Advanced analytics uses sophisticated techniques beyond traditional business intelligence to discover deeper insights from data. It includes techniques like machine learning, data mining, and neural networks. While many major companies invest in analytics, some hesitate due to a lack of structured data or past failures. The document provides suggestions for effective advanced analytics, including choosing the right data sources, building models to optimize business outcomes, and embedding analytics in tools to generate maximum profit. However, companies must set boundaries on data use and consider ethics to avoid illegal or reputation-damaging practices.

1. Making Advanced
Analytics Work for You

2. Advanced Analytics is the autonomous or semi-
autonomous examination of data or content using
sophisticated techniques and tools, typically
beyond those of traditional business intelligence
(BI), to discover deeper insights, make predictions,
or generate recommendations.
Advanced Analytics

3. Advanced Analytic Techniques include:
• Data/Text mining
• Machine Learning
• Pattern Matching
• Forecasting
• Visualization
• Semantic Analysis
Advanced Analytics

4. • Sentiment Analysis
• Network and Cluster Analysis
• Multivariate Statistics
• Graph Analysis
• Simulation
• Complex Event Processing
• Neural Networks
Advanced Analytics

5. •Google and Amazon
have turned into experts
in eclipsing competitors
with powerful new
business models that
derive from an ability to
exploit data.
The Risk of Advanced Analytics

6. • Despite many major companies investing in
Analytics, there are companies that still hesitate
to jump in the bandwagon.
• They are either not prepared with the
requirements of analytics such as structured and
organized data or have suffered losses previously
due to unsuitable data warehousing programs.
The Risk of Advanced Analytics

7. The article makes the following suggestions to
make Advanced Analytics work:
• Choosing the Right Data: Searching for new
sources of data such as social media or previously
ignored data such as customer complaints and
suggestions is a great way to start.
The right IT support will help in cleaning up
and structuring the data.
Suggestions to make Advanced Analytics
work

8. • Build models that predict and optimize business
outcomes: The most effective approach to build
a model originates with identifying the business
opportunity and determining how the model
improve performance.
The company must develop the least
complicated model to improve performance by
studying volumes of data by putting basic
requirements in mind.
Suggestions to make Advanced Analytics
work

9. • Transform the companies capabilities:
Developing useful business-relevant analytics
which are in sync with the company’s day-to-day
processes and decision-making norms by
embedding analytics into simple tools for the
managers to understand is a way to generate
maximum profit.
The managers need to jump into the process
in order to turn literate in data and analytics.
Suggestions to make Advanced Analytics
work

10. Insight
• Analytics despite it’s huge benefits, can have
some loop holes, especially in execution of ethics.
• The companies need to set boundaries on what
data to mine and analyse and what to abstain
from.
• There are several instances in which companies
have become fixated on gathering customer
information and use it unethical or illegal
purposes.

11. Insight
For E.g., some banks can harvest their customers’
checking account data and using advanced
analytics to identify other products that the bank
could cross-sell to them.
While this might not be illegal, these actions hurt
the reputation of banks and ultimately their
business and profit.

12. Insight
• Analysis, while can give great basis and guidance
for decision making, can raise ethical questions
about gathered customer data.
For e.g., For a website or app, the customer
has been asked consent for access for certain data,
he refuses, the website or app can still record his
aggregate behaviour and share, causing a breach
of privacy.

13. Managerial Relevance
• Advanced Analytics is growing not only first world
nation MNCs but also in Indian companies.
• An Indian manager has to jump into the
bandwagon of Advanced Analytics in order to be
able to make more informed decisions.
• Without the guidance of the manager, the team
of analysts can never make the required progress
in developing capabilities in Big Data.