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Big data &

cross-platform analytics MOOC lectures Pr. Clement Levallois

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6 families of business models centered on data

• Not a closed list, not a recipe! • Helpful toolkit for brainstorming on data for business

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Data: the many roads to value creation

1. Creating data, selling data

2. Gathering data, selling ads

3. Gathering data, selling predictive analytics

4. Adding data goodness to products

5. Adding data goodness to existing services

6. Creating new services enabled by data mining

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1. Gathering data, selling data • When selling data itself is the value proposition

– Thomson Reuters selling data from finance, scientific research, medicine and news

– Nielsen selling market data

– Twitter selling tweets through affiliated partners (GNIP and DataSift)

– Meteo France selling meterological data

– Orange (French Telecom company) can sell info to cities about car traffic and flows of

tourists in public places (museums…) based on the (anomymized) geolocalisation of tourists mobile phones.

– ImDB or Allocine which sells to analysts data about movie previews (which one are watch most often?)

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2. Gathering data, selling ads

Facebook, Yahoo, Microsoft, Google, LinkedIn, Twitter, etc: using data from our profiles, queries and social networks to offer ad targeting services.

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3. Gathering data, sell predictive analytics

• Tilkee: predicts the success of a commercial action based on history of email attachment usage patterns

• Visa: predicts credit score based on individual history of bank account balance / purchases

• PredPol: predicts occurrence of crime based on past history of crimes.

• InfraTest: predicts the success of a new product concept based on a database of 100,000+ tests of concepts.

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4. Adding data goodness to products

– Babolat connected tennis rackets: improve your game

– Withings body scale, watch etc: track your well being

– Nest thermostat: regulate your energy consumption

– Drinking cups

– Google car: let it drive for you, have a safer trip

Vessyl

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5. Adding data goodness to existing services (incremental innovation)

– ABN AMRO (Dutch bank) and its online banking service helping customers benchmark their expenses against a similar, average household

– Amazon shopping experience with ratings, comments and product recommendations.

– KLM Meet & Sit: connect to Facebook or LinkedIn to choose a sit next to somebody you’d like to meet

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6. Creating new services enabled by data mining (disruptive innovations)

Disruptive: because they put non-data intensive services at risk of becoming obsolete!

– Crowd-sourced apps like Waze or Coyote replacing static navigation systems?

– Uber replacing cabs? – MOOCs replacing in-class lectures in universities? – Building Information Modeling (BIM) replacing non data-intensive planning systems for building?

– Algorithms + data replacing manual trading on the stock market, automatizing the market for ad

placement, optimizing energy consumption at the household level, replacing brick-and-mortar travel agencies by online platforms, …

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This slide presentation is part of a course offered by EMLYON Business School (www.em-lyon.com) Contact Clement Levallois (levallois [at] em-lyon.com) for more information.