Paolo Neirotti, Politecnico di TorinoBusiness models and new value chainsfor big data
Big data as a source of GDP and wealth!But for which nations?
Big data and business models: crucialissues● Go beyond hypes and fads● Which opportunities for SMEs and large enterprises?...
Four reasons for a focus on theInfomobility industry1. Mature industry (e.g. maps) before the discontinuity produced byInt...
Four reasons for a focus on theInfomobility market● 4. the number of broadband mobiledevices is increasing  Just at thebe...
Discontinuities in the infomobility sector [1]● Factory-installed GPS equipment: around 1,500 €● After-market GPS navigati...
Discontinuities in the infomobility sector [2]TOMTOMGarmin2010Share PriceRepositioning towards  B2B: licensing maps and li...
Digital maps: not a business for many● Time compression economies exist!Big Barriers to entry exist! (time is needed to ac...
Value chain in big data for infomobilityData generationData aggregationData elaborationData visualizationData RetailCrowds...
High value added activities in theinfomobility service industry● Data generation for real-time traffic (e.g. Googlethrough...
Where is the market for infomobilityservices.● Multi-sided market. Sidesare:– Motorists/commuters– Merchants (location-bas...
Infomobility services. Segmenting themarketCompelling value proposition? For Whom?● Motorists? …Are they really interested...
Location-based Servicescomplementary to infomobility● Collaborative consumption (e.g. ride sharing servicessuch as Zimride...
Big data markets – Some predictions● Source of differentiation lies in customer interface and data– Source of differentiat...
Consequences of the re-intermediation process: thecase of the Italian hospitality industrySource: elaboration on AIDA data...
Consequences of the re-intermediation process:the case of the Italian hospitality industry15%20%25%30%35%40%45%50%GrandiMe...
Open data. Light and shade● Better transparency forcustomers● Better analytics forgovernments to reduceinefficiencies (Hea...
Open data. Beyond the hype● Data fusion and analytics as the value addedactivities.● From a survey on the Italian www.dati...
Recap and Final considerations● Big data as a disruptive innovation (re-intermediationprocesses, new entrants)● Big invest...
Upcoming SlideShare
Loading in...5
×

Paolo Neirotti - Modelli di business e nuove filiere per i big data nelle smart cities - Digital for Business

395
-1

Published on

L’enfasi posta di recente sul tema dei big data nasconde una serie di domande - per il momento ancora prive di una risposta esaustiva - sulle effettive trasformazioni che essi potranno generare in imprese e filiere. Nello specifico, quale possa essere la capacità delle imprese italiane di sfruttare le potenzialità del cambiamento tecnologico legato ai big data dipende in parte dalle risposte a queste domande di fondo. Come si stanno formando nuove filiere nei settori dei servizi basati sulla capacità di elaborare big data? In tali filiere quale specializzazione si stanno ricavando incumbents e nuove imprese? Quali sono i modelli di business che finora hanno dimostrato una buona sostenibilità economica? Quali servizi nella filiera dei big data sono invece ancora alla ricerca di un modello di business economicamente sostenibile? Quali sono le variabili di competizione nei servizi che si fondano sulla capacità di elaborare big data? L’intervento intende trattare tali questioni prendendo a riferimento il settore dell’infomobilità nelle smart cities.

Published in: Business, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
395
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
4
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Paolo Neirotti - Modelli di business e nuove filiere per i big data nelle smart cities - Digital for Business

