Energiaa, uusia innovaatioita, rohkeutta uudistua... Dreamforce to You -tapahtuma kokosi Helsinkiin yli 750 asiakasta ja yhteistyökumppania 3.11.2016. Tapahtuman jaettavat esitysmateriaalit koottuna.

41. koulutus

42. #Verkostot
10
Customers
50-­‐100
Events
20000
Followers
100
000
Readers/year
+300
000
Pageviews
10
Events
5000
Guests
130
000
Readers
380
000
Pageviews
Idea
Strategia
Johtaminen
Muotoilu
Digitalisaatio
1. Miksi? Enemmän ja parempaa
vähemmällä
2. Mitä? Omistaja-arvon
kasvattaminen, Kasvu,
Muutosjohtaminen, Digistrategiat,
Yritysmuotoilu
3. Miten? Valmennukset, konsultointi,
Koulutus, Puheenvuorot
4. M&M Mainetutkimuksen 1.
“Elää ja yrittää
kuten opettaa”
Digitalist
www.villetolvanen.com
Yritysmuotoilu

43. ”Etsimme uutta internetistä, vaikka ainoa
tehtävä olisi mullistaa vanha.”

44. Digitalisaation tehtävä on luoda enemmän ja
parempaa vähemmällä.
Digitalisoiminen on paras, tehokkain
ja halvin tapa luoda uutta arvoa.

45. Digijuna yritysten ja toimialojen
välillä pitenee.

46. Ollakseen ”strateginen” on
oltava keskeinen osa arkea.
Kulttuuri ahmii strategioita aamupalaksi.

47. Data, järjestelmät, prosessit,
arvoketjut, siilot, ATK
Arvo, Tieto, Ekosysteemit, Asiakaskokemus

48. Ekosysteemit, Alustatalous,
Yhteisöt & Asiakaskokemus

49. Janatodellisuus
Markkinat
Arvoketjut
Ratkaisut
Materiaalit
Ympyrätodellisuus
Ekosysteemit
Arvoverkostot
Arvo
Asiakkaat
TRANSFORMAATIO

50. Asiakaskokemus
Infrastruktuuri
Työ, verkostot
Prosessit
Toimintamallit,
Transformaatio – Digitalisaatiosta totta
KulOuuri
&
Johtaminen

51. Digitalisaation edellykset
1. Ymmärrys – kulttuuri, visio, roadmap,
2. Osaaminen – strategia,
toimintasuunnitelma
3. Työkalut – ympäristöt, organisaatio,
hankesalkku

52. KäyOöliiOymät
Vuorovaikutus
Sisällöt
Kumppanit
Asiakaspolku
Äly
AsioinU
Palvelut
AutomaaUo
Digivisio –asiakaskokemus?

53. Digiajan asiakaskokemus
INFRA
PROSESSIT
CRM
R&D
SCM
PALVELUT
MYMA
ASPA
ASIAKAS-
KOKEMUS

54. 5% technology 95%
culture & change management
Open
Close
Comms
Values
Production
R&D
Business models
Product
Marketing
Sales
Customer care
Experience
Network
NEXT

55. 170/100/100

56. Haasteita
1. Terminologia
2. Tuotelähtöisyys
3. Pistemäisyys
4. Sirpalemaisuus
5. Reaktiivisuus

57. Toimintasuunnitelma
1. Lähtökohdat (swot)
2. Tavoitteet, määrälliset & laadulliset
3. MWB toiminnoittain
4. Kehityshakkeet 12, 24, 36
5. ToSi = Tavoitteista totta
1. Kuka, Mitä & Milloin
Kilpailuetu
Toimituskyky
GTM

58. Tuotekehitys
&
innovaaUot
TyökulOuuri,
verkostot
ja
ekosysteemit
Tuotanto
&
jakelunhallinta
MarkkinoinU
&
myynU
Asiakaspalvelu
Analogiset
Sähköiset
Digitaaliset
-­‐prosessit
Mittarit - Digiprosentti
1.
Yrityksen
nykyiset
Sähköiset
ja
digitaaliset
Toimintamallit
2.
Benchmark
yli
Toimialojen
=
Mitä
käytössä
vs.
Parhaat.

59. Tee näin.
1. Arvoketju
2. Ymmärrys, osaaminen & työkalut
3. Roadmap, 1000pvå
4. Organisoituminen
5. Nopeat, helpot voitot
6. Tuloksellinen ja pitkäjänteinen tekeminen.

