18,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Leverage big data and demand into sustainable profitable growth Optimizing Growth is a handbook for how to succeed in the age of big data. Today's business environment looks dramatically different than it did even a decade ago, and it continues to evolve at an increasing rate; macroeconomic shifts, consumer trends, technological advances, and changing competitive dynamics are accelerating the pace of change, and businesses are struggling to grow amidst the turbulence. This book provides insightful guidance, real-world success stories and practical tools to achieve growth in this new era, utilizing big data to achieve a deeper understanding of demand, customers, competitors, and opportunity. With disruption around every corner, growth now demands innovative new approaches and an improved capacity to meet customer needs; by gaining a stronger grasp of demand, businesses can elevate performance from "survive" to "thrive." This book provides the approaches, analytics, frameworks, and organizational capabilities required to gain competitive advantage, and describes the new mindset required to leverage these tools into sustainable growth. * Develop a deeper understanding of your business's growth factors * Re-sync your thinking to gain greater leverage against disruption * Delve deeper into demand, and boost fulfillment capabilities * Capture more growth opportunities using precision analytics frameworks The one thing that will never change about business is the goal of growth--but the paths to growth change continuously. New opportunities forge new routes to the top, while others become obsolete--does your company know the difference? The ability to differentiate between fads and genuine evolution is more critical than ever before. Optimizing Growth provides deep knowledge of what's out there, and a clear framework for forging ahead.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 359
Veröffentlichungsjahr: 2018
Ähnliche
Table of Contents
COVER
PREFACE
ABOUT THE AUTHORS
SECTION I: Why Greater Precision
CHAPTER 1: The Growth Challenge
Precision That Pays
A Challenging Growth Environment
Generational Shifts in the U.S
The Age of Disruption
The Profitable Growth Imperative
The Innovation Edge
Big Data's Role
Cost Cutting and Its Limitations
Getting to Growth
Endnotes
CHAPTER 2: Building a Demand-Based Business System
Endnote
CHAPTER 3: A New Business Model
Expanding the Kingdom of the King of Beers
Changing the Existing “Mental Model”
Building the Quantitative “Demand Landscape”
From Insights to More Precise Actions
Getting It Right at Retail
Hitting the Sweet Spot
AB and the Eight Demand-Based Business System Characteristics
Banking on a New Model
Endnotes
SECTION II: The Precision to Optimize Your Current Business
CHAPTER 4: Building a Demand “Early Warning System”
Pet Industry Trends: From the Dog House to the Penthouse
Demand Trends
Current, Emerging, and Latent Demand
Current Demand: Growth Opportunities Hidden in Plain View
Emerging Demand: Getting Beyond the Tip of the Iceberg
Latent Demand: Tapping into Unarticulated Opportunities
Demand Triggers
Final Thoughts
Endnotes
CHAPTER 5: Enhanced Demand Landscape
The Failures of Traditional Market Segmentations
The Benefits of the Enhanced Demand Landscape
The Benefits of Enhanced Segmentation
The Challenge in Implementing a Complex System
Constructing an Enhanced Demand Landscape
Case Study in Financial Services
Endnotes
CHAPTER 6: Precisely Locating Demand
Locating Demand Using Traditional Statistical and Econometric Techniques
Disruptions to Traditional Approaches
Closing Knowledge Gaps and Vulnerabilities
Major Benefits of the Data-Driven Approach
How to Reap the Benefits of Higher-Precision Systems
Implementing a Precision-Demand System at Your Organization
Endnotes
CHAPTER 7: Brand Economics: Unlock the Power of Your Brand
What Is a Brand?
Driving Brand Value
The Brand Value Proposition
A Brand Turnaround: The Samsung Story
Characteristics That Set Great Brands Apart
Brand Economics at Facebook
Take the Brand Challenge
Endnotes
CHAPTER 8: Pricing with Precision
Driving for Differentiation
Price to Customer Segments, Not Markets
Differentiation in Commercial Printing
Managing the Value Equation
Good, Better, Best
Pricing Reference Points
Developing a Pricing Power Mindset
Conclusions
Endnotes
SECTION III: Moving to a Demand-Driven Business System: The Big Data Advantage
CHAPTER 9: Innovation That Works
Building the Right Foundation
A More Robust Innovation Process
An Innovation Portfolio
Finding Innovation Drill Sites
The Role of Big Data
Stepping Up to the Plate
Conclusions
Endnotes
CHAPTER 10: Demand-Based Cost Reduction
Endnotes
CHAPTER 11: Winning in a Digital World
Driving Digital Innovation
A Digital Early Warning System
Identifying and Understanding Target Consumers
Mapping Digital Purchase Decisions
Using Digital Tools to Build Affordable Housing
Digital Collaboration
A Mission to Win Consumers Back to the Store
Conclusions
Endnotes
INDEX
END USER LICENSE AGREEMENT
List of Illustrations
Chapter 1
Figure 1.1 Optimized business system insights and aligned activation.