  1. 1. Paolo Neirotti, Politecnico di TorinoBusiness models and new value chainsfor big data
  2. 2. Big data as a source of GDP and wealth!But for which nations?
  3. 3. Big data and business models: crucialissues● 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 arenot clear yet.– What services and what compelling value proposition?– For what market segments? A FOCUS ON THE INFOMOBILITY SERVICEINDUSTRY
  4. 4. Four reasons for a focus on theInfomobility industry1. Mature industry (e.g. maps) before the discontinuity produced byInternet and mobile business– New entrants (e.g. Google, Nokia, and many startups)– Mergers and acquisitions (e.g. Nokia and Navtech, TomTom andAtlas,– 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, andcrowdsourcing are a reality more than in any other industry.3. Cities are a generator of big data. Can they become “dataretailers” or wholesalers?
  5. 5. Four reasons for a focus on theInfomobility market● 4. the number of broadband mobiledevices is increasing  Just at thebeginning of the S-curve
  6. 6. 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 aboutpoint of interests, alerts for speed-limits and camera.  businessfor start-ups (e.g. Waze)
  7. 7. Discontinuities in the infomobility sector [2]TOMTOMGarmin2010Share PriceRepositioning 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 
  8. 8. Digital maps: not a business for many● Time compression economies exist!Big Barriers to entry exist! (time is needed to accumulate data)…
  9. 9. Value chain in big data for infomobilityData generationData aggregationData elaborationData visualizationData RetailCrowdsourcing (e.g. Waze, Open Street Map), open governmental data, telcos, municipalities, insurance firms, navigation companies , Google.Inrix, BusCheckerMapboxGoogle, Web portals, Radio and TV networks, navigation firms providing real‐time traffic information Data transportationMicrosoft MapPoint, Quantum GIS, Wikitude (AR)Infrastructure for data elaboration(e.g. data storage)
  10. 10. High value added activities in theinfomobility service industry● Data generation for real-time traffic (e.g. Googlethrough the service “My location” on mobile phoneswith Android)● Data elaboration and cleaning.● Data distribution, e.g. getting data from localtransportation municipalities (Google Live Transit)● The importance of data standards for an efficient valuechain (e.g. Google towards local transit authorities)● Standards for overcoming local information silos and forfast replication of initiatives across cities.
  11. 11. Where is the market for infomobilityservices.● Multi-sided market. Sidesare:– Motorists/commuters– Merchants (location-basedadvertising)– Local transit companies● Companies (e.g.Foursquare) needing to“repackage” digital mapscontents.● Completely free forconsumers● “Freemium”– Trade-off among the sides high prices reduce thecustomer base foradvertisers● Pay for the app (TomTom,BusChecker, etc. )Revenue modelsCustomer segments
  12. 12. Infomobility services. Segmenting themarketCompelling value proposition? For Whom?● Motorists? …Are they really interested when they do everyday the same route to go to work (and they barely havetwo alternative ways)?● Commuters? …Are they really interested in a couponwhen they have to rush to work or to catch a train?● A market segment: tourists/travellers, in big citiesespecially  large cities are “always on the move” andthey offer more scalable markets●  NOT A MASS MARKET. BUT ONLY CERTAINMARKET SEGMENTS
  13. 13. Location-based Servicescomplementary to infomobility● Collaborative consumption (e.g. ride sharing servicessuch 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 ofinvestments is needed…
  14. 14. Big data markets – Some predictions● Source of differentiation lies in customer interface and data– Source of differentiation will eventually shift from the algorithmsfor data fusion and cleaning to the data themselves– Economic value will lie in the complementarities of data fromdifferent sources● Winner-takes-it all markets  Only few players will remain!● Re-intermediation of merchants and many other localbusinesses (e.g. travel agencies are slowly disappearing, theyellow page industry is reconfiguring)  Big Infomediariessqueeze big profits!
  15. 15. Consequences of the re-intermediation process: thecase of the Italian hospitality industrySource: elaboration on AIDA data Market shares shifting from large to small players, BUT…
  16. 16. Consequences of the re-intermediation process:the case of the Italian hospitality industry15%20%25%30%35%40%45%50%GrandiMediePiccoleMicroHotel sizeServices costs/RevenuesSource: elaboration on AIDA data …BUT, Increasing unit service costs
  17. 17. Open data. Light and shade● Better transparency forcustomers● Better analytics forgovernments to reduceinefficiencies (Health publicexpense in the UK)● Precondition for citizens’empowerment.● They may allow the citizen todis-intermediate thegovernment and media.• Open data as a public good. Leave them it and thensomeone will figure out howto use them.• Not yet many cases ofcommercial exploitationfor open data.– Few start-ups born onopen data (e.g. only fourin the UK) and withbusiness models yet tobe constructed!LIGHT SHADE
  18. 18. Open data. Beyond the hype● Data fusion and analytics as the value addedactivities.● 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 forinforming on events, parking, touristic attractions,etc.– No business models around the majority of theapps (open data as a terrain for hobbyists? )
  19. 19. Recap and Final considerations● Big data as a disruptive innovation (re-intermediationprocesses, new entrants)● Big investments are needed. Not always a business for smallfirms…● 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”! StillSearching for a scalable business model.● Big data management capabilities and Italian companies.They are not only an opportunity…
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×