1. A collection of
corporate use cases
embedded into a
business framework
1
DATA-DRIVEN
COMPANIES
Steven Moore September 2018
2. BIG DATA AS SIMPLE AS THIS
VALUEINFORMATIONDATA
Form of
usage
Analytics
3. Firms should use a diverse set of data & permanently have
particular use cases in mind
Internally collected
Externally collected
Externally acquired
Internal value
External value
Strategic value
VALUEINFORMATIONDATA
Form of
usage
Analytics
BIG DATA AS SIMPLE AS THIS
4. DATA-DRIVEN COMPANIES
Externally
acquired data
How companies can derive value from data
Strategic
Assets
Externally
collected data
External
Value
Strategic
value
* An organization not necessarily has to operate with a central data unit. The data capabilities may as well lie in the business units itself.
External
Parties
Organization
Business
Units
Internally
collected data
Internal
value
Data Unit*
Market
User
Data
Information
Value
Analytics
5. DATA-DRIVEN COMPANIES
Improved decision making
Automation (New) Value Propositions
Tailored Offerings to Customer Needs
Data Asset
Analytical Asset
INTERNAL EXTERNAL
7. IMPROVED DECISION MAKING:
Granting managers or employees access to
relevant data can help to make better strategic
& operative decisions.
8. IMPROVED DECISION MAKING
Find out more
Airpal platform
Airpal is a user-friendly data analysis platform for regular
employees (web-based query execution and data
visualization tool).
The Airpal initiative has been particularly essential for Airbnb
as the company grew exponentially and employees not only
had to be informed quickly but also had to make crucial
decisions independently.
Airbnb
9. Walmart’s Data Café’s
Walmart, the largest retailer in the world, is in the process of
building the world’s biggest private cloud, big enough to
cope with 2.5 petabytes of data every hour. To make sense of
the data the company has created a “Data Café” - a
state-of-the-art analytics hub located within the Bentonville,
Arkansas headquarter.
The platform allows huge volumes of data to be rapidly
modelled, manipulated and visualised.
The system also provides automated alerts in case particular
metrics falls below a set threshold in any department.
More importantly, however, the Data Café acted as a central
station within the company where employees could find
solutions to their business problems.
IMPROVED DECISION MAKING
Walmart
10. IMPROVED DECISION MAKING
Personalized health care
The California based cognitive computing firm Apixio
has written out large amounts of unstructured health
data such as radiology, handwritten doctor reports
using Natural Language Processing (NLP) and Optical
Character Recognition (OCR) techniques.
This served as a larger knowledge foundation for
doctors. Having access to previous data, doctors could
for instance give their patients more personalized
medical health care.
Apixio &
Doctors
12. AUTOMATION
Data-driven oilfields
Royal Dutch Shell is one of the largest companies on the
globe by revenue. Shell leverages the power of data not
only to optimize its supply chain (manufacturing &
logistics) but tackle the difficulties of exploring and
drilling for new oil reserves - the industry’s major
expense. The search for new oil deposits requires a huge
amount of material, manpower and logistics. Drilling a
deep-water oil well often costs over €100 million, so no
one wants to be looking in the wrong place. Surveying
potential sites involves the usage of low frequency
waves that are distorted as they pass through oil or gas.
Find out more
Shell
13. AUTOMATION
Automated match reports
Narrative Science focus lies on Natural Language
Processing (NLP). “Quill”, one of Narrative Science’s
products, generates customized reports from all sorts
of structured data. Initially, the system was used to
create automated match reports for tennis matches but
then expanded to economic, financial or market reports.
Today, Quill even writes articles for forbes magazine
which hard to distinguish from articles written by
top-tier journalists.
Another product, “Quill Engage” helps companies to
interpret their website sessions, bounce rates and KPI’s
by transferring Google Analytics data into customized
reports.
Narrative
Science
14. AUTOMATION
Dynamic pricing algorithms
Like many successful companies, Uber also is a
data-driven company. Uber uses data to predict
demand, allocate resources accordingly and set fares.
Uber’s largest data use case is its dynamic pricing
system (“surge pricing”). The exponentially growing
company has developed algorithms that monitor traffic
conditions in real time meaning that prices can be
adjusted as demand for rides change. Another benefit
- the pricing system also regulates demand and supply
which is highly essential for Uber’s business model. If
prices increase more drivers are incentivized to go
beyond the wheel which will again decrease prices. The
surge pricing system of Uber is similar to the systems of
hotels or airlines in this sense.
