2. Dr. Jorge Ramírez Medina
Course Information
Grade
Class discussion 10%
Cases analysis 40%
Project 20%
Class Quiz 30%
Skype: karoshi.darkside
Email: Jorge.Ramirez@itesm.mx
3. Dr. Jorge Ramírez Medina
Rationale behind the course
Edinburgh at in the mid- to late eighteenth
century
A world-renowned cultural center
4. Dr. Jorge Ramírez Medina
Rationale behind the course
Colin Macfarquhar printer Andrew Bell an
engraver
1768 a “Dictionary of Arts and Sciences”
5. Dr. Jorge Ramírez Medina
Rationale behind the course
William Smellie editor
1771 three volume set.
By 1815, 20 volumes
6. Dr. Jorge Ramírez Medina
Rationale behind the course
Throughout the nineteenth century and into
the twentieth moved to US
Reputation as the premier source of
knowledge
7. Dr. Jorge Ramírez Medina
Rationale behind the course
1943 William Benton,
publisher and board chairman
8. Dr. Jorge Ramírez Medina
Rationale behind the course
late 1960’s and early 1970’s
Home Call Sales Presentation
9. Dr. Jorge Ramírez Medina
Rationale behind the course
By 1990 sales revenues hit $650 million USD
successful business model for over 200 years
10. Dr. Jorge Ramírez Medina
Rationale behind the course
650
650
586
540
453
400
325
300
350
400
450
500
550
600
650
700
1990 1991 1992 1993 1994 1995 1996
Annual revenues
($ in millions)
Year
Hard Copy encyclopaedia
sales
120,000
117,000
55,000
12. Dr. Jorge Ramírez Medina
Thoughts about discussion
Technologies that create an entirely new offering can lead to the formation of new industries.
Instead of competing to capture a share of the value in an existing industry, a new technology can
allow a firm to create and capture value in an entirely new industry.
13. Dr. Jorge Ramírez Medina
Value
The fundamental principles of competitive strategy are the same: The value captured depends on the
value you create, your competitive advantage, and your bargaining power.
14. Dr. Jorge Ramírez Medina
Digital disruption
Commercial Internet Economies of mass Hyperscaling.
Philip Evans & Patrick Forth
15. Dr. Jorge Ramírez Medina
Digital disruption
Commercial Internet the dot-com era, falling transaction costs altered the
traditional trade-off between richness and reach: rich
information could suddenly be communicated broadly and
cheaply, forever changing how products are made and
sold.
16. Dr. Jorge Ramírez Medina
Digital disruption
Economies of mass
Small became beautiful. It was the era of the “long tail”
and of collaborative production on a massive scale.
Facebook transformed marketing by turning a billion
“friends” into advertisers, merchandisers, and customers.
17. Dr. Jorge Ramírez Medina
Digital disruption
Hyperscaling Big—really big—is becoming beautiful, hyperscaling
demands a bold, new architecture for businesses .
Amazon Web Services (AWS)—cloud computing
19. Dr. Jorge Ramírez Medina
Data-Information-Knowledge
• Data
Is a set of values of qualitative or quantitative variables
• Information
Data that is accurate and timely, specific and organized for a purpose,
presented within a context that gives it meaning and relevance, and can lead
to an increase in understanding and decrease in uncertainty.
• Knowledge
is a familiarity or understanding of something, that geminates from
combination of information and individual experience.
20. Dr. Jorge Ramírez Medina
Types of information processing
Transactional Processing
Focus on individual data item processing: data insertion,
modification, deletion, and transmission
Analytical Processing
Focus on reporting, analysis, transformation, and
decision support
21. Dr. Jorge Ramírez Medina
Convert Transactional data
into Analytical data
Data Processing
Operational
Analytical
1980 Codd
OLTP OnLineTransactionProcessing
OLAP
22. Dr. Jorge Ramírez Medina
OLAP
(Online Analytical Processing)
OLAP is a function/operation that is optimized to answer queries that are multi-dimensional in
nature.
Multi-dimensional queries
• A dimension is a particular way (or an attribute) of describing and categorizing data
• Such queries are usually arithmetic aggregation operations (sum, average, etc.) on records grouped
by multiple dimensions (attributes) at different aggregation levels.
23. Dr. Jorge Ramírez Medina
OLAP Cubes
Cubes consist of:
•Dimensions
• Criteria for analysis of data
• Macro-problem objects
• Independent Variables
• Axes in the hypercube
• Measures
• Values or indicators to analyze
• Data associated with relationships between objects of the
problem
• Dependent Variables
• Variables in the intersection of the dimensions
24. Dr. Jorge Ramírez Medina
OLAP cubes
Analyze
Visualize
Discover
Search, access, and transform
public and internal data sources
Easy data modeling and lightning
fast in-memory analytics
Bold new interactive data
visualizations
25. Dr. Jorge Ramírez Medina
Datawarehouse
Integrates the information generated in all areas of business activity (sales, production, finance,
marketing, etc.) and allows access to and use of the information.
