Applied analytics is all about creating actionable insights that can be injected back into a business process at the point of highest impact. This slideshow walks you through the "11 Principles of Applied Analytics" from Georgian Partners.

1. How to Use Analytics to Create Value,
Enhance Your Business and Disrupt Your Industry
The 11 Principles
of Applied Analytics

2. Applied analytics is all about
creating actionable insights
that can be injected back into
a business process at the
point of highest impact.
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3. The idea is to use
the insights to make
your business
processes more
intelligent, efficient
and valuable.
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4. Get it right
and you can create better experiences
for your customers, grow your business,
and even disrupt your industry.
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5. But we’re getting ahead
of ourselves. First we’ve
got to understand how
to approach applied
analytics.
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6. To help, we’ve put together the
following 11 principles of applied
analytics to help frame your thinking.
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7. Understand the
process.1
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8. Understanding the process
means not just thinking about
the data you already have
access to or the analytics
technologies you currently
understand.
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9. Instead, you’ve got to
identify the most actionable
and valuable insights that
could change outcomes
in the business process
your solution drives.
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10. Identify and
prioritize the most
valuable insights.
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11. Since not all analytic
insights are of equal value,
you have to figure out
which ones are going to
have the greatest impact.
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12. And don’t just consider the
value of a particular insight.
You’ve also got to look at how
refined the insight is and how
widely it can be used across
an organization.
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13. To determine the value of your insights,
use this simple equation:
value of insight
degree of refinement
consumption
x
x
The value of analytic impact =
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14. Create a data set that
is unique and broad.3
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15. Try to draw data from the widest
range of sources possible and
to get exclusive usage rights
whenever possible.
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16. WHY?Because it would be hard to duplicate
your data, making it difficult for others
to provide the same insights.
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17. Ultimately, your goal
is to create a dataset
that no one else can
using data from across
a market eco-system.
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18. Recognize that raw
data alone is of little
or no value.
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19. Simply storing as much data as
possible isn’t useful. Your data
needs be refined to support insights.
Guess what.
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20. data validation
cleansing and de-duplication
data integrity checks
creating aggregates &
standardizing the structures
definitions of your data
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That means:
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21. Oh,
and by the way,
if you’re bringing together
multiple data sets, you’ve
got to use a common
data model.
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22. Insights are more
valuable the closer they
are to being actionable.
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23. Then you’ve got to
reduce the amount of
interpretation and effort
required to take action.
Want to succeed
with data and
analytics?
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24. In other words,
your goal should be to
minimize the effort that
a user —or even a
downstream process
— needs to turn an
insight into an action.
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25. That effort is the “analytic
delta.” The closer that any
insight is to the point where
an action could be taken,
the smaller the delta will be.
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26. Leverage the shortage
of data scientists to
your advantage.
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27. Ok, so there aren’t enough
people out there with big
data and analytics talent.
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28. The good news
is that if you can
deliver insights from
big data as a solution,
or part of a wider
offering, you’ll have a
competitive
advantage.
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29. In fact, the lack of data
scientists will give you the
opportunity to drive higher
margins, provided you can
deliver analytic insights in
your product.
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30. Separate analytic
insight from how
it’s consumed.
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31. Don’t limit your options for delivering
insights to the particular analytic tool or
platform your company knows best or
has access to today.
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32. Instead, consider all of your
delivery options, including:
reports
dashboards
search & query UIs
alerts
rules engines and APIs
“Insight as a Service”
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The bottom line is
don’t let your choice
of analytic tool
define your method
of delivery.
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33. Inject insights into
business processes
at the moment of
highest impact.
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34. is to enable insights that have
an impact on a business
process at the right
time and in the most
appropriate way.
The goal of
applied analytics
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35. You can increase the
value of those insights
by automating their
delivery either to the
right person or into the
right business process.
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36. It’s not about
“owning” the data.9
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37. Whether a company “owns”
a particular set of data, or
not, is less relevant than what
that company’s rights are to
use the data.
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38. In other words
you need the right
to use data.
And you have to ensure that your
usage complies with both regulations
and marketplace expectations.
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39. ✔
Once secured, these information rights
will become the basis for your applied
analytics strategy.
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40. Governance and
compliance is a
foundational discipline.
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41. When you don’t have a
pro-active strategy you wind
up with ad-hoc and reactive
responses to events.
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42. That means taking a
proactive approach
to privacy needs to
be a top priority. So
should customer
business continuity.
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43. Be analytical in your
own business.11
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44. You should be leveraging analytics
within your own company to
optimize your operations.
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45. That means analytically
enabling all of your
employees and making
your entire organization
more analytical.
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46. Your goal should be to
embrace data-driven
decision-making about
both your solutions and
your customers.
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47. Applied analytics represents a
huge opportunity for companies to
create value as business process
knowledge, big data, and
information rights converge.
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48. Understand the process.
Identify and prioritize the most valuable insights.
Create a data set that is unique and broad.
Recognize that raw data alone is of little or no value.
Insights are more valuable the closer they are to being actionable.
Leverage the shortage of data scientists to your advantage.
Separate analytic insight from how it’s consumed.
Inject insights into business processes at the moment of highest impact.
It’s not about “owning” the data.
Governance and compliance is a foundational discipline.
Be analytical in your own business.
To unlock that opportunity,
keep these 11 principle in mind:
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49. Want to learn more about
applied analytics?
Download our
white paper
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