Figure 1.2 The optimized approach to growth goes beyond traditional approaches while leveraging Big Data capabilities.
Chapter 2
Figure 2.1 Differing internal views of demand.
Figure 2.2 The demand system aligns activities.
Figure 2.3 The demand system aligns data.
Figure 2.4 Building the demand business system.
Figure 2.5 A demand-based business system.
Figure 2.6 Action plan to build a demand business system.
Figure 2.7 Demand chain business system: diagnostic questions.
Figure 2.8 Demand chain business system: diagnostic questions.
Figure 2.9 Demand chain business system: diagnostic questions.
Figure 2.10 Demand chain business system: diagnostic questions.
Figure 2.11 Demand chain business system: diagnostic questions.
Figure 2.12 Demand chain business system: diagnostic questions.
Figure 2.13 Demand chain business system: diagnostic questions.
Chapter 3
Figure 3.1 Dimension 1 – distinct consumer segments.
Figure 3.2 Consumer demand landscape – U.S. hypothetical example.
Chapter 4
Figure 4.1 The evolving role and relationship of dogs in the U.S., 1900–2007.
Chapter 5
Figure 5.1 Factors that distinguish consumers.
Chapter 7
Figure 7.1 Illustrative Brand Value Proposition for global IT firm.
Figure 7.2 In 1999, Samsung set an aggressive goal to build a brand rivaling Sony in five years.
Figure 7.3 Brand Economics model.
Figure 7.4 Cost-benefit trade-offs among Facebook users.
Chapter 8
Figure 8.1 Theoretical value equation alignment.
Chapter 9
Figure 9.1 Portfolio of innovation types.
Chapter 10
Figure 10.1 Typical ZBB toolkit.
Figure 10.2 Traditional cost reduction vs. demand-based orientation.
Figure 10.3 Two types of cost drivers.
Figure 10.4 Assessing where and how to take action.
Figure 10.5 Insights from the demand-based view.
Figure 10.6 Matching action with growth strategy.
Chapter 11
Figure 11.1 Consumer path to purchase – the new paradigm.
Guide
Cover
Table of Contents
Begin Reading
Pages
C1
iii
iv
vii
viii
ix
xi
xii
xiii
1
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
67
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
165
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
187
188
189
190
191
192
193
194
195
196
197
198
199
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
221
222
223
224
225
E1
OPTIMIZING GROWTH
Predictive and Profitable Strategies to Understand Demand and Outsmart Your Competitors
JASON GREEN | MARK HENNEMAN | DIMITAR ANTOV
Copyright © 2018 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600, or on the Web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002.
Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com.
Library of Congress Cataloging-in-Publication Data
Names: Green, Jason, 1963- author. | Henneman, Mark, 1961- author. | Antov, Dimitar, 1978- author.
Title: Optimizing growth : predictive and profitable strategies to understand demand and outsmart your competitors / Jason Green, Mark Henneman, Dimitar Antov.
Description: Hoboken : Wiley, 2018. | Includes index. |
Identifiers: LCCN 2017058594 (print) | LCCN 2018008033 (ebook) | ISBN 9781119462194 (pdf) | ISBN 9781119462200 (epub) | ISBN 9781119462224 (hardback)
Subjects: LCSH: Organizational change. | Creative ability in business. | Information technology—Economic aspects. | BISAC: BUSINESS & ECONOMICS / Finance. | BUSINESS & ECONOMICS / Development / Economic Development. | BUSINESS & ECONOMICS / Economics / General.
Classification: LCC HD58.8 (ebook) | LCC HD58.8 .G723 2018 (print) | DDC 658.4/06—dc23
LC record available at https://lccn.loc.gov/2017058594
Cover Design: Wiley
PREFACE
This is a book about successfully driving profitable growth in a rapidly changing environment. Our goal is to provide principles, approaches, frameworks, and tools that can be applied to virtually any type of business in any industry, whether business to consumer (B2C) or business to business (B2B), large or small, or local or global, to help drive growth. By describing the key steps in an overarching growth process in enough detail, we hope to make each step and its related components actionable for any manager. We have attempted to provide a range of approaches from simple “back of the envelope” exercises and key questions to sophisticated Big Data analytics to help kick-start any growth effort within any organization.