27. Dr. Jorge Ramírez Medina
Data + Intelligence + Technology + Business
28. Dr. Jorge Ramírez Medina
Business Intelligence, definition
Business Intelligence is a set of methods, processes, architectures, applications, and technologies that
gather and transform raw data into meaningful and useful information used to enable more effective
strategic, tactical, and operational insights and decision-making (to drive business performance).
Adapted from Forrester Report“Topic Overview: Business Intelligence”, 2008
30. Dr. Jorge Ramírez Medina
The 5 Stages of
Business Intelligence
1. The Data:
defining which data will be loaded into the system and analyzed.
Where all information is stored
Technology dependent
2. The ETL (Extract, Transform, and Load) Engine:
moving the source data to the Data Warehouse. This can be a complex step involving modifications and calculations on the
data itself. If this step doesn’t work properly, the BI solution simply cannot be effective.
3. Data Warehousing:
Connects electronic data from different operational systems so that the data can be queried and analyzed over time for
business decision making.
A data warehouse is an analytically oriented, integrated, time-variant, and nonvolatile collection of data that supports
decision making processes
Large databases that aggregate data collected from multiple sources
31. Dr. Jorge Ramírez Medina
The 5 Stages of
Business Intelligence
4. Analytic Engine:
analyzes multidimensional data sets found in a data warehouse to identify trends, outliers, and patterns. (ex. Data
Mining)
5. Presentation Layer:
the dashboards, reports and alerts that present findings from the analysis. Typically Technology Agnostic -The
presentation layer is for the user.
32. Dr. Jorge Ramírez Medina
The 5 Stages of
Business Intelligence
Data ETL
Data Warehousing
Analytic Engine
Presentation
35. Dr. Jorge Ramírez Medina
Digital disruption
• For over 5,000 years analytics were done manually
• 1985, the PC and Excel changes analytics forever
• 1995, Age of BI. The ability to manipulate data emerge
38. Dr. Jorge Ramírez Medina
Evolution of BI semantics
EndUser
3rd Wave
EndUser
Everyone
1st Wave
Technical
2nd Wave
SelfService
EndUserIT Analyst
39. Dr. Jorge Ramírez Medina
Levels of BI
• Strategic: focused on high level organizational strategies and directions
• Tactic: focused on goals of a organization unit
• Operational: focused on streamlining day-to-day operations.
46. Dr. Jorge Ramírez Medina
Hype Cycle for Business Intelligence and Analytics,
2015
47. Dr. Jorge Ramírez Medina
Gartner Magic
Leaders execute well against their current vision and are well positioned for
tomorrow.
Visionaries understand where the market is going or have a vision for
changing market rules, but do not yet execute well.
Niche Players focus successfully on a small segment, or are unfocused and do
not out-innovate or outperform others.
Challengers execute well today or may dominate a large segment, but do not
demonstrate an understanding of market direction.
48. Dr. Jorge Ramírez Medina
Magic Quadrant for Business Intelligence and Analytics
Platforms
50. Dr. Jorge Ramírez Medina
Final thoughts
• Business Intelligence (BI) is about getting the right information, to the right
decision makers, at the right time.
• BI is an enterprise-wide platform that supports reporting, analysis and decision
making.
• BI leads to:
• fact-based decision making
• “single version of the truth”
• BI use information from yesterday and today , in order to make better decisions
about tomorrow
52. Dr. Jorge Ramírez Medina
Summary
• Technologies that create an entirely new offering can lead to the formation of new industries.
• Instead of competing to capture a share of the value in an existing industry, a new technology can
allow a firm to create and capture value in an entirely new industry.
• According to Philip Evans & Patrick Forth, there are three competitive tech waves namely:
Commercial Internet, Economies of mass and Hyperscaling
53. Dr. Jorge Ramírez Medina
Summary
• Knowledge is the necessary condition for decisión making. Data-Information-Knowledge
• 2 Types of information processing; Transactional OLTP and Analytical OLAP
• OLAP is a function/operation that is optimized to answer queries that are multi-dimensional in
nature
• A Data Warehouse integrates the information generated in all areas of business activity (sales,
production, finance, marketing, etc.) and allows access to and use of the information.
54. Dr. Jorge Ramírez Medina
Summary
• Business Intelligence is a set of methods, processes, architectures, applications, and technologies that
gather and transform raw data into meaningful and useful information used to enable more effective
strategic, tactical, and operational insights and decision-making (to drive business performance).
