[OPLIN 4cast] OPLIN 4cast #559: Data = money

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OPLIN 4cast #559: Data = money
September 13th, 2017

[image: Coins] This past week, news broke of yet another huge data breach,
this time involving the financial data of 143 million people that was
stolen from Equifax. Obviously, the reason hackers break into systems and
steal data is because they want to sell it for nefarious reasons. But many
legitimate businesses also sell data, or monetize it in other ways. In
fact, monetizing data has become a significant revenue stream for certain
types of businesses, so much so that pundits predict it will become the
primary revenue stream in some cases.

   -
   - Data monetization: A new way of thinking
   <https://upside.tdwi.org/articles/2017/09/07/biz-all-data-monetization-new-way-of-thinking.aspx>
   (Upside | Savaram Ravindra)  “There are two ways you can make money from
   your data. You can create a supplemental revenue stream by providing access
   to your data (direct monetization) or use insights to improve your business
   services and operations (indirect monetization). Data monetization is not
   simply about turning over your existing data to another party. There are
   many other ways to utilize data that can impact costs or revenue.”
   - Monetizing data: A new source of value in payments
   <http://www.mckinsey.com/industries/financial-services/our-insights/monetizing-data-a-new-source-of-value-in-payments>
   (McKinsey Insights | Alessio Botta, Nunzio Digiacomo, and Kevin Mole)  “Any
   large business or bank has two types of customer data: line-of-business
   (LOB) data owned by a particular part of the business, and common data,
   which falls into two groups: enterprise-level data and supplemental
data. *Enterprise-level
   data* consists of the same elements as LOB data—customer preferences,
   needs assessments, and so on—but spans the organization, and in most
   evolved enterprises is drawn from a single source, such as a data
lake. *Supplemental
   data* ranges from raw data derived from external sources such as social
   media, weather data, and digital IDs to synthesized, value-added analytics
   that are captured through predictive modelling, sentiment analysis, and so
   on.”
   - Whose data is it anyway?
   <https://www.cuinsight.com/whose-data-anyway.html> (CUInsight | Austin
   Wentzlaff)  “The credit union should be focused on monetizing their own
   data and not giving that data away to someone else to monetize it for
   themselves and their own benefit. The fact of the matter is everyone wants
   your data. What company wouldn’t? It’s some of the most valuable data out
   there – where your members shop, how much they spend, what types of
   vehicles they have, or what their credit scores are, etc. Instead of giving
   away the value of its data, a credit union must figure out a means to
   monetize that data for itself.”
   - How APIs will make your next fridge — or even your next car — free
   <https://readwrite.com/2017/09/03/apis-next-fridge-even-next-car-free-p1l>
   (ReadWrite | Mehdi Medjaoui)  “Soon, car companies will make more money by
   making sense of where you are and where you’re going. Just imagine, if they
   can monetize at 20 cents/mile, on 100,000 miles they make $20,000: A free
   car. For 30 cents/mile, they almost triple their profits and can give the
   car away. They can collect and sell drivers’ data, traffic data,
   micro-location weather data, state of the road data and so on. They can
   sell ads on the radio or on the GPS with CPCD (Cost Per Change Direction),
   coupons to restaurants close to your destination, audiobooks to listen in
   the car — a lot of things to monetize your time and location in your car.”

*Articles from Ohio Web Library <http://ohioweblibrary.org>:*

   - Chief Data Officers: The new oil barons.
   <http://proxy.oplin.org:2054/login.aspx?direct=true&db=cmh&AN=116164760>
   (*Information Today*, June 2016, p.18 | John Thielens)
   - Monetize your data.
   <http://proxy.oplin.org:2054/login.aspx?direct=true&db=buh&AN=122350853>
   (*Leadership Excellence Essentials*, April 2017, p.60 | Andrew Wells and
   Kathy Chiang)
   - The smart thing to do: Practical applications of monetizing big data
   in finance.
   <http://proxy.oplin.org:2054/login.aspx?direct=true&db=aph&AN=124401095>
   (*KM World*, July/Aug. 2017, p.10-12 | Jelani Harper)

------------------------------
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