I read an intriguing article last week, authored by Don Peppers, noted author and founding partner at Peppers & Rogers Group. The article, titled Moore’s Law Doesn’t Apply to Business Decisions, talks about the proliferation of new data and how we are producing new information 50 times faster than in 2005. As a quick refresher, in its simplified form, Moore’s Law states that computing power will roughly double every two years.

1. Why Big Data Is Such A Big
deal in decision making
Jay Jesse
President, CEO
Intelligent Software Solutions
Presentation by:

2. Summary
I read an intriguing article last week, authored by Don Peppers,
noted author and founding partner at Peppers & Rogers Group.
The article, titled Moore’s Law Doesn’t Apply to Business
Decisions, talks about the proliferation of new data and how we
are producing new information 50 times faster than in 2005.
As a quick refresher, in its simplified form, Moore’s Law states
that computing power will roughly double every two years.

3. Massive memory database
The article discusses the convergence of this growing
computing power with the proliferation of data. According to
Peppers,
“businesses not only have thousands
of times more data to work with, but
they also have thousands of times
more computational power with which
to do the work, from massive ‘in
memory’ databases to advanced
statistical programs and algorithms.”

4. Keeping pace
Like me, you may be asking why, with this avalanche of
data, supported by extremely powerful hardware and
software – can the effectiveness of corporate and
governmental decision making keep pace? If not, we need
to ask whether the problem is one of process, technology
or people (or perhaps all three).

5. To quote from the Don Pepper’s article, “The problem
facing us now, however, is that the human skills and talents
business managers require, in order to make better
decisions with all this data and computational power are not
improving. Moore’s Law doesn’t make us a thousand times
better at reasoning every couple of decades. It doesn’t
even make us 10 times better.”
People

6. Individuals tasked with making decisions face challenges
that haven’t really changed over the years (decades). They
bring their past habits and biases to bear, as well as a
reluctance to try new things.
The problem may also be one of training or technical
sophistication.
People

7. Individuals tasked with making decisions face challenges
that haven’t really changed over the years (decades). They
bring their past habits and biases to bear, as well as a
reluctance to try new things.
The problem may also be one of training or technical
sophistication.
People

8. This is why many of us who have smartphones containing
dozens of features and applications may only take
advantage of only a handful. And perhaps the vast
distance between the speed of improvement for computing
vs. us humans is why some people predict the “rise of the
machines”.
People

9. Even the hottest new technology (hardware and software),
combined with talented and committed personnel, will fall
short of achieving goals if not combined with the business
processes necessary to capitalize on the data.
Process

10. Process
We talk about this in terms of the four V’s model of
capitalizing on Big Data in a way that allows organizations
to benefit from data, rather than being swamped or having
useful data disconnected and slumbering away on various
databases or storage media. The first three Vs in the value
chain are Volume, Variety and Velocity.

11. Contending with, and overcoming the challenges of the
first three Vs yields the fourth: Value. By accounting for
volume, variety and velocity, we equip our business
analysts and leaders to “shrink the haystack,”
establishing a data processing ecosystem that can
process, enable search and allow users to interact with
the data in fruitful ways, rather than being overwhelmed
and in the dark. The end result is better decision-making
through superior insight by revealing threats and
opportunities that had previously been invisible in a mass
of data.
Process

12. The role of technology in the decision process is to support
the processes and people as we identified above, in the
four key areas shown in this graphic.
Technology

13. Technology

14. Technology support for big data
decision making
Content Acquisition
Search/Discovery
Semantic Enrichment
Applying Data Perspectives

15. Content acquisition
The first stage of technology support is to pull all
information into a common environment so that it can be
pushed through an analysis pipeline.

16. Enterprise search is the first of a “one-two punch” that
eventually enables actionable insight from what was
previously an unmanageable mountain of data. After
content acquisition, content is indexed and pushed into
its own optimized search engine. This index can be
tuned for the kind of search and discovery that supports
the kind of queries your data analysts need to make.
Search/Discovery

17. NLP (natural language processing) is the second part of the
one-two punch that fuses what the analyst knows with what
he or she doesn’t know, allowing users to constantly tune
and refine smaller subsets of data for key factors. The
system “learns” as the user refines their searches to better
target their data domain, constantly improving search
effectiveness.
Semantic Enrichment

18. As refined searches isolate the critical content, data
perspectives give you the ability to reduce the data gleaned
from targeted queries and roll it up into graphs, time-series
databases, geospatial representations and more, revealing
connections and trends that were invisible at the beginning
of the process.
Applying Data Perspectives

19. By aligning and optimizing your people, processes and
technology, you will be able to take full advantage of
Moore’s Law, reap the fruits of Big Data and make
decisions that have a positive impact on shareholders,
customers, employees or citizens.
Total Alignment

20. Learn More
ISS is a company that cares deeply about data and, most importantly,
about empowering our customers by delivering the right data at the
right time. The amount of data being generated and shared is growing
exponentially, producing information overload and cluttering vision,
mission or enterprise goals.
ISS turns this information overload into information advantage.
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