Throughout the book we use case examples to help bring key concepts alive. Our intent is to provide a range of case examples across industries and situations from market-leading companies that wanted to extend their lead to turnaround situations where there was danger of failing. We hope the cases will be both informative and inspiring. When growth has stalled, it is often a symptom of fundamental changes among customers and markets that may make the tried-and-true playbook that drove prior successes less effective. Beyond having a plan for reigniting growth, it takes personal courage and conviction to undertake a process that might challenge the organization's conventional wisdom and then alter or even rewrite the playbook that built the business in the first place.
The book will reinforce four key themes based on our experiences that we believe are critical for successfully achieving growth objectives:
First, we believe that the most certain path for achieving profitable growth begins with insights into demand. We think of demand as the solutions consumers and customers are seeking across the entire range of situations they experience day in and day out. A solution for feeling more energized in the morning, a solution for transforming my business from selling products to providing services, a solution for paying off credit card debt, and so on. Some groups or segments of consumers/customers are highly satisfied with the current solutions available to them. Others are highly dissatisfied with everything they are aware of or have tried. This is why sales figures are not a true indicator of the actual demand in a given market; sales receipts do not measure unfulfilled demand.
Understanding how demand varies by segment of consumer and customer is a critical aspect of identifying the most attractive growth opportunities in the market. Demand is not one homogeneous block. Developing insights into what we call “demand segments,” along with insights into what drives demand, what fulfills demand, and the economics of demand, make up the foundation for building a successful growth strategy.
In addition, we believe much greater precision will be needed to drive growth than ever before. More precise insights leading to more precise investments and actions will reduce waste and create a potentially significant edge. Understanding precisely who to win with and how to win with them will require increasing levels of precision as retail channels expand, media options fragment, and the choices available to consumers and customers increase dramatically. For example, if businesses don't have a precise understanding of the new digital path to purchase, the most critical search terms being used by attractive customers, or the role of ratings and rankings on purchase decisions, their offers may never even make the consideration set for key consumers.
We also believe that growth is best achieved through a comprehensive system that continually identifies and tests potential growth hypotheses. The system we propose is focused on continually answering what we call the How, Who, What, Where, Why, and How To of growth opportunities. Starting from demand, we believe managers have to constantly ask and update their learnings about how demand is shifting and what the drivers of those changes are. The next question to address is to determine who the most attractive segments of consumers and customers are based on their demand within a given category. Then the firm can go deep with those attractive consumers and customers to understand precisely what their demand is for and how to fulfill it. Our goal is to describe a step-by-step system to follow that can be regularly updated to enhance the level of insights into demand.
Finally, almost every aspect of the growth process can be improved by leveraging Big Data capabilities, including digital approaches. Whatever your starting point, we believe the ability to leverage Big Data, including digital approaches, in ways that create a more precise understanding of demand, customers, competitors, and opportunities will become an increasingly important driver of competitive advantage. To be clear, Big Data in and of itself is not a strategy or a panacea for curing growth issues. Nor will sustainable growth be achieved by taking a flawed business model, a set of offers that are not aligned to demand, and a weak brand online. The promise of Big Data is to help identify trends and enhance your understanding of opportunities, not to do the critical thinking for you.
Ultimately, it is our hope that this book will inspire you to drive growth within your organization while providing the tools you will need to achieve your growth objectives.
ACKNOWLEDGMENTS
Writing this book has been a true team effort. There are many people we wish to thank for their contributions to the content of the book and for their support throughout the process of writing this book.
We'd like to start by thanking our families. Many thanks for all of the encouragement and advice from Gwen Farley Green, Alex Green, and Amanda Green. Thank you to Mary Blue Henneman, a former principal at The Cambridge Group, as well as Nicholas Henneman and Ellie Henneman. We are also grateful for the support from Stanimir and Tzvetanka Antovi. A book like this is an undertaking we could never have completed without ongoing support from each of our families.
Our team was very fortunate to have Linda Deeken, chief marketing officer of The Cambridge Group, engaged throughout the process of developing this book. Linda has been a valuable thought partner throughout this effort. She is also a true problem solver who cleared hurdles that seemed insurmountable and kept everything moving forward by providing insights, conducting research, and suggesting edits. On this team, Linda is our MVP.
We are grateful to our colleagues at The Cambridge Group for their contributions to this book and their guidance throughout the process of writing it. Special thanks to our very talented principal team at The Cambridge Group, including Jim Eckels, Chris Fosdick, Don Johnson, Tim Joyce, and Peter Killian. Thank you for the energy and insight you have brought to our client work and to collaborating with us to continually improve the approaches and intellectual capital we leverage in order to help our clients drive growth.
