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贝恩分析技能概要(overview+on+analysis).ppt

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贝恩分析技能概要(overview+on+analysis).ppt

上传人:管理资源吧 2011/12/28 文件大小:0 KB

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贝恩分析技能概要(overview+on+analysis).ppt

文档介绍

文档介绍:A Primer on Analysis
Overview
Confidential Document
TABLE OF CONTENTS
Introduction
General analytical techniques
Graphs
Deflators
Regression analysis
Supply side analysis
Cost structures
Design differences
Factor costs
Scale, experience, complexity and utilization
Supply curves
Demand side analysis
Customer understanding
segmentation and “Discovery”
conjoint analysis
multi-dimensional scaling
Price-volume curves and elasticity
Demand forecasting
technology/substitution curves
Wrap-up
LOGIC AND ANALYSIS CRITICAL TO STRATEGY DEVELOPMENT
Key to strategy development is laying out “logic” to
Understand what makes business work
economics
interactions petitors, segments, time, ......
anize client goals
Devise ways to achieve client’s goals
Help client “make it happen”
A tightly developed piece of this logic is analysis
plex reality to a few salient points
Isolating important economic elements
ANALYSIS IS MORE THAN NUMBER CRUNCHING
Analysis is......
Integrating quantitative and qualitative knowledge
Seeing the bigger picture
Thinking
creatively
conceptually
Not . . .
Endless calculations
Letting statistics dictate/rule
“Classic” scientific rigor
ANALYTICAL BIAS
“Everything can be quantified”
Not really, but
Most “qualitative” effects are based in economics
explicit or opportunity costs
accurately quantifiable or not
Client hires us to analyze and objectify
Quantitative analysis is the basis
CREATIVITY AND ANALYTICAL PERSEVERANCE ARE IMPORTANT TRAITS FOR SUPERIOR ANALYSTS
Strive to address a problem using different approaches to test hypotheses and find inconsistencies
Triangulate on answers
Never believe a data series blindly
Never stop at first obstacle
Clients often stop short of good analysis because they quickly surrender in the absence of good, readily available data
We never surrender to the unavailability of data
Your case leader does not want to hear that “there is no data,” but rather what can be developed, in how much time, and at what cost
WHE