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MAKING ADVANCED
ANALYTICS WORK FOR
YOU
Dominic Barton and David
Court
Big data and analytics have rocketed to
the top of the corporate agenda.
Big data could transform the way
companies do business, delivering the
kind of performance gains last seen in the
1990s, when organizations redesigned
their core processes.
As data-driven strategies take hold, they
will become an increasingly important
point of competitive differentiation.
The time has come to define a pragmatic
approach to big data and advanced
analytics—one tightly focused on how to
use the data to make better decisions.
Fully exploiting data and analytics
requires three mutually supportive
capabilities.
CHOOSE THE RIGHT DATA
1. SOURCE 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.
 Managers also need to get creative
about the potential of external and new
sources of data.
2. GET THE NECESSARY IT
SUPPORT.
 Legacy IT structures may hinder new
types of data sourcing, storage, and
analysis.
 Business leaders can address short-term
big data needs by working with CIOs to
prioritize requirements. This means quickly
identifying and connecting the most
important data for use in analytics, followed
by a cleanup operation to synchronize and
merge overlapping data and then to work
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.
The most effective approach to building a
model rarely starts with the data; instead
it originates with identifying the business
opportunity and determining how the
model can improve performance.
TRANSFORM YOUR
COMPANY’S CAPABILITIES
1. DEVELOP BUSINESS-RELEVANT
ANALYTICS THAT CAN BE PUT TO
USE.
Like early CRM misadventures, many
initial implementations of big data and
analytics fail simply because they aren’t in
sync with the company’s day-to-day
processes and decision-making norms.
2. EMBED ANALYTICS INTO SIMPLE
TOOLS FOR THE FRONT LINES
Managers need transparent methods for
using the new models and algorithms on a
daily basis.
The key is to separate the statistics
experts and software developers from
the managers who use the data-
driven insights.
3. DEVELOP CAPABILITIES TO
EXPLOIT BIG DATA.
Even with simple and usable models,
most organizations will need to upgrade
their analytical skills and literacy.
Managers must come to view analytics as
central to solving problems and
identifying opportunities—to make it part
of the fabric of daily operations.
RECAP
Fully exploiting data and analytics
requires three mutually supportive
capabilities.
1.Choose the Right Data
2.Build Models That Predict and Optimize
Business Outcomes
3.Transform Your Company’s Capabilities
THANK YOU

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Making advanced analytics work for you

  • 1. MAKING ADVANCED ANALYTICS WORK FOR YOU Dominic Barton and David Court
  • 2. Big data and analytics have rocketed to the top of the corporate agenda. Big data could transform the way companies do business, delivering the kind of performance gains last seen in the 1990s, when organizations redesigned their core processes. As data-driven strategies take hold, they will become an increasingly important point of competitive differentiation.
  • 3. The time has come to define a pragmatic approach to big data and advanced analytics—one tightly focused on how to use the data to make better decisions. Fully exploiting data and analytics requires three mutually supportive capabilities.
  • 5. 1. SOURCE 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.  Managers also need to get creative about the potential of external and new sources of data.
  • 6. 2. GET THE NECESSARY IT SUPPORT.  Legacy IT structures may hinder new types of data sourcing, storage, and analysis.  Business leaders can address short-term big data needs by working with CIOs to prioritize requirements. This means quickly identifying and connecting the most important data for use in analytics, followed by a cleanup operation to synchronize and merge overlapping data and then to work
  • 7. BUILD MODELS THAT PREDICT AND OPTIMIZE BUSINESS OUTCOMES
  • 8. Data are essential, but performance improvements and competitive advantage arise from analytics models that allow managers to predict and optimize outcomes. The most effective approach to building a model rarely starts with the data; instead it originates with identifying the business opportunity and determining how the model can improve performance.
  • 10. 1. DEVELOP BUSINESS-RELEVANT ANALYTICS THAT CAN BE PUT TO USE. Like early CRM misadventures, many initial implementations of big data and analytics fail simply because they aren’t in sync with the company’s day-to-day processes and decision-making norms.
  • 11. 2. EMBED ANALYTICS INTO SIMPLE TOOLS FOR THE FRONT LINES Managers need transparent methods for using the new models and algorithms on a daily basis. The key is to separate the statistics experts and software developers from the managers who use the data- driven insights.
  • 12. 3. DEVELOP CAPABILITIES TO EXPLOIT BIG DATA. Even with simple and usable models, most organizations will need to upgrade their analytical skills and literacy. Managers must come to view analytics as central to solving problems and identifying opportunities—to make it part of the fabric of daily operations.
  • 13. RECAP
  • 14. Fully exploiting data and analytics requires three mutually supportive capabilities. 1.Choose the Right Data 2.Build Models That Predict and Optimize Business Outcomes 3.Transform Your Company’s Capabilities