r a l l y c o n f o u n d e d b y c o m p l e x i t y
Instinct and experience increasingly dangerous
Knee jerk management is always dangerous
Dynamic connectivity
and multi-species
non-linearity

4. L i m i t e d :
- A s s u m p t i o n s
- M e a s u r e s
- T h i n k i n g
- M o d e l s
- D a t a
E v o l v e d f o r a n s l o w c h a n g i n g
a n a l o g u e w o r l d - l i n e a r i t y
r u l e d & o u r m a t h w o r k e d
- b u t i t a l l c r a s h e s a b o v e
o r d e r ( 5 ) - c o m p l e x i t y
n o w r u l e s w i t h 1 0 s t o
1 0 0 0 s o f v a r i a b l e s -
a n d p e r h a p s w o r s e
w e c o p e w i t h < 5 - 7
s i m u l t a n e o u s i d e a s
“There are lots of simple
solutions to complex problems
and they are all wrong”
tyranny of THE SIMPLE
We are linear thinkers but the world is complex

5. p o l i t i c s
M a n a g e r s
E C O N O M I CS
“People love simple - it is so
obvious and doesn’t involve thinking”

6. T H E K i n g s
o f s i m p l e ?
Both are IT illiterate - they cannot
operate a computer and ‘boast’
their inability and ignorance !!!
These are not good leadership
qualities..

7. Technology
Ecology
d e p e n d e n cy J I GS AW
Economics
Society
Industry
Care
Markets
Trade
Education
Policing
Defence
Commerce
Security
Logistics
Finance
Government
Companies
W e h a v e n o m o d e l o r u n d e r s t a n d i n g
The BIG DATA DOMAIN links everything and records relationships and
patterns of behaviour - in doing so it creates vast amounts of data vital
to the modelling of the real world…
Law & Order
Defence
Education
Health
Institutions

8. Technology
Ecology
d e p e n d e n cy J I GS AW
Economics
Society
Industry
Care
Markets
Trade
Education
Policing
Defence
Commerce
Security
Logistics
Finance
Government
Companies
W e h a v e n o m o d e l o r u n d e r s t a n d i n g
The BIG DATA DOMAIN links everything and records relationships and
patterns of behaviour - in doing so it creates vast amounts of data vital
to the modelling of the real world…
Law & Order
Defence
Education
Health
Institutions
“ S o m e t i m e s W E m i g h t
o b s e r v e o r i n f e r s o m e
l i m i t e d r e l a t i o n s h i p s a n d
typify some characteristics
however AI can produce a
comprehensive analysis and
a much fuller picture and/
or model”

9. A X I O M S
V e r y o b v i o u s ?
H i g h l y o p t i m i s e d m a c h i n e s
s y s t e m s a n d c o m p a n i e s a re
brittle and prone to drastic
a n d u n c o m p ro m i s i n g f a i l u re

10. H i g h l y o p t i m i s e d m a c h i n e s
s y s t e m s a n d c o m p a n i e s a re
brittle and prone to drastic
a n d u n c o m p ro m i s i n g f a i l u re
I n c re a s e d e f f i c i e n c y l e a d s t o
increased br ittleness and
m o re f a i l u re s … .
…more data is a must for
a c c u ra t e b u s i n e s s m o d e l s
a n d wa r g a m e s …
….BIG and small DATA are
key to a more predictable
t h e f u t u re
Stop Over Optim ising
if you wa nt your
c o m p a n y t o s u r v i ve a n d
p ro s p e r
Av oid erroneous KPIs
and bonus driven
cultures
Embrace a data and
business model driven
approach

11. - P o l i s h i n g w h a t w e h a v e w i l l n o t r e a l i s e s u s t a i n a b i l i t y
- N e w m a t e r i a l s & m a n u f a c t u r i n g m e t h o d s a r e r e q u i r e d
- N e w d i s t r i b u t i o n , s u p p o r t a n d m a i n t e n a n c e r e g i m e s
- E n e r g y a n d m a t e r i a l u s a g e h a s t o b e m i n i m i s e d
- R e u s i n g , R e p u r p o s i n g , R e c y c l i n g , h a s t o b e r e a l
- E c o n o m i c s y s t e m s h a v e t o b e f i t f o r p u r p o s e
A X I O M S
Not so obvious?

