Disruptive technologies can be forecasted using the SAW (Steps and Waits) model rather than exponential models like Moore's Law. The SAW model predicts technologies will improve in steps of big improvements separated by waits with no growth, as seen across 26 technologies. This model could have helped Sony timely invest in LCDs over CRTs. To develop disruptive technologies, organizations should build on best practices, consult trusted advisors, think non-incrementally, connect with customers in new ways, and focus on creating connected ecosystems.

1. Exploiting Disruptive Technologies 101
Peter Coffee
VP and Head of Platform Research
salesforce.com inc.

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3. Specifically, “Disruptive” Is*
• Technologically straightforward
• Simpler than prior approaches
• Less than expected by established market
• Attractive in new ways to emerging market
• Initially focused on low-profit customers
• Innovative at faster pace than incumbents
*Bower, Joseph L. & Christensen, Clayton M.
"Disruptive Technologies: Catching the Wave" Harvard Business Review, Jan–Feb 1995

4. In Memory of Disruptees Past
• Imaging: Film  CCD  CMOS
• Printing: Offset  Laser  Inkjet
• Storage: 8”5¼”3½”USB keyCloud
• Connection: Circuits  Packets
• Knowledge: Britannica  Wikipedia

5. Will Today’s Disruptors Sign In, Please?
• Mobility
• Social Computing
• Big Data

6. Mobility: More Than a Handle
There are three parts of user
experience to increase convenience:
immediacy, simplicity and context.
The three parts make up a customer’s
mobile context, or the overall feedback
of what a customer has told you and is
experiencing during engagement.
The Future Of Mobile Is User Context
Context Transforms Product Opportunities For
Consumer Product Strategists

7. The Opposite is “Antisocial”
• ‘Social’ is not non-business
• ‘Social’ is not non-serious
• ‘Social’ is a set of behaviors
– Sensitive to the
user’s context
– Adaptive to interests
– Driven by events to
offer proactive aid

8. Big Data Is Patterns, Not Records
“By combing through 7.2
million of our electronic
medical records, we have
created a disease network to
help illustrate relationships
between various conditions
and how common those
connections are. Take a look
by condition or condition
category and gender to
uncover interesting
associations.”
visualization.geblogs.com/visualization/network/

9. What If We Put Them Together?
What do you get from
• Patterns in big data
derived from
• Social networks
(people/devices)
via
• Ubiquitous mobile
devices/connections?

10. “Inform” is a Verb
• Wiener: information = bits
Shannon: information = entropy
Information  behavior change
• “Even the word ‘library’ is getting
hazy…as the number of media grew,
and the methods for searching became
more sophisticated, there was no
substantive difference between the
Library of Congress and the Central
Intelligence Agency. So they merged.”
– Neal Stephenson, Snow Crash (1992)

11. Social Systems ‘Close the Loop’
• Customers: records  communities
• Employees: appraisals  collaborations
• Partners: supply chain  value network
• Financials: transactions  scenarios
• USAF OODA:
“Observe, Orient,
Decide, Act”

12. Social Systems Demand ‘Big Data’ Power
• Islands of data are cheap, but low-value
• Integrate data with apps: cloud-platform (PaaS) strength
– Data.com: 2 million participants, 1 million updates/month
– Radian6: massive data flows distilled into understanding
– Heroku + Treasure Data Hadoop: 0 to Warehouse in 3 minutes
• Data-driven expertise for developers and managers

13. Social Systems Demand ‘Big Data’ Power

14. What’s Taking So Long?
• “The typical large organization, twenty years hence, will be
composed largely of specialists who direct and discipline
their own performance through organized feedback from
colleagues and customers.”
• “It will be a knowledge-based organization.”
Peter F. Drucker, in The New Realities
…in 1989

15. Barriers to Becoming Knowledge-Based
• Complex legacy IT portfolios have made mere integration of data an
overwhelming task
• Cumbersome and brittle integrations have relegated end users to
roles as mere consumers
• Path of least resistance
has led to over-emphasis
on complex measures…
…based on historical data
• Mere thin-client redesign
attacked the form, not
the substance, of these problems

16. Let’s Disrupt Our Notion of Normal
• On spec, on time, on budget deployment of a fully tested,
proven cloud capability: trusted security and global availability
• Modern applications, driven by user feedback for continuing
improvement – with “clicks, not code” customization
• “No Software”: what’s paid for is function, not code. Continuous
scrutiny of operations, maintenance of facilities, and world-class
security are literally “part of the service”
• Multiple upgrades per year: no disruption, shrinking deployment
times, backward compatibility to previous API releases
• “The future is already here – just not evenly distributed”
- William Gibson

