Brief analysis of "Simplify Your Analytics Strategy by Narendra Mulani"

1. Simplify Your
Analytics Strategy
by Narendra Mulani

3. Problem of Business
The interests in analytics and resulting benefits are
increasing by the day, some businesses are challenged by
the complexity and confusion that analytics can generate.
Companies can get stuck trying to analyze all that’s
possible and all that they could do through analytics,
when they should be taking that next step of recognizing
what’s important and what they should be doing — for
their customers, stakeholders, and employees.
Discovering real business opportunities and achieving
desired outcomes can be elusive.

4. Analytical solutions
To overcome this, companies should pursue a simpler path
to uncovering the insight in their data and making insight-
driven decisions that add value. Following are steps that we
have seen work in a number of companies to simplify their
analytics strategy and generate insight that leads to real
outcomes:
Fast data
Fast
insight
Fast
outcomes

5. Insight 1
Next-Gen Business Intelligence (BI) and data
visualization.
• Help companies improve and optimize their
decision making and organizational
performance. BI does this by turning an
organization’s data into an asset by having
the right data, at the right time and place
(mobile, laptop, etc), and displayed in the
right visual form (heat map, charts, etc) for
each individual decision-maker, so they can
use it to reach their desired outcome.
For example, a financial services company
applied BI and data visualization to see the
different buckets of risk across its entire
loan portfolio.

6. INSIGHT 2
Data Discovery
Through the use of data discovery
techniques, companies can test and
play with their data to uncover data
patterns that aren’t clearly evident.
For instance, a resources company
was able to predict which pipelines
are most risky from both physical
and a typical threats through data
discovery techniques. Due to the
insights gained, the firm was able
to prioritize where they should
investfunds for counter-failure
measures and maintenance repairs.

7. INSIGHT 3
Analytics
applications.
Applications can
simplify advanced
analytics as they put
the power of
analytics easily and
elegantly into the
hands of the
business user to
make data-driven
business decisions.
For example, an
advanced
analytics app can
help a store
manager
optimize his
inventory and a
CMO could use
an app to
optimize the
company’s global
marketing
spend.

8. Insight 4

9. Managerial Relevance

10. The role of big data is
becoming larger and larger
in daily life of a business
decision maker. With big
data, it is extremely
important to uncover the
hidden data patterns and
make them applicable
inline to business process.
using the relevant
techniques, a manager can
save a lot of time and
money.

11. With the progress in
'Artificial intelligence‘
field, machine learning
techniques are being
harnessed to reduce the
human efforts. It
removes much of the
human element from the
data modeling process to
produce predictions of
customer behavior and
enterprise performance.

12. Using these relevant
techniques available,
managers can help a
firm saves a lot of
money on other assets
like human workforce,
outsourcing the
research needs, etc.

13. Prakash Raj
Ramjas college
Delhi university.
Internship project
Sameer Mathur
IIM-Lucknow