12. C O M P A N Y C O L L A P S E
M a n a g e m e n t h u b r i s i g n o r a n c e
A great world leading company - what could
possibly go wrong ??
Did the board understand their technology
Did the board understand their market
Did they heed their own experts
Did they ‘eat their own dog food’
Did management assumed the style of ‘Gods’
Did they think themselves infallible/all knowing
Did they rely on instinct instead of facts and models
D E S T R O Y E D

13. C O M P A N Y C O L L A P S E
L o s s o f l e a d e r s h i p & m a n a g e m e n t
Another great world leading company - what
could possibly go wrong ??
They lost their leaders
They lost sight of their core values
They lost sight of their core mission
They lost their grip on technology and markets
They then drastically changed direction
The company core competences were lost
What is now left is smething much less than it was!
D A M A G E D

14. 1884 - George Eastman patents photographic film on a roll
1888 - First film camera perfected
1892 - Kodak founded in Rochester, NewYork.
1900 - Brownie camera launched at a price of $1
1930 - Eastman Kodak launched on the Dow Jones.
1969 - Kodak film used on the Apollo 11 missions
1975 - The first company to build a working digital camera
1976 - 90% of photographic film and 85% of camera sales market
1994 - Kodak designs Apples first consumer digital camera
2004 - Stopped selling film cameras in the face of digital alternatives.
2005 - Largest seller of digital cameras in the US, revenue reaching $5.7Bn
2009 - Stopped selling 35mm colour film after 74 years of production.
2011 - Shares fell >80pc as it struggled to maintain market share
2012 - Files for chapter 11 bankruptcy.
L E A d e r
L a g g a r d
B A N K C R U PT

15. 1884 - George Eastman patents photographic film on a roll
1888 - First film camera perfected
1892 - Kodak founded in Rochester, NewYork.
1900 - Brownie camera launched at a price of $1
1930 - Eastman Kodak launched on the Dow Jones.
1969 - Kodak film used on the Apollo 11 missions
1975 - The first company to build a working digital camera
1976 - 90% of photographic film and 85% of camera sales market
1994 - Kodak designs Apples first consumer digital camera
2004 - Stopped selling film cameras in the face of digital alternatives.
2005 - Largest seller of digital cameras in the US, revenue reaching $5.7Bn
2009 - Stopped selling 35mm colour film after 74 years of production.
2011 - Shares fell >80pc as it struggled to maintain market share
2012 - Files for chapter 11 bankruptcy.
L E A d e r
L a g g a r d
B A N K C R U PT
A s s i s t c o m p a n y t o
m u t a t e
f r o m
p r o d u c t i o n
&
s u p p l y
t o o
i n n o v a t o r
a n d
m a r k e t
l e a d e r w i t h
n e w
p r o d u c t s
H R
C H A L L E N G E ?
H R
C H A L L E N G E ?
H e l p
t h e
c o m p a n y
r e s p o n d
t o
t h e
p e n d i n g
d e s t r u c t i o n
o f
t h e i r
p r i m a r y
b u s i n e s s
m a r k e t
a n d
m o d e l

16. -1889:Time-recording equipment maker Bundy incorporated
-1896:The (punched card)Tabulating Machine Co incorporated.
-1918: CEO Watson becomes business icon, pioneering worker benefits
-1923: First electric key punch a big advance on mechanical systems
-1928: 80-column IBM punched card, 2x previous capacity introduced
-1931: IBM 400 accounting machines offer alphabetic data
-1932: IBM 600 performs multiplication and division
-1933: IBM acquires Electromatic Typewriters
-1944: Mark I, first machine to accomplish long operations automatically
-1946: IBM 603 first machine to offer electronic arithmetic circuits
-1948: IBM the Selective Sequence Electronic Calculator
-1952: IBM 701 first production electronic computer, featuring tape-drive
-1957: FORTRAN introduces as the main language for technical work
-1961: Selectric typewriter released later models offer memory and word processing.
-1964: IBM 360 Solid Logic Technology microelectronics
-1966: IBM's Robert Dennard invents the Dynamic Random Access Memory
-1969: IBM onboard computer used in first manned flight to the moon
L E A d e r
S u rv i vo r
i n n ovato r

