dreamforce to you helsinki 3.11.2016
TRANSCRIPT
koulutus
#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
”Etsimme uutta internetistä, vaikka ainoa tehtävä olisi mullistaa vanha.”
Digitalisaation tehtävä on luoda enemmän ja parempaa vähemmällä.
Digitalisoiminen on paras, tehokkain ja halvin tapa luoda uutta arvoa.
Digijuna yritysten ja toimialojen välillä pitenee.
Ollakseen ”strateginen” on oltava keskeinen osa arkea.
Kulttuuri ahmii strategioita aamupalaksi.
Data, järjestelmät, prosessit, arvoketjut, siilot, ATK
Arvo, Tieto, Ekosysteemit, Asiakaskokemus
Ekosysteemit, Alustatalous, Yhteisöt & Asiakaskokemus
Janatodellisuus Markkinat Arvoketjut Ratkaisut Materiaalit
Ympyrätodellisuus Ekosysteemit Arvoverkostot
Arvo Asiakkaat
TRANSFORMAATIO
Asiakaskokemus
Infrastruktuuri
Työ, verkostot
Prosessit Toimintamallit,
Transformaatio – Digitalisaatiosta totta
KulOuuri & Johtaminen
Digitalisaation edellykset
1. Ymmärrys – kulttuuri, visio, roadmap, 2. Osaaminen – strategia,
toimintasuunnitelma 3. Työkalut – ympäristöt, organisaatio,
hankesalkku
KäyOöliiOymät
Vuorovaikutus
Sisällöt Kumppanit
Asiakaspolku Äly AsioinU Palvelut
AutomaaUo
Digivisio –asiakaskokemus?
Digiajan asiakaskokemus
INFRA
PROSESSIT
CRM
R&D SCM PALVELUT MYMA ASPA
ASIAKAS-KOKEMUS
5% technology 95% culture & change management
Open
Close
Comms
Values
Production R&D Business models
Product Marketing Sales Customer care Experience Network
NEXT
170/100/100
Haasteita
1. Terminologia 2. Tuotelähtöisyys 3. Pistemäisyys 4. Sirpalemaisuus 5. Reaktiivisuus
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
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.
Tee näin.
1. Arvoketju 2. Ymmärrys, osaaminen & työkalut 3. Roadmap, 1000pvå 4. Organisoituminen 5. Nopeat, helpot voitot 6. Tuloksellinen ja pitkäjänteinen tekeminen.
Arvoketju
• Missä kohtaa arvoketjua olemme parhaita? • Mitkä toimijat uhkaavat tekemistämme? • Mitä mahdollisuuksia digitalisaatio tuo • Miten varmistamme kyvymme ajatella
liiketoimintamme asiakkaan/ulkopuolisen silmin?
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
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
Yritysmuotoilu & digitalisaatio
Liikeidea
Strategia
Johtaminen
Muotoilu
Digitalisaatio
YMMÄRRYS
OSAAMINEN
TYÖKALUT
Ekosysteemit, Yhteisöt & tekoäly ovat jo täällä. Digiaika on tänään, tässä ja nyt.
`
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 McKinsey & 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 McKinsey & Company
The Hour Glass Your guide to mindfulness
McKinsey & Company
70 McKinsey & Company 70 McKinsey & Company
5/60 3% full
1/60 50% full
71 McKinsey & Company 71
Section 1 “The trouble is you think you have time”
72 McKinsey & Company 72 McKinsey & Company
The Human Genome Project
Timeline
1985
2000
73 McKinsey & Company
MIT announces that driverless car cannot
be implemented before 2030s
Autonomous driving
2004 STOP STOP
until 2030
74 McKinsey & Company
DARPA announces the "Grand Challenge" for autonomous vehicles
2004/ 2005
Autonomous driving
75 McKinsey & Company
Google Car debuts and takes a blind man for tacos
2010
Autonomous driving
76 McKinsey & Company
Tesla announces driverless car with ability to drive "across U.S." for mass production S-model in 2017
2016 Autonomous driving
77 McKinsey & Company
DeepMind’s AlphaGo matches in Spring 2016
78 McKinsey & Company
1883
1949 1979
2015
1913
+300,000
-10,000
Speed of innovation
79 McKinsey & Company
80 McKinsey & Company 80
Section 2 “Change is inevitable. Progress is optional.”
81 McKinsey & Company
Question
VS.
82 McKinsey & 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 McKinsey & 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 McKinsey & 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 McKinsey & 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 McKinsey & 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 McKinsey & Company
Even where AI capability exists, maturity is low
Companies employing AI at scale
967
494
87 Strategic direction for business
Building applications
Lab projects/proof of concept
88 McKinsey & 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 McKinsey & Company
Question
VS.