60. Arvoketju
• Missä kohtaa arvoketjua olemme parhaita?
• Mitkä toimijat uhkaavat tekemistämme?
• Mitä mahdollisuuksia digitalisaatio tuo
• Miten varmistamme kyvymme ajatella
liiketoimintamme asiakkaan/ulkopuolisen
silmin?

61. Digitaalinen liiketoimintaympäristö
Markkinat
Yleisö
Ekosysteemit
Asiakkaat
Ratkaisu
Arvo
1. Kevytyrittäjät, henkilöbrändit =
Artistit, kirjailijat, asiantuntijat, yrittäjät
2. Yritysten omat kanavat & Kauppapaikat
3. Yritysten yhteisöt esim. Novita, Pentik, Varusteleka
4. Kauppapaikat esim. Oikotie, autotalli, Amazon, jne.
5. Ekosysteemit esim. Tori.fi, Digitalist, jne.
Digitalist

62. 300
000
sivulatausta
12
000
seuraajaa
75
00
FB
fania
5000
Osallistujaa
4000
FB
ryhmässä
10
kumppania
”Digitalisoidaan Suomi
pikseli kerrallaan”
TBWA Digitalist Marketing Forum
Dingle Digitalist Social Business Forum
Ixonos Digitalist Customer Experience Forum
Technopolis Digitalist pop-up
MTV Digitalist 5M
Meltwater Digitalist Communications Forum
IBM Digitalist Leadership Forum
Salesforce Digitalist Growth Forum
Sonera Digitalist IOT Forum
Solita Digitalist Thinkers Forum
Digitalist Network 2016

63. Yritysmuotoilu & digitalisaatio
Liikeidea
Strategia
Johtaminen
Muotoilu
Digitalisaatio
YMMÄRRYS
OSAAMINEN
TYÖKALUT

64. Ekosysteemit, Yhteisöt & tekoäly ovat jo täällä. Digiaika on tänään, tässä ja nyt.

67. 3 November 2016
Confidential and proprietary: Any use of this material without specific
permission of McKinsey & Company is strictly prohibited
Machine learning
in the digital age

68. 68McKinsey & Company
Mindfulness – “The quality or state of being
conscious or aware of something”
Take a big breath and relax,
with your eyes open and looking
at the hourglass
Bring your awareness to the
sensations of breathing
You may softly count your breaths,
one to ten and then start over
Once your mind settles down
during the first few minutes,
get more absorbed in the breath
Be aware of whatever is moving
through the mind
1
2
3
4
5

69. 69McKinsey & Company
The Hour Glass
Your guide to
mindfulness
McKinsey & Company

70. 70McKinsey & Company 70McKinsey & Company
5/60
3% full
1/60
50% full

71. 71McKinsey & Company71
Section 1
“The trouble is you
think you have time”

72. 72McKinsey & Company 72McKinsey & Company
The Human
Genome Project
Timeline
1985
2000

73. 73McKinsey & Company
MIT announces that driverless car cannot
be implemented before 2030s
Autonomous
driving
2004
STOPSTOP
until 2030

74. 74McKinsey & Company
DARPA announces the "Grand Challenge"
for autonomous vehicles
2004/
2005
Autonomous
driving

75. 75McKinsey & Company
Google Car debuts and takes
a blind man for tacos
2010
Autonomous
driving

76. 76McKinsey & Company
Tesla announces driverless car with
ability to drive "across U.S." for mass
production S-model in 2017
2016
Autonomous
driving

77. 77McKinsey & Company
DeepMind’s
AlphaGo matches
in Spring 2016

78. 78McKinsey & Company
1883
1949
1979
2015
1913
+300,000
-10,000
Speed of
innovation

79. 79McKinsey & Company

80. 80McKinsey & Company80
Section 2
“Change is inevitable.
Progress is optional.”

81. 81McKinsey & Company
Question
VS.