Uber
15. AUTOMATION
Demand Prediction
Traditionally firms within the fashion industry have
predicted the success of a new product based on the
sales numbers of a similar product that has already been
on the market. Nowadays, however, advanced machine
learning systems that are fed diverse data do a much
better job at demand prediction, because these
systems can learn more complicated features that are
not obvious to humans. Demand prediction is
particularly important in the fashion industry as it has a
huge impact on customer satisfaction and supply
chain management.
Zalando
17. TAILORED OFFERINGS TO
CUSTOMER NEEDS
A better customer understanding allow more
tailored offerings and more personalized
customer communication
18. TAILORED OFFERINGS TO
CUSTOMER NEEDS
Recommender Systems
Back in the days firms offered customers ONE product and
customer decided whether it was worth their money. Today,
firms adjust their value proposition specifically to their
customers. Netflix has been building a business around being
able to predict exactly what its customers will enjoy watching.
Therefore, Big Data analytics is the fuel that fires the
“recommendation engines” designed to serve this purpose.
User receive movie recommendations in line with their
preferences and previous behavior. Netflix’s
recommendation system not only uses standard features
such as genre or actors or but also detailed features about the
content of a movie.
Netflix
19. TAILORED OFFERINGS TO
CUSTOMER NEEDS
Customized Advertising
LinkedIn tracks every move a user takes, every click
every page view. Based on this knowledge the company
offers tailored value offerings to its users. For instance,
the “People you may know” section gives users
personalized suggestions who to add to their network
based on whether they have clicked on a profile, worked
at the same company or share mutual connections.
Further, LinkedIn’s advertising platform - which
accounts of 20 - 25 % of the company’s revenue - is
completely personalized. Analysts and data scientists
continually look at what ads are being clicked by what
specific users to offer the most effective advertisement
to firms.
LinkedIn
20. TAILORED OFFERINGS TO
CUSTOMER NEEDS
Personalized marketing
During the 1980’s banks pushed (almost forced) their
products onto customer. Acxiom, a database marketing
company which is often referred to as “the biggest company
you have never heard of”, started off providing segmented
mailing lists to banks and credit card providers. After a while
Acxiom took over the entire direct marketing activities for
these firms and ran tailored marketing campaigns. Today,
Acxiom’s advertisement systems such as “personicx” which
produces detailed customer profiles based on social media,
public records or online surveys data, are highly effective and
successful. The company accounts to 12% of the entire
marketing revenue in the US.
Acxiom &
Financial
Institutions
21. TAILORED OFFERINGS TO
CUSTOMER NEEDS
Adjusting products to customer wants
Bernard Marr, a writer, consultant and business influencer ran
a project with a local butchers store in the the north-west
London. The store faced tough competition by a supermarket
and had little indications what their customers wanted. So
they installed sensors into the store’s window which were
able to detect mobile signals. In this way the local butchers
store found out how many people passed the shop, stopped
at the window or entered the shop - solid customer
acquisition KPI’s for such store. The data revealed a
surprising fact. A lot of people would pass the store at around
9 pm before going to a nearby bar. Pendleton & Son Butchers
reacted to this by offering pulled pork burger exactly at this
time (Google trend data showed that pulled pork was a
favoriable dish in this area). Today the late pulled pork burger
accounts to almost 50% of the store’s revenue.
Pendleton &
Son Butchers
23. (NEW) VALUE PROPOSITIONS
Data Products in farming
Agricultural manufacturer John Deere is faced with a global
problem. The world’s population is growing rapidly which
means that there is an increasing demand for food. With
genetically modified food still not appealing to the public,
increasing efficiency of production is still key to tackling this
problem. For this, John Deere has launched several data
services that let farmers benefit from crowdsourced, real-time
monitoring data. Myjohndeere.com is an online portal that
allows farmers to access data gathered from sensors
attached to their own machinery as they work on the fields.
It is also connected to external datasets including weather or
financial data. Accessing this data helps farmers to optimize
their farm practices and increase yield of their production.
John Deere also offers predictive maintenance as a service
to farmers as well as another data service named “Farmsight”.
Launched in 2011, Farmsight recommends what crops to
plant based on the current market situation or weather
conditions.
