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Day 1 Competing with Analytics by Mind Map: Day 1 Competing with Analytics
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Day 1 Competing with Analytics

Quotes

The unexamined life isn't worth living - Socrates

The unexamined decision isn't worth making. -Davenport/Harris

Statistics are often used as a drunken man uses a lamppost -- for support rather than illumination. - Andrew Lang

Segmentation

National

Analytical Drivers, Situational Analysis / Drivers, What is driving us to do this?, SWOT Analysis, Strengths, Weaknesses, Opportunities, Threats, Customer Findings - What have we learned from customers?, Competitive Analysis, Do we have competitors and threats in these target markets with the proposed offerings?, What are our competitors doing and how are they positioning?, How do we position against each competitor?, Target Customer(s), Buyer Profile, Title, Industry, Geography, Business Size, Influencer Profile, User Profile, What do customers want and need?, What business problems do each of these customers have?, Customer Segmentation, Which customers or sets of customers do we sell to?, What are the target market segments that we want to go after?, What are the distinct problems for each segment of the market?, Total Available Market, New Prospects, How much of each target segment have we penetrated?, How much opportunity is available in each target segment?, Existing Customers, Can we up-sell existing customers?

International

Analytical Drivers, Situational Analysis / Drivers, What is driving us to do this?, SWOT Analysis, Strengths, Weaknesses, Opportunities, Threats, Customer Findings - What have we learned from customers?, Competitive Analysis, Do we have competitors and threats in these target markets with the proposed offerings?, What are our competitors doing and how are they positioning?, How do we position against each competitor?, Target Customer(s), Buyer Profile, Title, Industry, Geography, Business Size, Influencer Profile, User Profile, What do customers want and need?, What business problems do each of these customers have?, Customer Segmentation, Which customers or sets of customers do we sell to?, What are the target market segments that we want to go after?, What are the distinct problems for each segment of the market?, Total Available Market, New Prospects, How much of each target segment have we penetrated?, How much opportunity is available in each target segment?, Existing Customers, Can we up-sell existing customers?

Global

Analytical Drivers, Situational Analysis / Drivers, What is driving us to do this?, SWOT Analysis, Strengths, Weaknesses, Opportunities, Threats, Customer Findings - What have we learned from customers?, Competitive Analysis, Do we have competitors and threats in these target markets with the proposed offerings?, What are our competitors doing and how are they positioning?, How do we position against each competitor?, Target Customer(s), Buyer Profile, Title, Industry, Geography, Business Size, Influencer Profile, User Profile, What do customers want and need?, What business problems do each of these customers have?, Customer Segmentation, Which customers or sets of customers do we sell to?, What are the target market segments that we want to go after?, What are the distinct problems for each segment of the market?, Total Available Market, New Prospects, How much of each target segment have we penetrated?, How much opportunity is available in each target segment?, Existing Customers, Can we up-sell existing customers?

Predictive Modelling

Churn

Loyalty

Overview of Business Analytics

Analytical Problems and Decision Making

Benefits of being analytical, Help manage and steer the business in turbulent time, Know what's really working, Leverage previous investments in IT and information, more insight, faster execution, more business value in many processes, Cut costs / improve efficiency, Manage risk, Anticipate changes in market conditions, Have a basis for improving decisions over time

analytical, use of analysis, data, and systematic reasoning to make decisions

key questions, dimensions, Time frame, past, present, future, Innovation, information, insight, questions (Fig1-1, p7), What happened?, past, information, Reporting, How and why did it happen?, past, insight, Modeling, experimental design, What is happening now?, present, information, Alerts, What's the next best action?, Present, Insight, Recommendations, What will happen?, Future, Information, Extrapolation, What's the best/worst that can happen?, future, insight, prediction, optimization, simulation

where apply analytics, customer relationship management, supply chain, operations, human resources, performance management, finance and accounting, other

analytics not practical, no time, no precedent, history is misleading, decision maker has considerable expertise, variables can't be measured

decision making errors, Logic, not asking right questions, incorrect assumptions / not testing assumptions, use analytics to "justify" rather than let facts guide, fail to take time to understand alternatives, fail to interpret data correctly, Process, make careless mistakes, fail to consider analysis and insights in decisions, fail to consider alternatives, use incorrect / insufficient decision-making criteria, gather data or completing analysis to late to be of use, postponing decision because of data or analysis dissatisfaction

Gut Feel

40% of major decisions are based not on facts, but on the manager's gut.

Analytical Assessment

Five Stage Model of Analytics, 1: Analytically Impaired, 2: Localized Analytics, 3: Analytical Aspirations, 4. Analytical Companies, 5. Analytical Competitors

Being Analytical

defined: the use of analysis, data, and systematic reasoning to make decisions

key is to be thinking how to become more analytical and fact based in decision making and to use the appropriate level of analysis for the decision at hand (p. 4)

Where to Analytics Apply?

customer relationships

supply chain and operations

human resources

finance and accounting

When are Analytics Not Practical?

When there's no time

When there's no precedent

When history is misleading

When the decision maker has considerable experience

When the variables can't be measured

Authors

Davenport, Thomas H.

Harris, Jeanne G.

Morison, Robert

Stubbs, Evan

Campaign Systems

Introduction

Optimization

Optimization in practice

Analytical Landscape