new business model in smart cities: emerging trends and ... · pdf filenew business model in...

New business model in smart cities: Emerging trends and methods of

analysis

Paolo Neirotti ‐ Politecnico di Torino

Department of Management and Production Engineering

Smart City Finance & Technology Program

Master Smart Cities Politecnico di TorinoTorino – 11 Aprile 2013

Goals of the lecture• Understand business modes for the delivery of “smart”

services– How is economic value created?– How do the private and public sectors appropriate economic value?

win‐win relationships?

• Provide concepts and tools to interpret business models andvalue generation (Rich Picture, Business Model Ontology)

• Understand new value chains in the smart city w.r.t.:– Technologies– ICT‐related services

• Discuss the main critical elements in the technological choicesthat cities must take

Politecnico di Torino

Outline of the lecture• Smart cities initiatives may require innovation in business models, namely new ways through which the private and public sector generate and distribute economic value

• Business models as…– …new rules to generate economic and social value in smart cities: current trends and critical points (part 1 theory and facts)

– ….new flows through which economic value is generated, new coordination mechanisms among different actors (part 2 value chains)

– ….methods and tool to assess the economic and contractual sustainability of new initiatives (part 3 business model representation)

Part 1. Some theory and facts on how economic value can be generated in the smart city

Innovation in smart cities: discontinuitiesAcceptance of new technologies and practices can be troublesome:

– e.g. Usage of smart meters in 2009 a in Bakersfield (CA) has been sued through a class action againts PG&E

Smart city as rise of new behavioural patterns: from property to service, increased environmental awareness, more civic participation, new patterns of consumption, new ways for managing social relationships, new financing mechanisms.

Techno‐logical change

Changes in meaningsSource: adapted from Verganti, R. (2009). Design‐Driven Innovation – Changing the Rules of Competition by Radically Innovating What Things Mean: Harvard Business Press

Techno‐logy

epiphany

Incremental Radical

Incremental

Radical

Investments in new infrastructure areneeded: long pay back, longinstallation times, uncertainty on theevolution of costs and performancefor the enabling technologies, lock‐inrisk, difficult to estimatecomplementarities amongtechnologies,

Creation of value in the smart cityStakeholders dellacittà

Driver di valore economico e sociale

Public sector (Citymanagers)

1. Economic development ( growth of GDP, employment, exports, Foreign Direct Investment)

2. Quality of life indicators3. Cost‐to‐serve the citizen4. Environmental sustainability (less emissions)5. Social sustainability (less divides)6. Less negative externalities (dynamic pricing may favour

internalization of externalities)

Firms 1. New markets and new revenue opportunities2. Productivity growth

Citizens 1. Cost savings (in energy, transportations, etc.)2. Higher productivity (savings in time)3. Empowerment (see the Iceland’s quite revolution)


Smart cities in the world: some findings

The number of domains covered by “smart initiatives” is related:

Curvilinearly to city size (taking a U‐shaped relationship)

Population density

Today there is no correlation between city’s wealth and domains covered


From a sample of about 100 cities world‐wide

Population (logarithimic scale)31 100 316 1.000 10.0003.162 31.622

Population (thousands omitted)

Great heterogeneity in the initiatives. Not a flat world.

Smart cities in the world: some findings

Asian cities are active on a higher number ofdomains due to:1. Most critical needs (e.g. Climate and

population density)2. Fewer financial constraints and more

centralized decision‐making

European cities are more active on projects related to smart grids, renewable energies, and policies for entrepreneurship and human capital (“Lisbon Agenda effect”)

There are no systemic approaches to the design of smart cities

Prevalence of “technology‐push” initiatives (in Italy, in particular)


Smart cities in the world• Why a U‐shaped effect in the relationship between city size

and number of domains covered by smart initiatives?• On the one hand, small cities..

– are the ideal settings for pilot projects– Deal with shorter installation time when an investment in new

infrastructure is needed (e.g. street lighting, smart waste) – Less inertia in IS infrastructure (green field)

• On the other, Large cities…– have more critical needs– Already have the information system infrastructure – Have the critical mass of users for new technologies and

practices (e.g. new businesses can more quickly scale up –> Buschecker)

– Can more easily attract more human and financial capital

An example of a non repeatable businessElectric Vehicles (EV) 3 problems w.r.t. the battery of EV1. Price (dai 6 a 12 k€)2. Recharging time 3. Duration

Car manufacturer

EV €(lump sum)

The consumer owns the car(But not the battery)

Better Place

Battery switch stations

Charge spot

electricity

Charged battery

Package of electricity for a given # Km per year

€ annual subscription fee

government

€ (debt capital)

Coordination for standard in battery and interfaces

Leases battery to car owners

€ tax incentives/discount on EV

Electricity spot

market

Green Energy Systems

Lower CO2 emissions!

