dreamforce to you helsinki 3.11.2016

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


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


MIT announces that driverless car cannot

be implemented before 2030s

Autonomous driving

2004 STOP STOP

until 2030


DARPA announces the "Grand Challenge" for autonomous vehicles

2004/ 2005

Autonomous driving


Google Car debuts and takes a blind man for tacos

2010

Autonomous driving


Tesla announces driverless car with ability to drive "across U.S." for mass production S-model in 2017

2016 Autonomous driving


DeepMind’s AlphaGo matches in Spring 2016


1883

1949 1979

2015

1913

+300,000

-10,000

Speed of innovation


Section 2 “Change is inevitable. Progress is optional.”


Question

VS.


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


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


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?


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


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…


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


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


Question

VS.


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


Section 3 “May your choices reflect your hopes, not your fears.”


What can you do for your company?

McKinsey & Company 93

# 1 Vision: Unreasonable aspirations



Vision Processes

Business demand

Location

Sourcing & partner

mgmt.

People

Organization

Architecture

Governance


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


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


# 2 Use cases:

Driving change


# 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


# 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


#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


#3 – Foundation Excellence: how to get it right


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


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.


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

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.

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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