82. 82McKinsey & Company
Connectivity and processing power
Billions of people connected on the go, unprecedented
processing power, storage, and knowledge access
New stakeholders vs incumbents
Value created by entrants that provide value from data
Incumbents threatened
New points of view
New way of looking at decisions and events across
physical, digital & biological worlds
New business models
Emergence of new disruptive business models
reshaping production, consumption and delivery
models
Incentives redefined
Intermediate players in value chain must enable
data, promote transparency
Why does machine learning matter

83. 83McKinsey & Company
End-to-end analytics transformation driven
by cultural and organisational change
Motorsports
CONTEXT
RESULTS
40%
JOURNEY
20%
• Formula 1 is the largest
racing series in the world
• Continuous in-season
engineering
improvements are key to
winning on the track
• Spend on testing is
heavily limited by
regulations
• Innovative use of
communication data to
find the most effective
R&D operating model
• Analytics-empowered
teams now able to focus
on optimising parts with
highest predicted
potential
Improvement in
investment yield
Earlier warning on
project performance
What is possible? CLIENT EXAMPLE

84. 84McKinsey & Company
Boosting
traditional
P&L levers
Delivering
the digital
model
Developing
new areas of
growth
Strategic
priorities
Gather and analyse
real-time data to fully
realise digital and
seamless multi-
channel experience
Explore new operating
and business models
Generate revenue and
improve margin, optimise
efficiency, control and
manage risks
What are the opportunities for you?

85. 85McKinsey & Company
Driving change across your company
Improve
Margin
Material cost reduction by reduced complexity
of components
5-10%
Inventory buffer reduction through improved
forecasting
>50%
Improved R&D productivity driving reduced time
to market
20%Revenue uplifts through improved sales
force effectiveness at same cost base
15%
Component
complexity
management
Supply chain
forecasting and
inventory
management
Digital
procurement and
R&D
Sales force cost
efficiency and
effectiveness
Yield
management
Yield improvement through improved planning
2-4%
Generate
Revenue
Improve MROI by
modelling marketing
spend effectiveness
300% 20%
Increase sales through
better Next Best Action
suggestions
Increase conversion by
tailoring commercial
solutions to customers
75%
Increase potential customer by identifying new high
potential customers
8-10%
Reduce churn rate
through improved
customer profiling
20-25%
Marketing
and new customer
onboarding
Product sales:
cross and up-
selling (NBA)
Value-added
services and
solution tailoring
Customer base
acquisition
Customer
retention

86. 86McKinsey & Company
Machine Learning Based Study
Largest 500,000 companies
350 TB unstructured business data
10 Million business relationships
100 Million people behavioural data
15 Billion page views
Classified companies into
levels of AI Maturity…

87. 87McKinsey & Company
Even where AI capability exists, maturity is low
Companies employing AI at scale
967
494
87Strategic direction for business
Building applications
Lab projects/proof of concept

88. 88McKinsey & Company
Application of AI concentrated in digital and
data based business
60%
in digital and
data based
businesses
Companies investing in AI by industry
Analyzed by spiderbook
8.78%
Internet
4.19%
Telecommunications
3.37%
Research
2.66%
Retail
2.55%
Marketing and advertising
32%
Software
information
technology
services
2.35%
Financial service
2.15%
Automotive
2.04%
Government administration
1.33%
Internet
1.33%
Telecommunications
1.33%
Research
1.53%
Retail
1.63%
Marketing and advertising
1.63%
Financial service
1.74%
Banking
1.84%
Management consulting
1.94%
Semiconductors
1.33%
Internet
0.92%
Internet

89. 89McKinsey & Company
Question
VS.

90. 90McKinsey & Company
The Fortune 1000 company churn rate
1973 1983 1993 2003 2013
35% 45% 60% 70%
Companies new
to the Fortune
1000
2023
over
80%
Companies
expected to
fall

91. 91McKinsey & Company91
Section 3
“May your choices
reflect your hopes,
not your fears.”

92. 92McKinsey & Company
What can you do for your company?

93. McKinsey & Company 93
# 1 Vision:
Unreasonable
aspirations

94. McKinsey & Company 94
# 1 Vision:
Unreasonable
aspirations
Vision Processes
Business
demand
Location
Sourcing
& partner
mgmt.
People
Organization
Architecture
Governance

95. McKinsey & Company 95
What does this mean?
What does this not mean?
▪ Board level "owner"
▪ Stretching and coherent vision
▪ Value-oriented targets
▪ Adding “analytics” to existing responsibilities
▪ Uncoordinated, one-off initiatives
▪ Slot time-to-market
# 1 Vision:
Unreasonable
aspirations