Special thanks to Tim Joyce for contributing to writing the Facebook “Brand Economics” case. The case is based on the work that Tim, Jim Eckels, and others from The Cambridge Group have conducted with the team at Facebook. We also want to thank Zach Phillips, a consultant at The Cambridge Group, who helped edit the initial manuscript of the book. We recognize the contributions of our former colleague at The Cambridge Group and current data science collaborator Alex Moore, who assisted us with editing the content in the book. Zach and Alex added significant value by continually challenging us to clarify the concepts in the book, simplify language whenever possible, and avoid consulting jargon.
It would be impossible for us to thank Rick Kash adequately. It would also be impossible to fully describe the incredible impact Rick has had on each of us and all of us at The Cambridge Group. Rick, who founded our firm and is the former vice chairman of Nielsen, has been a colleague, a mentor, and a friend to each of us over the past two decades. His absolute passion for helping clients, his insights into customer demand and how companies can win, his creative problem solving, and his boundless energy continue to be an inspiration to all of us. Rick's insights, coaching, and example helped shape much of the thinking behind this book.
When he retired a few years ago, our team learned how truly irreplaceable Dr. Kevin Bowen, our former senior principal, actually is. Kevin created, helped create, or influenced many of the approaches described in this book over his thirty-year career with The Cambridge Group. We miss Kevin's insights, guidance, and camaraderie enormously.
We would also like to acknowledge our many Nielsen colleagues, including Mitch Barns, Steve Hasker, John Lewis, Chris Morley, Karen Fichuk, Susan Dunn, Pat Dodd, and the many others across Nielsen who have collaborated with us to help our many mutual clients succeed. Thank you for your partnership over the past eight years. Having the tremendous advantage of working with the global Nielsen team has enriched every aspect of our work with clients.
We would be remiss if we did not thank our former colleagues, Gloria Cox, Eddie Yoon, Louise Keeley, and Taddy Hall. For many years we had the benefit of their outstanding contributions, partnership, and friendship. Each of them made our firm stronger and better able to help clients achieve their profitable growth goals.
None of this would have been possible without the clients across industries, who have partnered with us to drive profitable growth. Thank you for trusting us to help solve your most difficult growth issues. It has been a privilege to work with these amazing client teams across industries and around the world.
ABOUT THE AUTHORS
Jason Green is a managing director with Alvarez & Marsal and has almost 30 years of consulting experience. He is the former CEO of The Cambridge Group and was a principal with the firm for over 20 years. Jason has worked with senior management teams at companies across industries and global markets to create and sustain profitable growth in their businesses. Prior to joining The Cambridge Group, Jason was with McKinsey & Company. He holds an undergraduate degree from Yale University and an MBA from the Kellogg School at Northwestern University.
Mark Henneman has delivered profitable growth for more than two decades as a senior partner with The Cambridge Group, a principal with Booz Allen Hamilton (now Strategy &), and an executive with Motorola, Inc. Mark is the architect of the Demand Business System and collaborates with executive teams to unlock new sources of growth by aligning business activities with the most profitable demand in the marketplace. Mark holds a BA & MA in economics from Northwestern University and an MBA from Dartmouth College.
Dimitar Antov (Chicago, IL; www.thecambridgegroup.com) is a current Director and former Principal at The Cambridge Group and previously led IP development at their Economic Center of Excellence. He is also the Managing Director at Straight Forward Concepts, a consultancy specializing in sales and marketing strategy activation. In this role, he leads teams that heavily utilize quantitative analysis, machine learning, predictive modeling, CRM database scoring, BI reporting, and data visualization; he also speaks at conferences covering state-of-the-art techniques in data mining and consumer research. Dimitar holds a PhD in Economics from Northwestern University.
SECTION IWhy Greater Precision
CHAPTER 1The Growth Challenge
The Big Ideas
Profitable, organic revenue growth is harder than ever to achieve due to economic conditions, demographic shifts, changing consumer demand, and disruptive technologies among other drivers.
Despite this dynamic, profitable, organic growth remains critical to the success of every business.
Many of the traditional approaches for driving growth are not as successful as they once were.
A new, more precise business model built on actionable insights into consumer demand and powered by emerging “Big Data” capabilities is a proven approach to achieving profitable growth.