90 McKinsey & 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 McKinsey & Company 91
Section 3 “May your choices reflect your hopes, not your fears.”
92 McKinsey & Company
What can you do for your company?
McKinsey & Company 93
# 1 Vision: Unreasonable aspirations
McKinsey & Company 94
# 1 Vision: Unreasonable aspirations
Vision Processes
Business demand
Location
Sourcing & partner
mgmt.
People
Organization
Architecture
Governance
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
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
96 McKinsey & Company
# 2 Use cases:
Driving change
97 McKinsey & 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 McKinsey & 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
# 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 McKinsey & 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 internally Employees
Data used by few to manage efficiently Democratisation of data Data
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 McKinsey & Company
#3 – Foundation Excellence: how to get it right
101 McKinsey & 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 McKinsey & Company
What can you do for yourself?
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
Personal experience: Visiting the disruptors
Example: Doing a Board offsite at a Silicon Valley ‘bootcamp’
2.
Silicon Valley – still the capital of
tech
McKinsey & Company
And it is not just the Valley!
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
Personal experience: Get a reserve mentor
4.
Personal experience: Five at five
5.
109 McKinsey & Company 109
Section 4 “Those who cannot change their minds or ways cannot change anything.”
Learn, don’t protect. “Leadership and learning are indispensable from each other.” – JF Kennedy
Section 4 “Those who cannot change their minds or ways cannot change anything.”
Be an adaptive leader – not a technical one.
Beta 13-40 Hz
Alpha 7-13 Hz
Theta 4-7 Hz
Delta 0-4 Hz
“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.
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
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The only way is forward @tommituovila @nestecorp
© 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
© 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.
© Wärtsilä
Minkä ilotta oppii, sen
surutta unohtaa.
© Wärtsilä
Kysyen kylän löytää.
© Wärtsilä
Kylhä työlki elää,
mut kaupal rikastuu.
© Wärtsilä
POHJA-
TYÖ
UTELIAS
MIELI
TUKIJOUKOT ASIAKAS-
ARVO
© Wärtsilä
DREAMFORCE TO YOU 2016
ENABLING PERSONALISED CUSTOMER JOURNEY
@arivee_ www.linkedin.com/in/arivant
CMO Ari Vänttinen, Comptel Corporation
“ YOU CHANGE THE STORY AND YOU WILL
CHANGE THE BUSINESS.
MARKETING FOR GOOD!
NEW ERA
WE ARE LIVING MAGICAL TIMES IN MARKETING.
Why-How-What?
GENERATION
FLUX IS IN CHARGE
NOW.
1) POWERSHIFT
“ I WANT” “THANK YOU”
SUCCESS FORMULA “ I WANT”
“THANK YOU”
1) MOBILE
YOUR CUSTOMER IS MOBILE!
Mobile is the new TV!
VIRALITY
DEMAND ATTENTION
3) MARKETING ROI
Why?
POWER SHIFT
CUSTOMER IS MOBILE
MARKETING ROI
Why-How-What?
FORGET B2B, B2C
----- YOU ARE IN
BUSINESS TO MOMENTS!
1) CREATE VALUE IN-THE-MOMENTS
“I WANT” “I NEED” “I BUY” “I CHOOSE” “I LEARN” - MOMENTS
PERCEIVED VALUE CURVE
DELIVER VALUE HERE!
STOP BUYING
ATTENTION, START PAYING
ATTENTION!
2) FROM CAMPAIGNS TO JOURNEYS
HELLO WORLD,
I AM THE INTERNET OF
ME
3) IT´S NOT ABOUT THE CUSTOMERS BUT A CUSTOMER
MASS
YOUR MARKET USED TO BE HERE!
YOUR MARKET WILL BE HERE!
LONG TAIL
How?
CREATE VALUE IN-THE-MOMENTS
FROM CAMPAIGNS TO JOURNEYS
THINK NOT THE CUSTOMERS
BUT A CUSTOMER
Why-How-
What?
DATA REFINERY -‐ INTELLIGENT FAST DATA FABRIC ™
FASTERMIND™ Customer Engagement
Intelligence & Automation
• Engagement actions • Journey Builder • Next Best Actions • Recommendations • Real Time Profiling
Relevant Other Data Relevant Fast Data
CUSTOMER ENGAGEMENT AUTOMATION
ACTIONS IN THE MOMENTS
MACHINE LEARN. OPTIMIZE .SCALE
Channels
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