Advanced analytics uses sophisticated techniques like machine learning, data mining, and predictive modeling to gain deeper insights from data beyond traditional business intelligence. While executives see the potential benefits, most companies are unsure how to implement advanced analytics. The document recommends starting with targeted efforts to build models from existing data sources and transform organizational culture, rather than massive overhauls. This balanced approach can help companies develop analytics capabilities and maintain flexibility as technologies and opportunities evolve.

1. Making Advanced
Analytics Work For You
~ Dominic Barton & David Court
Under guidance of
Prof. Sameer Mathur

2. Introduction
Big data and analytics have rocketed to the top of the corporate
agenda. Executives look with admiration at how big companies
like amazon, Google and others have eclipsed competitors with
powerful new B-model that derive from an ability to exploit data.
They also see that big data is attracting serious investment from
technology giants such as IBM and HP. Meanwhile, the tide of
private-equity and venture-capital investments in big data
continues to swell.

3. Big data could transform the way companies do
business, delivering the kind of performance gains
last seen in the 1990s, when organisations
redesigned their core process.
The trend is generating plenty of hype, but we
believe that senior leaders are right to pay attention.
As data-driven strategies take hold, they will
become an increasingly important point of
competitive differentiation.

4. Advanced Analytics
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
techniques include those such as
data/text mining, machine learning,
pattern matching, forecasting,
visualisation, semantic analysis,
complex event processing, neural
networks.

5. Why Advanced Analytics is
Important
The current age of information and digitalisation has
brought with it new technologies and methods for
improving business operations and maintaining
competitive advantage: New big data technologies cable
cost-effective storage, processing and analysis of large
amounts of data, Modern and intuitive user interfaces
allow more user groups to draw insights and make
informed decisions, Advanced analytics software enables
better analysis, and analysis of relationships and future
events.

6. Since modern technologies and techniques to accelerate or otherwise
improve decisions or processes along the value chain are now widely
available, it is important to carefully evaluate how advanced analytics
can be used within your company in order to keep pace with the
competition.

7. How Important Is Advanced
Analytics For Professionals
Generally, most companies see advanced and predictive analytics
as one of the more important BI trends in 2017. However, there are
a few differences in viewpoint across various user and company
types.
Best-in-class companies and organisations in North and South
America lead the way when it comes to predictive and advanced
analytics.
On the other hand, the trend is much less important in
telecommunications companies and the German-speaking region
of Central Europe.

8. Big Data: The Management
Revolution

9. According to research by Andrew McAfee and
Erik Brynjolfsson, of MIT, companies that
inject big data and analytics into their
operations show productivity rates and
profitability that are 5% to 6% higher than
those of their peers.
Even so, our experience reveals that most
companies are unsure how to proceed.

10. Skepticism
Leaders are understandably leery of making substantial
investments in big data and advanced analytics.
They’re convinced that their organisations 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 insights that can be put to use.
Or all of the above, no wonder skepticism abounds.

11. Solution
Rather than undertaking massive overhauls of their companies,
executives should concentrate on targeted efforts to source data,
build models, and transform the organisational culture.
Such efforts will play a part in maintaining flexibility.
That nimbleness is essential, given that the information itself-along
with the technology for managing and analyzing it- will continue to
grow and change, yielding a constant stream of opportunities.
As more companies learn the core skills of using big data, building
superior capabilities may soon become a decisive competitive
asset.

12. Overview
Overall, the data shows that the trend for advanced
and predictive analytics is on the rise. This is
especially true in best-in-class, Eastern European
companies and organisations from the United
Kingdom and Ireland, as well as the
telecommunications industry.
Surprisingly, advanced and predictive analytics is seen
as less important by companies from the
telecommunications industry this year.

13. “Thank-you”
–Veerbhadra Sharma