©2013
Lavastorm
Analytics. All rights reserved.
1
MARKET UPDATE: Following the
Paradigm Shift
of
Data Analysis
©2013
Lavastorm
Analytics. All rights reserved.
2
Agenda
Changing Data Requirements: Big, Agile, Accurate
Transforming Data Analytics
from
Search
to
Discovery
Turning Data to Information Value
Creating
an
Analytics
-
driven Culture
Analytics for Non
-
technical Executives
New Sales Opportunities from Analytics
Q&A
©2013
Lavastorm
Analytics. All rights reserved.
3
Changing Data Requirements: Big Data
Relational Database Silos,
Structured Data, Data Warehouses
New Databases
& Sources
Enterprise Data
Outside The DW
Unstructured, Semi
-
structured Documents
Big Data Analytics
Unify Silos, More Data
Traditional Analytics
Third
-
Party Data
©2013
Lavastorm
Analytics. All rights reserved.
4
The Importance of Agile Business/IT Collaboration
Organizations that have achieved lasting benefits from
formal data quality improvement programs tend to take
a holistic approach involving
people
, repeatable
processes
, and appropriate
technology
.
An
agile
approach is predicated upon
decentralization
,
moving the
ownership
of data closest to those who
understand
the data and are impacted by quality
control
over the data.
All of this requires
trust
, which is fueled by increased
agility
of analyses and
accuracy
of results.
©2013
Lavastorm
Analytics. All rights reserved.
5
A Virtuous Cycle Of Agility, Accuracy, And Trust
Agility
Accuracy
Trust
Agile collaboration
between self
-
sufficient business
SMEs and data
brokers yields
better, faster
results
Accurate results
increase trust,
lowering objections
to further
decentralization
Trust fosters collaboration between IT departments and business users,
starting with the data
-
driven requirements gathering process which is
essential to trustworthy analyses
©2013
Lavastorm
Analytics. All rights reserved.
6
What Type of Data Manager Are You?
Data Waster
Data Collector
Data
Valuer
Strategic Data User
©2013
Lavastorm
Analytics. All rights reserved.
7
How to Become a Data Strategist
Senior
-
level ownership of the organization’s data strategy
Partnership with IT
©2013
Lavastorm
Analytics. All rights reserved.
8
Analytics as an Organizational Philosophy
Constant tuning and monitoring
of processes
Requires a mix of data sleuths,
analytics software, reporting
coupled with data management
and business stakeholder
involvement
Analytics that provide process
guardrails, coupled with ability to
discover new exceptions
Ability to quickly identify and
resolve issues by business
owners
Explore
Data
Define
Analytics
Define
KPIs
Measure
KPIs
Adjust
Behavior
©2013
Lavastorm
Analytics. All rights reserved.
9
Putting Data to Work at
Fairpoint
NNE
500,000+ customers offering
services from Plain
O
ld Telephone
to Carrier Ethernet services
Converted Northern New England
Verizon territory (ME, NH, and VT)
in 2009
Shifting of revenue from voice to
DSL and Carrier Ethernet service
required advanced data analytics
©2013
Lavastorm
Analytics. All rights reserved.
10
Transforming Data Analytics
from
Search
to
Discovery
Fairpoint
NNE has evolved its
data management and analytic
capabilities over the past 3 years
1. Sync Data
Bring data
together
2. Clean Data
How does it relate
across systems
3. Data Analytics
B
ase decisions on
a single source of
data (single dept.)
4. Expanded Trust
Spread analytics to
other departments
up to the
CxO
level
5. Strategic Adoption
Drive changes at
executive level from
analytics (Book to Bill)
©2013
Lavastorm
Analytics. All rights reserved.
11
Creating an
Analytics
-
driven Culture with Clear
-
cut ROI
Data knowledge
-
> trust
-
> greater value
–
Show how you can relate data across systems
–
Demonstrate you can deliver results in a short period of time
–
Ex: On many occasions turning
CxO
level requests regarding order activity
or customer tendencies in 1
-
2 days
.
•
Led
to a change in Sales criteria: which customers to target for DSL service
Data control leads to better ROI
–
Easy to demonstrate value compared to a traditional Requirements, Design,
Build, Test process
–
Ex: Daily analysis and improvement
of data gathering regarding our
customer line
terms and promotions
with
the
CMO
•
Led
to a repository of customer data leveraged by many department that drives
mail campaigns, SFDC Opportunity generation, and call center activities
©2013
Lavastorm
Analytics. All rights reserved.
12
Qualifying
Analytics Potential
to
Non
-
technical
Executives
Add technology for projects with specific goals/results
–
Ex. Data Sync
of applications was
an initial use of Lavastorm yielding
numerous cleanup efforts increasing revenue and order flow through
Demonstrate that additional analytics can replace or improve
existing processes
–
Ex. Replacing 3
rd
Party “
Scorecarding
” application with one Lavastorm
graph/process
Demonstrate value over and above current process, such as:
–
With
the Lavastorm solution we could visually review the process, and
sample the data at any point in the process to ensure
validity
–
Decommissioned
the old data warehouse and OBIE solution replacing it
with the Lavastorm /
Cyfeon
solution
©2013
Lavastorm
Analytics. All rights reserved.
13
The Difference Between Data Value and Information
Value
Data value
–
just the facts
–
Ex:
R
etention
data analytics
reveals customer
trends associated with what
our customers do at the end of a term or promo
period
Information value
–
Extrapolation shows what the data really means
–
Ex: Realize people are more
likely to leave within the first 30 days after
expiration
of a promotion than at
any time following the
expiration
Business value comes from information value
–
Information value leads to understanding
–
Ex: Drive re
-
term
and promo sales initiatives
at the end of their term
–
we
have
a better chance of retaining a
customer
©2013
Lavastorm
Analytics. All rights reserved.
14
New Sales Opportunities from Analytics
Data management and analytics has yielded a single source of
the truth for
our company
–
Resulting in many
expansions
into the operating
groups within
Fairpoint
–
Personalized analytics
by developing a web
interface to address ongoing
analytic requests from the operating groups
Integration with CRM/
Salesforce
data ties data to sales activities
–
Customer
retention data
reveals customer
trends
and indicators
–
Use
Lavastorm
to generate
opportunities
in
Salesforce
to drive our sales
team to reach out to customers at the point we found that our customers
were leaving
us
©2013
Lavastorm
Analytics. All rights reserved.
15
Summary
Changing data requirements
–
bigger, more agile, more accurate
Strong data analytics foundation is the key, leading to
–
Information that leads to business value
–
Use
–
Trust
–
Expansion
Demonstrations lead to executive buy
-
in and an analytics
-
driven
culture
Analytics exposes greater insights, including new
sales
opportunities
©2013
Lavastorm
Analytics. All rights reserved.
16
Questions, Next Steps
Get Lavastorm
Analytics Engine Public Edition
(FREE)
http://www.lavastorm.com/resources/software
-
downloads
-
trials/
Contact Us
Kerry
Reitnauer
+1
603
-
656
-
8188
kreitnauer@fairpoint.com
Mark Marinelli
+1
617
-
948
-
6244
mmarinelli@lavastorm.com
Brandon Smith
+1
512
-
981
-
9408
bsmith@cyfeon.com
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