96. Decision
as the focal point
End-to-end
connection from data to
decision (people, IT,
processes)
Step-by-step approach
to enable organization
Use cases
96McKinsey & Company
# 2 Use cases:
Driving change

97. 97McKinsey & Company
# 2 Use cases: accelerator –what it means for an organisation
The
strategic question
Identify
similar
use cases
Develop
hypotheses
Embedding
Apply
analytics
Develop
decision
support
Break into
use cases
Design and
build the
data lake
Test and
refine
Insights
Factory
1
2
3
4 5
6
7
8
9
Links to Insights Factory

98. 98McKinsey & Company
# 2 Use cases: Accelerator – how to get it right
§ There is an opportunity to rapidly
capture significant value
§ The current business model has an
existing analytics interlock
§ You plan to use returns on high-
value use cases to finance an
analytics transformation
§ You need to quickly develop and
attract analytics talent
§ Forming silos with sub-scale teams
§ Failing to unlock value through synergies
§ Failing to change the wider organisational culture
§ Missing exploration of new business models due to focus on current problems
When to choose What to watch out for

99. # 3 Foundation
excellence
Flexible big data IT stack
(Lambda architecture)
IT/Infrastructure
Agile and flexible
software development
(e.g., scrum teams,
microservices)
IT/Software
New capabilities (data engineers and
scientists, analytical engineers,
software developers, GUI designers)
Capabilities and talent
Full spectrum of analytics from r
egression to ensembled learning
Analytics

100. 100McKinsey & Company
#3 – Foundation Excellence: what it means for an organisation
Culture Reactive to market
dynamics
Proactively taking advantage of
and defining market dynamics
IT Traditional warehouse
with siloed data
Integrated architecture based
on data lake
Organisation Traditional organisation
with CDO
Clearly defined roles in agile
organisational structure
Processes
Independently-designed
processes for each business
unit
Aligned, data-enabled processes
with organisation-wide
workflows
Recruit talent externally Build talent internallyEmployees
Data used by few to
manage efficiently
Democratisation of dataData
Central closed platform,
capable of basic analytics
Distributed open platform used
for advanced analytics
Analytics
Decisions based on
periodic reporting
Decisions made in real time
Performance
management
From To

101. 101McKinsey & Company
#3 – Foundation Excellence: how to get it right
101McKinsey & Company
When to
choose
What to watch
out for
When to choose What to watch out for
§ There is clarity on specific needs for use cases
§ It is possible to pilot in smaller business units
§ There is strong political will to implement the programme
§ Long term foundation-only projects
§ ‘Build it and they will come’ mentality
§ Uncontrolled data ingestion

102. 102McKinsey & Company
What can you do
for yourself?

103. Personal experience:
Building your digital
& analytics skills
Example:
Pursuing “analytics”
enlightenment
(e.g., through Coursera)
§ Code in a day
§ Data in a day
§ Hacking in a day
§ Tech in a day
§ Innovation in a day
1.
Innovation
Data Skills
Leadership Infrastructure

104. Personal experience:
Visiting the disruptors
Example:
Doing a Board offsite at a
Silicon Valley ‘bootcamp’
2.
Silicon Valley – still the capital of
tech

105. McKinsey & Company
And it is not just
the Valley!

106. Personal experience:
Establish Analytics
Advisory Council
3.
Serial analytics
entrepreneur
CDO of non-
competing firm
Technology leader
“Wacky” digital
evangelist/futurologist
CEO of a tech
start-up bootcamp
Senior partner
at a tech VC fund
Digitalle/savvy
customer of the company

107. Personal experience:
Get a reserve mentor
4.

108. Personal experience:
Five at five
5.

109. 109McKinsey & Company109
Section 4
“Those who
cannot
change their
minds
or ways
cannot
change

110. Learn,
don’t protect.
“Leadership
and learning are
indispensable
from each other.” –
JF Kennedy

111. Be an adaptive
leader – not a
technical one.
Beta 13-40 Hz
Alpha 7-13 Hz
Theta 4-7 Hz
Delta 0-4 Hz

112. “A problem
cannot be
solved at the
same level of
consciousness
that created it.
You must learn
to see the
world anew.”
- Einstein
Serve others rather
than yourself.

