This document discusses how companies can make advanced analytics work for them by leveraging big data. It provides three key insights: 1) Companies should identify a clear strategy for how they will use data analytics to compete, deploy the right technology, and take an integrated approach to data, models, and organizational transformation. 2) Companies need to choose the right data sources to solve business problems, get necessary IT support to analyze data, and build models that predict and optimize outcomes. 3) Companies must transform their capabilities by developing business-relevant analytics tools for managers, embedding analytics in frontline tools, and developing skills to exploit big data.

1. Making Advanced Analytics
Work for You
Data Analytics Internship under Prof Sameer Mathur,
IIM Lucknow
Submitted by:N.Girish
IIT Madras.

2. 1st Insight
•Companies working
with big data and its
applications in
analytics are
benefitting and are in
a better position than
their peers.

3. •Even then, most companies are unsure how to
proceed. They’re convinced that their
organizations simply aren’t ready. After all,
companies may not fully understand the data
they already have, or perhaps they’ve lost
piles of money on data-warehousing
programs that never meshed with business
processes, or maybe their current analytics
programs are too complicated or don’t yield

4. •There are many
advantages of working
with big data analytics.
•But companies usually
amy not implement
them.
•Now it is high time that
we start tinking
practically about big

5. Fully exploiting data and analytics requires
three mutually supportive capabilities.
•identify, combine, and manage multiple
sources of data.
•capability to build advanced analytics models
for predicting and optimizing outcomes.
•management must possess the muscle to
transform the organization so that the data
and models actually yield better decisions.

6. This previously mentioned can be done if:
•a clear strategy for how to use data and
analytics to compete.
•deployment of the right technology
architecture and capabilities.
•an integrated approach to data sourcing,
model building, and organizational
transformation.

7. Insight 2
•Choose the Right Data
There's humungous amounts of data
present.We should know what is it that we
require.We must know to source our data
creatively.
Companies can impel a more comprehensive
look at information sources by being specific
about business problems they want to solve or
opportunities they hope to exploit.

8. •Get the necessary IT support.
quickly identifying and connecting the most
important data for use in analytics, followed by a
cleanup operation to synchronize and merge
overlapping data. Such short-term tactics may
lead companies to vendors that focus on
analytics services or emerging software. Hence
establishing an IT infrastructure propels
innovation by facilitating collaboration, rapid

9. •Build Models That Predict and Optimize
Business Outcomes
Data are essential, but performance
improvements and competitive advantage arise
from analytics models that allow managers to
predict and optimize outcomes. More important,
the most effective approach to building a model
originates with identifying the business
opportunity and determining how the model's

10. •Transform Your Company’s Capabilities
the new approaches don’t align with how
companies actually arrive at decisions, or they
fail to provide a clear blueprint for realizing
business goals. Tools seem to be designed for
experts in modeling rather than for people on the
front lines, and few managers find the models
engaging enough to champion their use—a key
failing if companies want the new methods to

11. Using big data requires thoughtful
organizational change, and three areas of action
can get you there.
•Develop business-relevant analytics that can
be put to use.
•Embed analytics into simple tools for the front
lines.
•Develop capabilities to exploit big data.

12. Managerial Relevance
•A manager must encourage the use of big
data analytics if possible.Also he must try to
link these with the new IT skills and
softwares.Managers also need to get creative
about the potential of external and new
sources of data.
•Managers need transparent methods for using
the new models and algorithms on a daily
basis. These managers must use the data-

13. Thank You