No CO2 emissions!

VC funds

Electricity supply

€ (equity)

Stakeholder Economic Value Changes required

Motorist Reduction in the Total cost of ownership

‐ New process of purchase of the (where, how and when recharge the battery?)

Firm New market, new revenues Build the supply chain of a new sector Define and enforce standards and the achitecture for the EV

Public sector Less CO2 emissionsdevelopment of the local clean‐tech cluster

Create the conditions for an efficient and competitive electricity supply.Tax incentives to motorists purchasing an EV

An example of a non repeatable business model

Limited scalability/replicability of business model ‐ > it works where: 1. The supply of clean energies is already well developed(Israel w.r.t. solar energy,

Denmark for wind energy)2. Driving distance are limited small and isolated countries

Smart Grid

Public lighting

Renewable energies

Waste

Agricolture Water man.

City logistics

Infomobility

Mobility services

Smart Building (services)Facility mngmt

Entertainment

HospitalityPollution control

Housing quality

Public safety Healhcare

Social inclusion

CulturePublic spaces

E‐government

E‐dem.

E‐Procurement PA

Trasparency PA

Eneterpreneurship

Cultural heritage

Education

Human capital

0%

10%

20%

30%

40%

50%

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

Italy (%

cities with

initiatives)

Rest of the world(% cities with initiatives)

Covered domains in Italian cities vs. “Rest of the World”


Obstacles to smart city developments

• Financial – Budget availability for smart city initiatives follows the economic cycle: big top‐down project have been delayed (e.g. Masdar, Songdo) most successful initiatives are “frugal” and bottom‐up (e.g. Amsterdam)

– New business model must be created. How to share economic value between public and private partners? Who are the “residual claimants”?

– Which city‐level metrics for measuring the impact of smart initiatives? “Before decide the strategy, then choose the metrics”


• Technological – Many domains of interventions (logistics, energy, water, waste, surveillance, etc.)…but information sylos still exists Lack of technology standards for data, technologies, etc.

• Greenfield investments (e.g. Songdo) can achieve a native integration of IS in the various domains

– Digital divide (it leads to a social divide and to the empowerment of elites)?

– The duration of the investments in infrastructure can be longer than the life cycle of the technology (e.g. smart street lighting)


• Organizational– Governance of smart cities investments. Who has the accountability for deciding and executing investments in new initiatives?

– Which type of governance model among the various entities in a city?

• Monarchy? • Feudal? • Federal?

Governance of smart city initiatives

• A central body:– Designing the smart strategy for the city– Defining how IT can serve to the execution of the city strategy

– Prioritizing IT investments– Defining and enforcing technological standards

• Attention to backward compatibility of information systems , especially for investments in infrastructure that require long period of installation (e.g. in a large city the entire installation of smart street lamps may take 10 years)

Recap• Not a dominant paradigm of a smart city• City size matters

– Small cities are ideal for frugal approaches and pilot projects

• Prevalence of non‐systemic and “technology push” approaches to smart cities

• Analogies with the problem encountered in IT investments in large enteprises

• A federal governance is needed • Delay of Italian cities in the domains where:

– Investments in the infrastructure are needed– Public‐private partnerships are needed– New business models must be created

• Technological, organizational and financial obstacles exist

Part 2. Value chains in the smart city

Relevant technological trends for smart cities

• Big and open data• Urban platforms • Mobile platform three key attributes

– Ubiquity – Identifiability

• SIM cards have a unique identifier (both for identity and payment)– Context awareness

• A GPS receiver in smartphones can communicate their position to any software application

– Problems: low internet speed and small screens. Still relevant with LTE networks and the diffusion of tablets?

• Augmented reality: – Not yet clear the applications of AR for value creation:

• Tourism (e.g. Voyager Xdrive) and entertainment?• Infomobility (relevant to car manufacturers?)• …

19

Value chain in information services for smart cities

• New urban software platform. (es. Intelligent Operating Center di IBM, Plan IT Valley) analogous to the operating system in a PC– An ecosystem around the new “operating system” for complementary

software applications (e.g. for videos surveillance, public lighting)– Trade‐off between replicability of the solution and costs induced by

technological di lock‐in on the long term• Other “stand‐alone” applications (e.g. StreetBump) • Firms focused on infomediary services many two‐sided markets

(es. Google, Streetline, Tripadvisor).