John Deere
24. (NEW) VALUE PROPOSITIONS
Voice Assistance and Health Care Apps
Despite being the most profitable tech company, Apple
found themselves not in the lead with Big-Data.
While Apple’s strength lied in excellent product design,
Google’s business model was built around collecting and
analysing user data. This gave Google a competitive
advantage with everyday apps (google maps, voice
recognition etc.) to which Apple needed to catch up.
Therefore, Apple has entered a partnership with IBM named
MobileFirst to develop health related mobile apps. The
partnership allows iPhone and Apple Watch users to upload
their data to IBM’s Watson Health cloud based analytics
platform. Further, Apple has also launched own data
products, such as Siri. Originally developed as a spin-off
project by the SRI International Artificial Intelligence Center,
Apple acquired the technology two months after being
launched as a mobile app to the Apple App Store.
Apple
25. (NEW) VALUE PROPOSITIONS
Nest Learning Thermostat
Nest’s mission is it to create a home that takes care of the
people inside and the world around it. The company has
several data products in its repertoire, such as smart security
devices or video doorbells. Nest is also well known for its
“Learning Thermostats” which monitor your daily activity to
optimize the efficiency and comfort of your home. The
system’s sensors track your location, humidity &
temperature level or whether you are home or not using
motion sensors. Over time, the smart thermostat even learns
customer preferences. According to Nest, their products lead
to a 50% decrease in energy usage - according to objective
studies the savings are around 10-15%. Regardless of the
exact figures, energy companies have also showed high
interest in the data and pay Nest around $50 per customer
in the case they are willing to share the data with the
respective energy company.
Nest
26. (NEW) VALUE PROPOSITIONS
After-sales services
Rolls-Royce serve a great example of an industrial giant of the
“old age” - when innovation was about steel and sweat -
transitioning to the new age of data-enabled improvements
and efficiency. The company manufacture enormous engines
that are used by more than 500 airlines. Within this business,
failures and mistakes can cost billions and even endanger
hundreds of lives. In this sense, Rolls Royce installed several
sensors that monitor their engines after being sold. Rolls
Royce leverages this data by offering multiple after-sales
services to their business partners. Predictive maintenance
is one of them. By continually analyzing the vibration,
pressure and temperature of their machines, Rolls Royce can
notify their customer one week in advance a machine breaks
down. More interestingly, maybe, Rolls Royce has even
adapted its entire business model. The machine
manufacturer spare their customer high purchase costs and
instead charge airlines on mile usage. A clear win for both
sides.
Rolls Royce
27. (NEW) VALUE PROPOSITIONS
MagicBands
Family entertainment company Walt Disney bring 126
million visitors annually to their theme parks and resorts.
With MagicBand, a colorful wristband, Disney are able to
track every guests’ move around their resort in Orlando,
Florida. The band acts as a room key, entry pass and can
also be linked to visitors’ credit card to easily purchase food
and merchandize. Further, it stores visitors’ personal details so
that kids can be greeted by name. Disney on the other hand,
get detailed feedback on their customer profiles and
demands. The wristband even helps Walt Disney to analyze
the traffic flow in their resorts and manage queues or
restaurant demand.
Walt Disney
28. (NEW) VALUE PROPOSITIONS
Connected PoloTech Shirt
Wearables are expected to become increasingly popular as
the Internet of Things (IoT) takes off. At the 2014 US Open
tennis tournament Ralph Lauren unveiled their Connected
PoloTech Shirt. A credit card sized sensor in the shirt tracks
an athlete’s movements, heart rate, breathing rate, steps
taken and calories burned all aiming to improve fitness and
wellness. The fashion retailer has also created an app within
the data is stored and that offers users customized cardio,
strength and agility workouts based on their fitness level.
Ralph Lauren is also firmly planning on releasing data
products outside the sports industry. Sensors within their
shirts could also offer new value propositions for business
associates by for example automatically reporting and
summarising business meetings.
Ralph Lauren
31. DATA ASSETS
Leveraging activity data
Fitbit’s entire business model is built on data. By tracking
users’ activity and eating habits Fitbit helps individuals to
become healthier. Users have real-time information on their
progress nicely illustrated with dashboards. The data
gathered not only helps individuals but also has implications
for healthcare professionals and insurance companies.
Users can upload their data to Microsoft HealthVault service
and through this give doctors access to their activity data.
Having access to this sort of data can give doctors a more
thorough picture on a patient’s overall health conditions.
