New business model in smart cities: Emerging trends and ... · PDF fileNew business model in...
Transcript of 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)
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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
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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)
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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”
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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”
Obstacles to smart city developments
• 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)
Obstacles to smart city developments
• 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
Value chain in information services for smart cities
• 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).
Value chain in information services for smart cities
• 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
Key activities Value propositions
Customer relationships
Customer segments
Key resources
Channels
Cost structure Revenue streams
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
Key activities Value propositions
Customer relationships
Customer segments
Key resourcesChannels
Cost structure Revenue streams
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?