Digital Data generation

Tlc infrastructure management: Connectivity

Data fusion and management

Service delivery applications

Sensor technology

Urban Operating System

Urban infrastructure mngmt.: roads, parking, public lighting, etc

Software appsAPIs

Primary activities

Support activities

Business models of technology providers

• Sensors and other OEM devices. Sell the technology

• Platform leaders a la Microsoft (IBM, Living Planet) – Sell the platform – Control the revenues from the “ecosystem” of complementary‐compatible software products


• Service delivery can be based on:– Real‐time analytics: for infomobility, energy retailing, etc.– Real‐time tracking

• donteat.at in NYC, links with Fousquare to send an alert when a user is about to book a table at a restaurant that is at risk of being closed for hygiene violations

• buschecker (http://www.buschecker.com/): real‐time, live information, based on GPS receivers located inside each actual bus). Sold at 2.99 USD on Apps store

– Aggregation of contextual real‐time data (e.g. MyCityWay)– Infomediation (e.g. in healthcare, real estate properties, market

(both B2B and B2C))• Cities can be a generator of open data, but even a user

(to improve the decision‐making process of city managers and policy‐makers).


• Less vertical integration. Who delivers the service is not the entity that has generated the data

• Drivers of vertical de‐integration are manifold:– Some firms/entities generate data that have a low marginal value for them (e.g. Telcos and city municipality)

– Search for firms with complementary physical assets (e.g. the partnership between Turin’s Registry Office and Poste Italiane)

– Some firms have developed the interface with customers (e.g. Google) but not have the data (e.g. Google buys infomobility data from TomTom)

What business models for open data?

• Data generation can be costly (cleaning, fusion, dynamic delivery)

• Should local governments deliver open data for free?• Open data as a way to improve budget, lower taxation,

encourage the delivery of new services and start‐ups– In the UK the Open Data Institute aims to make more official

data available and to train people how to use it to commercial and other ends

• Or just to create more welfare? for free or at the marginal cost of producing the data

• Open data are Not only a key ingredient for new business and revenue model. They can also be a way to increase transparency and inform the citizen (information is a key requirement for empowerment): – e.g. The London Data store

Recap• New value chains for IT and information services are formed.

• Open public data as the key input for new business models.

Part 3

Methods for Business model representation

Innovation in business model

• A business model describes the rationale of how an organization creates, delivers, and captures value.

• Reference book: Osterwalder and Pigneur, 2010, Business Model Generation

• 9 building blocksHow to deliver value How to create value

Value proposition Revenue streams

Customer segments Cost structure

Channels (distribution and sales) Key resources

Customer relationships Key activities

Key partners

These are key blocks!

Key partnerships

Key activities Value propositions

Customer relationships

Customer segments

Key resources Channels

Cost structure Revenue streams

KP

KA

KR

C$

CR

CS

CH

R$

The right canvas. Value generation

• Value proposition – It seeks to solve customer problems and satisfy customer needs with a product

or a service.– Must be compelling! (solving a real problem for customers)

• Customer segments– Group of customers with homogeneous needs and approach towards the focal

firm’s products/services– Which type of segments? Niche or mass market?

• Customer channels– Value propositions, products, services are delivered to customers through

communication, distribution, and sales Channels• Customer relationships

– How the focal firm maintains the relationship with the customer (how the customer contact begins, in which way customers are retained and are served after sales, etc.)

• Revenue streams– In which way are revenues generated? For what and how does the customer

pay?(e.g. “freemium”, subscription fees, usage fees, “as‐pay‐as you go” pricing)

The left side of canvas – efficiency • Key resources

– the assets required to offer and deliver the products/services at the basis of the value proposition

• Key activities – The activities that must be performed to offer and deliver the products/services

• Key partnerships – Some activities are outsourced and some resources are acquired outside the enterprise.

• Cost structure– Which cost structure for using the resources and the partnerships to perform key activities

Key partnerships



Customer segments

Key resources

Channels


Stadium management

Host attractive

sport events (soccer, rugby)

Host big events (e.g. concerts)

Host/manage 360° events

(e.g. shopping, marriages, etc.)