Further, users can share their activity data with insurance
companies and in return receive financial rewards.
Fitbit
32. DATA ASSETS
Creditworthiness and insurability
assessement
Experian is a consumer credit reporting agency that collects
and aggregates information on over one billion people and
businesses. In total, Experian has more than 30 petabytes of
data on individuals gathered from financial institutions,
public records (e.g. birth and death records), electoral
registers or court registers. Experian knows exactly how
much money individuals have borrowed in the past and
whether or not they have paid back in time. Experian then
leverages this data asset by offering financial institutions paid
services on the creditworthiness and insurability of lenders.
Banks and insurance companies try to avoid playing a game
of chance and want to be confident that their customer
afford repayment with interest. Other services from Experian
include fraud alert, cyber security as well as identity theft
protection.
Experian
33. DATA ASSETS
Increased firm evaluation
Weather affects almost everything. Being well aware of this
fact, IBM acquired The Weather Company for an
astonishing price of over $2 billion. If you are scratching
your head and asking yourself why a software company
would pay this amount. One word: Data. Instantly IBM had
moved its weather data to IBM’s cloud computing platform
and started selling companies access to the information as
well as related forecasting services. IBM said the acquisition
will lift the company’s new Watson Internet of things unit and
related cloud platform as businesses can connect their
devices to weather data using Watson. For example, a
trucking business could access IBM’s weather data, receive
notifications that a storm is moving in a certain direction, and
then alert all of its drivers to steer clear of its projected path.
The same idea could be applied to airliners or salespeople on
the road.
Weather.com
34. DATA ASSETS
Strategic venture building
Coup, a new Bosch subsidiary, is proving a hit in Berlin thanks
to its app-controlled sharing platform for e-scooters, a
genuine alternative for current vehicles. However, when
inventing Coup, Bosch was not necessarily looking for a new
cash cow. Instead the new start-ups provides its parent
company with access to relevant data for their core
business. How come? Coup is integrated into the mobility
department of Bosch, separated into connected mobility,
automated mobility, powertrain systems and electrified
mobility. Importantly, however, Bosch is still mainly a
manufacturing company without a direct touchpoint to
end-customer. That’s why Bosch’s corporate strategy is
increasingly focusing on connected services in the B2C
context. Coup gave Bosch a direct touchpoint to end-user
which helps the parent to understand customer’s mobility
behavior more in detail.
Coup &
Bosch
36. ANALYTICAL ASSETS
Data-as-a-service
Though critics may think that innovation is not the core
strength of Microsoft, dealing with complex datasets - a very
demanding business area - is.
The software giant is increasingly moving towards
data-as-a-service (DAAS) or service-as-a-service (SAAS)
solutions. Let’s see a few examples. Microsoft’s DAAS
packages offer Hadoop-based analytics platforms and their
own machine learning algorithms. Microsoft Azure is
another service framework for IoT projects. Their Power BI
toolset gives millions of users access to advanced analytics
functionalities into Microsoft Excel.
Microsoft
37. ANALYTICAL ASSETS
Machines that learn & speak
From the early beginnings Computer were incredibly quick at
calculations, but language has always been a big barrier until
recently. This has changed. And after winning the US TV
gameshow Jeopardy! in 2011, IBM Watson manifested this fact
into the heads’ of everybody. Watson is connected to the
internet and has access to the collective dataset of humanity
(encyclopaedias, scientific studies, news articles and
statistics). By using advanced machine learning algorithms -
Watson’s backbone is Natural Language Processing (NLP)-
the system learned to work out what information it needs
and can efficiently communicate this knowledge human-like.
Since its victory against Brad Rotter & Ken Jennings, the
system has put to use across many major industries,
including healthcare, marketing, finance, retail and waste
management.
IBM
38. ANALYTICAL ASSETS
Anomaly detection
Named after the magical stones of The Lord of The Rings,
Palantir have made itself a name by using Big Data to solve
security problems, ranging from fraud to terrorism. Based
on a technology developed by PayPal the firm offer services
that spot anomalies in data which indicate suspicious or
fraudulent activities. Initially focused on fraudulent credit
card transactions, the company also expanded to terrorism
and international drug trade. Palantir helps the CIA for
instance to detect bombs in Afghanistan. A big part of
Palantir’s success lies in handling massive datasets and their
advanced anomaly detection algorithms.
Palantir