This document provides tips for simplifying an analytics strategy. It recommends accelerating data by creating a hybrid data platform. It also suggests delegating work to analytics technologies like interactive BI tools. Additionally, it advises using data discovery techniques to uncover patterns and find opportunities. Industry-specific applications and machine learning can also simplify advanced analytics. Developing an data-driven culture and talent is important for ensuring an effective analytics strategy.

1. Simplify Your Analytics
Strategy

2. • Analytics are increasingly getting popular due to the
benefits they bring in. Some businesses are
challenged by the complexity and confusion that
analytics can generate.
• Some businesses avoid analytics due to the confusion
they generate or they are unable to find success in
determining the right strategy for their business
model.
The uncertainty of Analytics

4. Following are steps that simplify their analytics
strategy and generate insight that leads to real
outcomes:
•Accelerate the data: Liberate and accelerate
data by creating a data supply chain built on a
hybrid technology environment — a data service
platform combined with emerging big data
technologies
The tips that work

5. •Delegate the work to your analytics
technologies: An interactive BI and visualization
solution can help companies improve and
optimize their decision-making and organizational
performance.
The insight-driven decisions derived from
them could benefit the business.
The tips that work

6. •Through the use of data discovery techniques,
companies can test and play with their data to
uncover data patterns that aren’t clearly evident.
When more insights and patterns are
discovered, more opportunities to drive value for
the business can be found.
The tips that work

7. •Industry- specific and tailored 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.
The tips that work

8. •Advanced Analytics is not the only thing that
works, Machine Learning and Cognitive
Computing also play a major role.
Machine learning is an evolution of analytics
that removes much of the human element from the
data modelling process to produce predictions of
customer behaviour and enterprise performance.
The tips that work

9. •Each path to insight for analysis is unique. Many
different and ever-changing elements come to play
such as business goals, technologies, data types, data
sources, and then some are in a state of flux.
Another main component of a company’s analytics
journey depends on the company’s culture itself. The
company can be more conservative or more willing to
take chances.
The tips that work

10. •The article mentions that there is a chance a
company’s culture might be conservative. Hence,
more hesitant to accept a change.
There is a chance that this might be a
disadvantage as it might bring setbacks in making
the company data-driven.
Insight

11. Hence, the company needs to actively try and
bring in a data driven culture by methods such a
developing insightful, consultive research led by
strong methodlogy.
Insight

12. •Developing talent by recruiting, training and
retaining employees for analytics is another way
to ensure your analytics strategy is getting a great
foundation.
Insight

13. •An Indian manager needs to understand the new
development, i.e., analytics and machine learning
change by constantly trying to be as data literate
as possible.
He is needs to help create a culture of trust
where anyone who is honest and contributes is
rewarded.
Managerial Relevance