17. -1971: Floppy disk is introduced to later becomes the PC data storage standard
-1975: IBM 5100 Portable Computer enters the market, 50 pounds priced at $9 to $20k.
-1981: IBM PC launched at $1,565, the lowest priced PC to date
-1984: IBM second-generation PC, runs on a 6MHz Intel 80286 processor
-1987: IBM PS/2is launched along with the OS/2 jointly developed with Microsoft
-1990: IBM 390 family, midrange machines and supercomputers
-1991:An annual loss of $2.82Bn, the first of three annual losses in a row
-1993: Louis Gerstner states his intention to keep IBM together as an integrated company
-1995:Acquires Lotus and Notes making IBM the world's largest software company.
-1995: Introduces the ThinkPad 701cm, which runs on the Intel 133MHz Pentium
-1996: Launch of the DB2 Universal Database, capable of querying alphanumeric data
-1997: Deep Blue supercomputer defeates Gary Kasparov Chess Master
-2002: Further strengthens services business with a $3.5 billion acquisition PWC Tech unit
-2005: Sold more than 20 million ThinkPads and sells business to Lenovo
-2011: IBM Watson artificial intelligence defeats TV Jeopardy game show champions
-2012: IBM Watson outguns medical doctors at diagnosis
-2013: IBM Watson APIs made public
L E A d e r
S u rv i vo r
i n n ovato r
A s s i s t
m u t a t i o n
f r o m
o n e
i n n o v a t i v e
b u s i n e s s t o
t h e
n e x t
b y
p r o v i d i n g
f l e x i b i l i t y
o f
r e c r u i t m e n t
a n d
e m p l o y m e n t
H R
C H A L L E N G E ?

18. H E A D I N G
Tow a r d a
T e c h i m p a ss e
Business cannibalisation
Search business model based on clicks
AI search business model based fewer clicks
Revenue collapse projected
Pending business collapse!
Diversification into new sectors
Driverless vehicles
Delivery drones
AI as a service
AI office
+++

19. H E A D I N G
Tow a r d a
T e c h i m p a ss e
Business cannibalisation
Search business model based on clicks
AI search business model based fewer clicks
Revenue collapse projected
Pending business collapse!
Diversification into new sectors
Driverless vehicles
Delivery drones
AI as a service
AI office
+++
C o n t i n u a l l y a d j u s t e m p l o y m e n t
a n d r e c r u i t m e n t m o d e l t o m e e t
a
v e r y
w i d e
&
d y n a m i c
r a n g e
o f a c t i v i t i e s &
b u s i n e s s e s
H R
C H A L L E N G E ?

20. Managing the resources of the planet by a
single parameter ($$) is never going to
work - it can only result in chaotic
economies & eventually a total
demise…we need far
more sophistication!
AX I O M AT I C
W e h a v e B I G D A T A
b u t w e n e e d B I G
U N D E R S T A N D I N G
Trying to manage the resources and
capabilities by a limited number of
KPIs and/or simple minded thinking
now guarantees failure..we need to
be far more sophisticated!

21. • Raw Data
• Meta Data
• Small Data
• B I G D a t a
E v e r y s e c t o r i s a w a s h / o v e r w h e l m e d
W hat w e HAVE TODAY
W h a t w e a c t u a l l y n e e d :
K n o w l e d g e & U n d e r s t a n d i n g

22. DATA Big & SMALL
Small Data
Focussed
Detail
Big Data
Macro-View
Relationships
Limited
C o n t a i n e d
C o n s t ra i n e d
Expanding
Tending to
T h e I n f i n i t e
Both important and dynamic

23. distribution
Automated & intelligent

24. distribution
Automated & intelligent
BIG DATA
Where has the package
come from and where is it
going ? Where is it now and
what does it contain ?
small DATA
The detailed product
history of how it was
created; where it has been
s t o re d a n d d e t a i l e d
handling history including
humidity, temperature, G-
force, damage +++
Item
Box
Pallet
Warehouse
Container
Supplier
Customer

25. O B S E RV AT I O N S
- Change is always a surprise
- It tends to come from an unexpected direction
- Mechanism tends to be novel and not anticipated
- Responding quickly is absolutely essential
- There is a BIG first mover advantage
F a v o u r s t h e A d a p t a b l e