17. Let’s Talk About ‘Why’ – not ‘How’
Fast: no delays of capital budgeting; upgrades part of the service
Focused: no ‘keep the lights on’ software maintenance tasks
Field-ready: deliver coherent data & logic in any user context
Federated: apps market with click-to-try, click-to-integrate
For any organization, anywhere, of any size

18. Can Disruption Be Forecast?

19. Can Disruption Be Forecast?
According to the researchers, Moore’s Law
and other models such as Kryder’s Law and
Gompertz’ Law predict a smooth increasing
exponential curve for the improvement in
performance of various technologies. In
contrast, the authors found that the
performance of most technologies proceeds
in steps (or jumps) of big improvements
interspersed with waits (or periods of no
growth in performance)… While no one law
applies to every market, Tellis and his co-
authors looked at 26 technologies in six
markets from lighting to automobile
batteries, and found that the SAW model
worked in all six, in contrast to several other
competing models.

20. Excuse me, sir, about that rathole…
An example of how the SAW model could
have saved a company from decline is
Sony's investment in TVs. Sony kept
investing in cathode ray tube technology
(CRT) even after liquid crystal display
technology (LCD) first crossed CRT in
performance in 1996...
Sony introduced the FD Trinitron/ WEGA
series, a flat version of the CRT. CRT out-
performed LCD for a few years, but
ultimately lost decisively to LCD in 2001. In
contrast, by backing LCD, Samsung grew to
be the world's largest manufacturer of the
better performing LCD…
"Prediction of the next step size and wait
time using SAW could have helped Sony's
managers make a timely investment in LCD
technology," according to the study.

21. Excuse me, sir, about that rathole…
An example of how the SAW model could Abstract:
have saved a company from decline is The estimates of the model provide four important results.
Sony's investment in TVs. Sony kept
investing in cathode ray tube technology
First, Moore's Law and Kryder's law do not generalize across
(CRT) even after liquid crystal display markets; none holds for all technologies even in a single
technology (LCD) first crossed CRT in market. Second, SAW produces superior predictions over
performance in 1996... traditional methods, such as the Bass model or Gompertz
law, and can form predictions for a completely new
Sony introduced the FD Trinitron/ WEGA technology, by incorporating information from other
series, a flat version of the CRT. CRT out- categories on time varying covariates. Third, analysis of the
performed LCD for a few years, but
ultimately lost decisively to LCD in 2001. In
model parameters suggests that: i) recent technologies
contrast, by backing LCD, Samsung grew to improve at a faster rate than old technologies; ii) as the
be the world's largest manufacturer of the number of competitors increases, performance improves in
better performing LCD… smaller steps and longer waits; iii) later entrants and
technologies that have a number of prior steps tend to have
"Prediction of the next step size and wait smaller steps and shorter waits; but iv) technologies with
time using SAW could have helped Sony's long average wait time continue to have large steps. Fourth,
managers make a timely investment in LCD
technology," according to the study.
technologies cluster in their performance by market.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2115237

22. The World is How Flat?
“It “It now possible for
is is now possible
more people than ever to
more people than ever
collaborate and compete
to collaborate and
in real time...
compete in real time...
…with more other people…
…on more different kinds of work…
…from more different corners of the planet…
…and on a more equal footing…
…than at any previous time in the history of the world.”

23. Build on Best Practices

24. Call on Trusted Advisors

25. Do Not Think Incrementally
• In 1908, 4,700 hours of factory labor would
pay for a Model T Ford;
• Today, the same amount of labor will earn the
price of a Porsche Cayman.
That doesn’t make the Porsche
the commuter vehicle of choice…
…and even a Prius is not tomorrow’s
solution.

26. Do Not Think Incrementally
• In 1908, 4,700 hours of factory labor would
pay for a Model T Ford;
• Today, the same amount of labor will earn the
price of a Porsche Cayman.
That doesn’t make the Porsche
the commuter vehicle of choice…
…and even a Prius is not tomorrow’s
solution.
But in 1908, New York City’s
first subway was only four years old.
• Are you thinking in terms of the
network that will create value?

27. Connect With Customers
in a Whole New Way
Connected Connected
Partners Products
Connected Connected
Customers Employees

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Thank You
pcoffee@salesforce.com