Paolo Neirotti, Politecnico di TorinoBusiness models and new value chains

for big data

Big data as a source of GDP and wealth! But for which nations?

Big data and business models: crucial issues

● Go beyond hypes and fads

● Which opportunities for SMEs and large enterprises?

● Are open data economically exploitable?

● In many industries, business models around big data are not clear yet. – What services and what compelling value proposition?

– For what market segments?

A FOCUS ON THE INFOMOBILITY SERVICE INDUSTRY

Four reasons for a focus on the Infomobility industry

1. Mature industry (e.g. maps) before the discontinuity produced by Internet and mobile business

– New entrants (e.g. Google, Nokia, and many startups)– Mergers and acquisitions (e.g. Nokia and Navtech, TomTom and

Atlas, – Convergence with other industries

● directories/advertising (Google and the attempt to acquire Groupon)● Car manufacturing (e.g. GM and OnStar)

2. In location-based services big data, customer co-creation, and crowdsourcing are a reality more than in any other industry.

3. Cities are a generator of big data. Can they become “data retailers” or wholesalers?

Four reasons for a focus on the Infomobility market

● 4. the number of broadband mobile devices is increasing Just at the beginning of the S-curve

Discontinuities in the infomobility sector [1]● Factory-installed GPS equipment: around 1,500 €

● After-market GPS navigation into the car dashboard: 1,000 €

● Portable GPS device (Garmin, Magellan, TomTom): from 35 €(“plain vanilla” service) to 200 € (live traffic data)

● Google Maps Navigation: FREE

● Many other “low-cost” apps for mobile linking information about point of interests, alerts for speed-limits and camera. business for start-ups (e.g. Waze)

Discontinuities in the infomobility sector [2]

TOMTOM

Garmin

2010

Share Price

Repositioning towards  B2B: licensing maps and live traffic data delivery to car makers (e.g. PSA, Renault)Not producing the HW anymore!In search for new markets in the B2C: e.g. fitness smart watch 

Digital maps: not a business for many

● Time compression economies exist!

Big Barriers to entry exist! (time is needed to accumulate data)…

Value chain in big data for infomobilityData 

generation

Data aggregation

Data elaboration

Data visualization

Data Retail

Crowdsourcing (e.g. Waze, Open Street Map), open governmental data, telcos, municipalities, insurance firms, navigation companies , Google.

Inrix, BusCheckerMapbox

Google, 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)

High value added activities in the infomobility service industry

● Data generation for real-time traffic (e.g. Google through the service “My location” on mobile phones with Android)

● Data elaboration and cleaning.

● Data distribution, e.g. getting data from local transportation municipalities (Google Live Transit)

● The importance of data standards for an efficient value chain (e.g. Google towards local transit authorities) ● Standards for overcoming local information silos and for

fast replication of initiatives across cities.

Where is the market for infomobilityservices.

● Multi-sided market. Sides are:– Motorists/commuters

– Merchants (location-based advertising)

– Local transit companies

● Companies (e.g. Foursquare) needing to “repackage” digital maps contents.

● Completely free for consumers

● “Freemium”– Trade-off among the sides high prices reduce the customer base for advertisers

● Pay for the app (TomTom, BusChecker, etc. )

Revenue modelsCustomer segments

Infomobility services. Segmenting the market

Compelling value proposition? For Whom?

● Motorists? …Are they really interested when they do every day the same route to go to work (and they barely have two alternative ways)?

● Commuters? …Are they really interested in a coupon when they have to rush to work or to catch a train?

● A market segment: tourists/travellers, in big cities especially large cities are “always on the move” and they offer more scalable markets

● NOT A MASS MARKET. BUT ONLY CERTAIN MARKET SEGMENTS

Location-based Services complementary to infomobility

● Collaborative consumption (e.g. ride sharing services such as Zimride, Blablacar, Carpooling.com)

● Location-based social networks (e.g. Foursquare, Nextdoor to strenght local physical communities)

● “Quantified-self” tracking services for sports (e.g. Runtastic), places you have been, etc.

● …

● Still Opportunities for small businesses? Probably, yes. But competition is time-based and a large scale of investments is needed…

Big data markets – Some predictions

● Source of differentiation lies in customer interface and data– Source of differentiation will eventually shift from the algorithms

for data fusion and cleaning to the data themselves– Economic value will lie in the complementarities of data from

different sources

● Winner-takes-it all markets Only few players will remain!

● Re-intermediation of merchants and many other local businesses (e.g. travel agencies are slowly disappearing, the yellow page industry is reconfiguring) Big Infomediariessqueeze big profits!

Consequences of the re-intermediation process: the case of the Italian hospitality industry

Source: elaboration on AIDA data 

Market shares shifting from large to small players, 

BUT…

Consequences of the re-intermediation process: the case of the Italian hospitality industry

15%

20%

25%

30%

35%

40%

45%

50%

Grandi

Medie

Piccole

Micro

Hotel sizeServices costs/Revenues

Source: elaboration on AIDA data 

…BUT, Increasing unit service costs

Open data. Light and shade

● Better transparency for customers

● Better analytics for governments to reduce inefficiencies (Health public expense in the UK)

● Precondition for citizens’ empowerment.

● They may allow the citizen to dis-intermediate the government and media.

• Open data as a public good. Leave them it and then someone will figure out how to use them.

• Not yet many cases of commercial exploitation for open data.

– Few start-ups born on open data (e.g. only four in the UK) and with business models yet to be constructed!

LIGHT SHADE

Open data. Beyond the hype

● Data fusion and analytics as the value added activities.

● From a survey on the Italian www.dati.gov.it– 151 apps providing data that are in large part static– Apps as “a static Window” for municipalities for

informing on events, parking, touristic attractions, etc.

– No business models around the majority of the apps (open data as a terrain for hobbyists? )

Recap and Final considerations● Big data as a disruptive innovation (re-intermediation

processes, new entrants)

● Big investments are needed. Not always a business for small firms…

● Many examples of small businesses providing services “linked” to the ones of “platform leaders” á la Facebook.

● Can open data really be a “key ingredient” for start-ups? Strategic resources are rarely for free, “by definition”! Still Searching for a scalable business model.

● Big data management capabilities and Italian companies. They are not only an opportunity…