26. W A R
G A M I N G
A r t i f i c i a l
I n t e l l i g e n c e
M
odelling
Com
puter
M at e r i a l
S c i e n c e
Clouds
B I G
D A T A
BYOD
BMOB
DIY IT
Sensors
Robots
C y b e r
Security
Nano
Bio
T H E B I G G A M E C H A N G E R S
IoT + Auto Immunity
Block Chain + Apps

27. EXPANDING HR FUNCTION
In an ideal world HR would be ahead:
Aware of tech progress & change
Providing management updates
Anticipating new applications
Following new social trends
Promoting new practices
Monitoring competitors
Using latest office tech
Watching the market
Identifying key staff
Helping the board
+++++++++++
++++++++++

28. O n e S I z e D O ES n ot F I T a l l
- Companies are seldom monolithic
- Technology change is challenging
- Competition never sleeps
- Solutions are dynamic
A D A P T A B I L I T Y
I S
K I N G !

29. Fa i l FA S T ! !
- Recognise failures quickly
- Respond & repair immediately
- Be ruthless in the action necessary
- Mid-course corrections generally work - reboot if needs be
- Evolution is not linear - it is chaotic with many false avenues
“Doing something, making
a decision is always better
than doing nothing”

30. H R : P E O P L E S K I L LS c h a n g e
Compensation
Recruitment
Compliance
Legislation
Training
Welfare
Safety
Cognitive
System
Complexity
Content
Processes
Social
Resources
Technical
Physical
Growing Stable Declining
2000 - 2025

31. E M P L OY M E N T: P R E M I U M S K I L LS
At a premium:
Leaders
Analysts
Specialists
Innovators
Generalists
Negotiators
Communicators
Educated managers
Complex problem solvers
Hard to find fixers:
Software
Electrical
Electronic
Mechanical

32. E M P L OY M E N T: T H E N O M A DS
Motivation:
Lifestyle
Freedom
Burn out
Excitement
Higher earnings
Self determination
Second career:
Do not want job !
Object to the routine
Seeking challenging work!
Do not want responsibility

33. A dva n c i n g t e c h n o l o g y
AI v Human Defeats:
Chess
Poker
Go
Debating
General Knowledge
Medical Diagnostics
+++
Robotics v Human Defeats
An endless list
D e m a n d s m o r e p e o p l e
‘Machines are good at dealing with vast
quantities of the expected”
“People are good at dealing with small
quantities of the unexpected”

34. When robots do all the work, how will people live?
Tom Watson
U K
I S
S H O R T
O F
2 0 0 k A N A L Y S T S

35. Analytics:
Veracity
Medical
Security
Big Data
Political
Networks
Economic
Genomic
Proteomic
Diplomatic
Complexity
++++
We are way past the point where humans can
analyse complexity even on a small scale !
Design:
Chips
Devices
Systems
Networks
Behaviours
++++
Knowledge:
Veracity
Linking
Creation
Curation
Searching
Selection
++++
A I : A p r i m a ry to o l o f i n n ovat i o n

36. N E W M a n a g e m e n t To o ls
- AI
- The IoT
- BIG DATA
- small DATA
- DATA Analytics
- Business Modelling
- War Gaming/Simulation
- The Cloud ?
- Block Chain ?
- Social Networking ?
- Behaviour Monitoring ?
- +++

37. E M P L OY M E N T: I N /o u t s o u r c i n g
Leaders
VisionariesNiche Players
Challengers
Completeness of Vision
AbilitytoDeliver
“Do what you do best
- outsource the rest”

38. The ability to solve problems
now trumps pure and isolated
academic attainment…
HR IMPLICATIONS: Hiring ??
Collaboration helps us
g e t a n i n c r e a s i n g l y
difficult balance right
dynamically !
AI and Robotics are the
new tools of many
professions
Multi-skilled people are
rare and at a premium

39. H R - B I G I M P L I C AT I O N S
- Point of production change
- Different business models
- Green agenda drivers
- Faster tech innovation
- New manufacturers
- New processes
- New skill sets
- New tools
- Greater accessibility & freedoms
- Changing people expectations
- More autonomy/less control
- Shorter projects/contracts

40. Thank You
cochrane.org.uk
ca-global.biz