113. McKinsey & Company
Let go, don’t
be attached.
“It is not because things
are difficult that we do
not dare, it is because we
do not dare that they are
difficult.”– Seneca

127. 127

154. The only way is forward
@tommituovila
@nestecorp

158. © Wärtsilä
In one year:
We serve
12,000 customers
115,000
deliveries,
constituting
more than
900,000 line
items, packed
in 134,000
packages Around 106,000
transportations making
use of roughly 150
carrier modalities
Our 3,600 field service
professionals perform 100,000
field service jobs
16,300,000 kg
of parts, with a total
volume of 46,700 m3
66,700
export
declarations
We maintain knowledge and
skills for 350 different product
types
117,000
unique
materials
stored
We provide
100,000
technical
answers
We maintain 600
installations under
long-term contract
...One promise
to the customer:
We offer expertise,
proximity and
responsiveness for all
customers in the most
environmentally sound
way.
WÄRTSILÄ SERVICES

159. © Wärtsilä
12,000
Customers
100,000
Field Service and
workshop jobs
450
Installations with
long-term
contracts
900,000
Parts
order lines
350
Product
types
20,000
Technical
answers
Ei kädet ristissä
rikkaiksi tulla.

160. © Wärtsilä
Minkä ilotta oppii, sen
surutta unohtaa.

161. © Wärtsilä
Kysyen kylän löytää.

162. © Wärtsilä
Kylhä työlki elää,
mut kaupal rikastuu.

163. © Wärtsilä
POHJA-
TYÖ
UTELIAS
MIELI
TUKIJOUKOT
ASIAKAS-
ARVO

164. © Wärtsilä

166. DREAMFORCE TO YOU 2016
ENABLING PERSONALISED
CUSTOMER JOURNEY
@arivee_
www.linkedin.com/in/arivant
CMO Ari Vänttinen, Comptel Corporation

167. “ YOU CHANGE THE
STORY AND YOU WILL
CHANGE THE
BUSINESS.

168. MARKETING
FOR GOOD!
NEW ERA

169. WE ARE LIVING MAGICAL
TIMES IN MARKETING.

170. Why-How-
What?

171. GENERATION
FLUX IS
IN CHARGE
NOW.
1) POWERSHIFT

172. “ I WANT” “THANK YOU
SUCCESS FORMULA
“ I WANT”
“THANK YOU”

173. 1) MOBILE
YOUR CUSTOMER
IS MOBILE!
Mobile is
the new TV!

174. VIRALITYDEMANDATTENTI
ON
3) MARKETING ROI

175. Why?
POWER
SHIFT
CUSTOMER
IS MOBILE
MARKETING
ROI

176. Why-How-
What?

177. FORGET
B2B, B2C
-----
YOU ARE IN
BUSINESS TO
MOMENTS!
1) CREATE VALUE IN-THE-
MOMENTS

178. “I WANT”
“I NEED”
“I BUY”
“I CHOOSE”
“I LEARN” - MOMENTS
PERCEIVED VALUE CURVE
DELIVER VALUE HERE!

179. STOP
BUYING
ATTENTION,
START PAYING
ATTENTION!
2) FROM CAMPAIGNS TO
JOURNEYS

180. HELLO WORLD,
I AM THE
INTERNET OF
ME
3) IT´S NOT ABOUT THE
CUSTOMERS BUT A CUSTOMER

181. MASS
YOUR MARKET USED TO BE HERE!
YOUR MARKET WILL BE HERE!
LONG TAIL

182. How?
CREATE VALUE
IN-THE-MOMENTS
FROM CAMPAIGNS
TO JOURNEYS
THINK NOT THE
CUSTOMERS
BUT A CUSTOMER

183. Why-How-
What?

184. DATA REFINERY -­‐
INTELLIGENT
FAST
DATA
FABRIC
™
FASTERMIND™
Customer Engagement
Intelligence & Automation
• Engagement actions
• Journey Builder
• Next Best Actions
• Recommendations
• Real Time Profiling
Relevant Other DataRelevant Fast Data
CUSTOMER ENGAGEMENT
AUTOMATION
ACTIONS IN THE MOMENTS
MACHINE LEARN. OPTIMIZE .SCALE
Channels

185. Thanks!
Let’s amaze
customers.

186. THE FIRST 50 JOIN FREE!
GO TO
NEXTERDAYNORTH.COM
FREE CODE:
Nexterday4Salesforce

213. www.salesforce.com/fi/blog