• The 5 Stages of Business Intelligence are; Data, ETL, Data Warehousing:, Analytic Engine,
Presentation Layer (related to BI LifeCycle)
55. Dr. Jorge Ramírez Medina
Summary
• 3 levels of BI; Strategic, Tactic and Operational
• Power BI is a free BI tool
• Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies
and applications, and how they are potentially relevant to solving real business problems and
exploiting new opportunities.
• Gartner Magic Quadrant putsTechnology Players Within a Specific Market
Scotland enjoyed its own “information age,”
It was an era that embraced industrialization, spawned revolutionary ideas (Adam Smith’s “invisible hand” theory of economics is one example), and transformed
http://www.hbs.edu/faculty/Publication%20Files/20007_EncyBrit_A%5B1%5D_a1eed6be-ff5a-4de9-a353-0feabaabdc0e.pdf
Colin Macfarquhar was a printer and Andrew Bell an engraver when they formed a partnership in 1768 to publish what they called a “Dictionary of Arts and Sciences.”
two enterprising men decided to capture and market that knowledge
Oposición a la iniciativa francesa de Diderot
William Smellie, hired to edit the vast collection, emphasized usefulness in his preface to the three volume set.
William Smellie, hired to edit the vast collection, emphasized usefulness in his preface to the three volume set.
The new reference guide, which took three years to complete, was offered to consumers in weekly installments
Even George Washington even bought a set.
The company recruited notable scientists and scholars, including Thomas Malthus, Sigmund Freud, and Marie Curie, to contribute.
It expounded upon such cutting-edge topics as taboos, anarchism, ether, and Darwin’s theory of evolution.
fue co-fundador de Benton & Bowles con Chester Bowles en Nueva York. Se trasladó a Norwalk, Connecticut, en 1932, y sirvió como vice presidente a tiempo parcial de la Universidad de Chicago desde 1937 a 1945.
Target;
Medium income parents
children an advantage in school and in life.
By 1990, consumers were snapping up Encyclopædia Britannica print sets at $1,500
to $2,000. The company’s sales revenues hit a new high—$650 million. Not only
that, the 32-volume set remained the standard to which other encyclopedias around
the world aspired.
Encarta, sold for less than
$100.
How vulnerable was this model in the early 1990’s?
1989 Brittanica releases CD-ROM versión of comptons enciclopedia
1996 Britanica solds to invertors for 135 M
2012 print versión closes
https://watson.analytics.ibmcloud.com/
one of the most striking and important aspects of new technology is that it can create an entirely new offering.
The genius of Facebook, for example, is that it allows advertisers to do something they couldn’t do before: insert their messages into people’s social communications.
The advent of the smartphone, for example, led to the creation of a mobile apps industry.
Whether a company is competing using a new technology or an existing one,
The difference with a new technology is that all of these are continually changing as the market grows and the technology develops. If the new technology produces a competitive advantage, competitors will rush to exploit it.
A large market will open up. Having created value, the challenge for the technology innovator is to capture a share of that value in the face of the many other market participants—suppliers, powerful customers, competitors, potential entrants, suppliers of substitute products, and complementors—who would like to secure that value for themselves.
A successful strategy for a technology innovator will include many of the following elements:
● Seek to dominate a market segment.
● Sustain competitive advantage by improving the value proposition.
● Be prepared to adjust your offering and cannibalize your business.
● Preempt competitors.
● Establish and defend intellectual property.
● Establish a position of power in an ecosystem.
● Exploit switching costs and increasing returns to scale.
In the first wave of the commercial Internet, the dot-com era, falling transaction costs altered the traditional trade-off between richness and reach: rich information could suddenly be communicated broadly and cheaply, forever changing how products are made and sold. Incumbent value chains could be “deconstructed” by competitors focused on narrow slivers of added value. Caso de la encyclopedia Britannica y encarta
Small became beautiful. It was the era of the “long tail” and of collaborative production on a massive scale. Caso Linux y Wikipedia.
IBM embraced Open Source to challenge Microsoft’s position in server software;
Apple and Google curated communities of app developers so that they could compete in mobile;
SAP recruited thousands of app developers from among its users;
Facebook transformed marketing by turning a billion “friends” into advertisers, merchandisers, and customers.
Big—really big—is becoming beautiful, hyperscaling demands a bold, new architecture for businesses
The exemplar of this is Amazon, whose successive innovations have been at the leading edge of each phase.
Jeff Bezos’s initial idea was to exploit the Web to deconstruct traditional bookselling. offered a catalogue ten times larger than that of the largest Main Street superstore, at prices 10 to 15 percent cheaper.