Soccer Teams

Entertainment companies

Wedding planners

Merchants

Concession and renting fees Advertising and

sponsorships

Advertising agencies

Facility management

Brand management

Venue management

Citizens

multi‐sided market

Event mng. firms

administrative and marketing OpEx

Facility management (cleaning,

conditioning, lighting)

CAPEX for the infrastructure

Position

maintenance

Stores

VIP loungesTouristic operators/bureausAds

Stadium management

• Which type of Public private partnership? • A multi‐year concession to whom? a special purpose firm? The city soccer club?

• Which type of profit‐maximising scheme for the city?

• Which type of firm is more able to exploit the complementarities among the various resources of the stadium ecosystem (soccer club’s brand, spaces, contents)?

Some examples: Google Live Transit

Google Live TransitCitizens

Transit companies

Merchants

data €Car/bike sharing

companies

€Slots for mobile ads

Mobile commerce € €

How can I go from PoliMI to PoliTO, departing at 8,30

am?

Do U want 2 tickets for the exhibition at

OGR?

It is a service providing real‐time transit updates to users

of Google Maps. (live departure and arrival times to transit stations, service

alerts, etc.)Information useful for “door‐to‐door” journey planning

Some examples: Google Live Transit

• Who pays for the data?• Two sided markets theory suggests the sides with less price elasticity. Thus, merchants?

• …or local transit companies (which are data generators)? In the airline industry, airline carriers pay “infomediaries”…(e.g. Sabre, Cheapfligths.com)

• Are the same competitive dynamics of the airline industry applicable also to local city transportation?

Value chain in big data for infomobilityData

generation

Data aggregation

Data elaboration

Data visualization

Retail

Crowdsourcing (e.g. Waze), Telcos, municipalities, insurance firms, navigation companies , Google

Inrix, BusChecker

Web portals, Radio and TV networks, navigation firms providing real‐time traffic information

Data tran

sportatio

n

Microsoft MapPoint, Quantum GIS, Wikitude (AR)

Infrastructure fo

r data elab

oration

(e.g. d

ata storage)

Value chain in big data for infomobility

• Customer segments can be – B2C (Business to consumers)

• Motorists, in particular for having real‐time information/forecasts on traffic and driving time

– B2B (Business to business)• Radio, TV, web portals broadcasting real time traffic info• Municipalities (e.g. for real time coordination of traffic lights, monitoring of air pollution)

• Car ways companies• Police departments• Insurance firms• Advertising firms• And potentially many others?

Discontinuities in the infomobility sector

TomTom

Garmin

2010

Share Price

Key partnerships



Customer segments

Key resourcesChannels


Google in the infomobility sector

Provide real‐time transit updates

Free navigator

Real‐time traffic info

Citizens (user of public transit)

Motorists

Merchants

Infomobilityoperators?

Apps developers

Freemium?(for motorists)

Big Data fusion,

cleaning, etc.

Data storage

Lump sum + Usage fees (e.g. click through rates) for transit companies,

merchants, sw developers

Multi sided market

Big Data fusion,

cleaning, etc.

Navigation companies

Google play (app store)

Car manufacturing

firms?

Maps making

Apps development

Marketing and Sales

Ideas in search for a business model: the case of Infoblu Traffic for Milan

• Free Apps for smartphones: InfobluTraffic for Milan

• Detailed localization of traffic congestion in the main ways to enter the citiy

• Routing of vehicles based on real‐time traffic monitoring

• Integration with real time data about parking availability, real‐time scheduling from the public transportation systems.

• What for the future? Which business models about a nice‐to‐have application? Freemium? What Willingness to pay for motorists?

Informazioni di Traffico

Congestionato Scorrevole

Smart Public lighting• New economics for LED streetlamps

– Lamps can be monitored remotely, light can be “informatized” and modulated and dimmed (for cities light can be no longer a fixed committed cost, but a variable discretionary cost)

– Lower operations and maintenance costs, longer useful life– Light consumption metered at the level of each streetlamp

• Street lamps as the platform for the delivery of other services ? – security video applications, traffic monitoring and environmental

readings (e.g. pollution, carbon dioxide, and air quality), ads, re‐charging sports for EV, Wi‐Fi hot spots,

• Who control the cash flow generated by these services? – Revenue sharing mechanisms– A new business for energy companies? – Sell the data? To whom?

• And who does manage the monitoring system for street lighting? The city? The provider?

Recap• New value chains are formed

• New entrants in traditional business (e.g. maps and infomobility)

• New business models must still be developed – some nice‐to‐have services in search of Revenue streams and a

compelling value proposition

• Critical mass is needed to achieve success in many initiatives (e.g. mobility, public lighting)

• How does the city control value and “skim profits” to private partners?

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