Then Amazon went on to exploit the emerging economics of community. collaborative filtering algorithms, goosing sales with messages that “people like you who bought X often buy Y.” launched Amazon Marketplace more than 2 million. All these strategies benefited from the network effect
At third wave Amazon built a global network of 80 fulfillment centers and relentlessly broadened its product line to include almost any product that can be delivered by truck. It offered fulfillment services as an option for small merchants, which could thereby distribute almost as efficiently as Walmart. In 2006 opened Amazon Web Services (AWS)—cloud computing. a complex stack of computing services. (Amazon even sells the service to competitors such as Netflix.) According to Gartner, in 2013, AWS had five times the capacity of the next 14 competitors put together
ruthlessly cannibalizing its own business where necessary
Kindel llego cuando ten´pia que llegar y Clou también.
he adapted his business model to the possibilities—and the imperatives—of technology
We are entering the third, and most consequential, wave of digital disruption. It has profound implications not only for strategy but also for the structures of companies and industries.
Caso de la encyclopedia Britannica y encarta
The exemplar of this is Amazon, whose successive innovations have been at the leading edge of each phase.
Jeff Bezos’s initial idea was to exploit the Web to deconstruct traditional bookselling. offered a catalogue ten times larger than that of the largest Main Street superstore, at prices 10 to 15 percent cheaper.
Caso Linux y Wikipedia.
Then Amazon went on to exploit the emerging economics of community. collaborative filtering algorithms, goosing sales with messages that “people like you who bought X often buy Y.” launched Amazon Marketplace more than 2 million. All these strategies benefited from the network effect
At third wave Amazon built a global network of 80 fulfillment centers and relentlessly broadened its product line to include almost any product that can be delivered by truck. It offered fulfillment services as an option for small merchants, which could thereby distribute almost as efficiently as Walmart.
In 2006 opened Amazon Web Services (AWS)—cloud computing. a complex stack of computing services. (Amazon even sells the service to competitors such as Netflix.) According to Gartner, in 2013, AWS had five times the capacity of the next 14 competitors put together
El volumen.en los últimos 10 años se ha creado más información que en toda la historia de la humanidad.
La tendencia es cada vez generar más datos.
Muchas personas utilizan como sinónimo el término OLAP con Datawarehouse.
En 1980 Codd introdujo el término
(Bases Datos Operativas).
Hablar de OData
OLTP : indican si hay lugares disponibles en un avión para cierto vuelo, y generar una reservación.
OLAP : muestran la ocupación histórica de los vuelos, esto permite calendarizar sus actividades, etc.
BI is the an umbrella term for a set of methods, processes, applications, and technologies used to
–gather, provide access to, and analyze data and information
–support decision making
•Narrowly speaking, intelligence comes from data (facts).
–In this sense, BI focuses on analytical processing.
•Broadly speaking, intelligence, or knowledge, also comes from human experience and tacit knowledge.
–In this sense, BI is also related to knowledge management (either BI under KM or vice versa)
Not easy….
Technology transforms industries
The position of an industry on this curve depends on the degree to which companies and customers within it have embraced a technology
While conceptual, the curve shows how laggard incumbents have already disappeared from industries in which digital disruption began early, such as traditional media.
In industries where digitization is less pervasive but more a gathering force, there is still time for incumbents to adapt and survive.
Moore refers to the gap between the needs of the early adopters and the needs of the majority as a chasm. “Crossing this chasm,”
Richard Foster describes the evolution of the performance of a technology using an S-curve, as shown in Figure 1. In the beginning, performance improves slowly.
Then, as problems are solved, performance improves rapidly. Finally, the technology reaches its performance limit, and additional expenditure to improve it is unproductive
Most markets experience technology transitions, as shown in Figure 4.
While one technology is in wide use, the next new technology is in development. A technology transition occurs when the performance of the new technology
surpasses the old one. In the lighting industry,
for example, the energy efficiency of incandescent bulbs was surpassed by compact fluorescent tubes, which were in turn overtaken by LED bulbs.
“Crossing this chasm,” he writes, “must be the primary focus of any long-term high-tech marketing plan.”
Clayton Christensen cites the example of 3.5-inch disk drive manufacturers, which targeted the new portable computer market rather than the large and well-established desktop computer market.
Netscape, the producer of the first widely used Web browser, chose instead to challenge Microsoft openly with a potential replacement for applications software (Web apps), eliciting a powerful competitive response. Michael Cusumano and David Yoffie, arguing that this may not have been the wisest strategy, offer this memorable advice:
“Don’t moon the giant.”
A Magic Quadrant provides a graphical competitive positioning of four types of technology providers, in markets where growth is high and provider differentiation is distinct:
El Cuadrante Mágico de Gartneres una representación gráfica de la situación en el mercado de un producto tecnológico en un momento determinado.
http ://www.gartner.com/
El gráfico está dividido en cuatro partes dónde se distribuyen las principales compañías en función de su tipología y la de sus productos.