“Net, Net
Economic Growth Slowing +
Margins for Error Declining =
Easy Growth Behind Us”
—Mary Meeker, Kleiner, Perkens, Caufield, Byer1
Few quotes sum up the current challenges facing businesses around the world better than this insight from Mary Meeker's annual “Internet Trends Report” from 2016: Perhaps growth was never easy to achieve, but clearly it will only get harder going forward. All of which makes the ability to successfully achieve profitable, organic revenue growth an even greater competitive advantage going forward. But how do managers get from the realities Mary Meeker points out to the systematic growth they need? Answering that question in detail is the purpose of this book: To share the approaches, frameworks, and analyses needed to identify and realize growth opportunities with greater precision, regardless of function or industry and to do so with solutions that range from simple “back of the envelope” exercises to those that use sophisticated Big Data analytics.
Precision That Pays
Ultimately, achieving profitable growth in a rapidly changing environment requires a more precise business system, complete with actionable insights into customer demand that leverage Big Data capabilities as much as possible. Building a more precise, demand-based business system has helped our clients, across industries and around the world, to attain new levels of growth after years of flat or declining sales, despite challenging market conditions, a changing competitive set, and disruptive new technologies.
In our experience, “precision that pays” starts with new insights into a firm's most valuable customers. Not just who they are and what they buy, but how they think about a category, a firm's offers, the brand, and the competition. Those insights are translated into more precise ways of reaching high-value customers and consumers in their preferred purchase locations and in the forms of media with which they are most engaged through a more compelling message and ultimately with offers that are more closely tailored to their demands. In short, the model we are describing starts by anticipating the demands of your most attractive customers, aligning offers and all business functions to serve those demands, and continually improving every aspect of the business by using a “test and learn” approach to monitor results and adapt as needed. This structure depends upon Big Data, or the growing sets of data that are now available, and analytics, by which we mean the tools for analyzing and making sense of those data. The dynamic growth in available information about consumers, in addition to increased sophistication in the tools and techniques used in synthesizing those data, are essential components in this framework. An overview of the approach and the questions addressed at each step could appear as shown in Figures 1.1 and 1.2.
Figure 1.1 Optimized business system insights and aligned activation.
Figure 1.2 The optimized approach to growth goes beyond traditional approaches while leveraging Big Data capabilities.
Precision, in the context of this discussion, has two distinct meanings. One important aspect of precision is assessing how accurately you understand customer demand for your products. A good gauge for determining if you have the insights you need to build from is to ask yourself and your team a question that the founder of our firm, Rick Kash, often asks our clients: “What do you know about the demand of your most profitable customers that your competitors don't know?” Many business leaders take pause at this deceptively simple question in part because they are not exactly certain who their most profitable customers are or how best to describe them. Beyond that, they may have only a rudimentary knowledge of their customers' most important needs and the rational, emotional, and social reasons that really drive their purchase decisions.
The ultimate litmus test is to identify those insights that are truly proprietary to your business. These are the insights that create potentially significant advantages because they are not known to your competitors, or at the very least, your competitors are not acting on them. It is the type of insight we uncovered in our work with Allstate Insurance that led Allstate to be the first to offer “Accident Forgiveness” and “Deductible Rewards®” for good drivers.2
Prior to introducing the Accident Forgiveness and the Deductible Rewards® features in a new offer Allstate called “Your Choice Auto Insurance,” Allstate and other insurance companies that sold through insurance agents were facing significant pressure from insurance companies like GEICO that sold policies directly over the phone or online. The “direct model” had much lower costs than the agent model, which allowed the direct players to charge less for “no-frills” insurance packages. GEICO, the leader among direct players, embodied this approach through its well-known ad slogan, “15 minutes could save you 15% or more on car insurance.”3 As the no-frills, direct insurance players continued to grow, the management team at Allstate was concerned that car insurance was quickly becoming a commodity market in which the lowest-cost provider would always win. Increasingly, the benefits of having a personal insurance agent located close by did not seem to justify the costs of the agent-based model. The team at Allstate wondered how it could break out of the commodity trap by successfully differentiating its offers while also making its agent network an advantage again.
The answer would come from two important, proprietary customer insights. First, Allstate discovered through quantitative research that lowest price was not the only consideration among all car insurance customers. In fact, about 40% of consumers were looking for high-quality coverage and the ability to protect their net worth in the event of a car accident.4 Second, Allstate came to realize how unfair these highly attractive, quality-focused insurance customers thought car insurance was. These customers did not understand why even the most responsible driver could be penalized for things that they could not possibly control, such as having his or her car damaged by another driver while parked in a parking lot. It also seemed incredibly unfair that consumers paid insurance premiums for coverage year after year, but if the consumer ever actually needed to use his or her insurance policy by filing a claim for an at-fault accident, those premiums would suddenly spike upward. What these valuable consumers really wanted was to make the current relationship with their insurer less one-sided and much more reciprocal. With these insights, Allstate created “Your Choice Auto Insurance” to satisfy those complaints of inequity that the company was hearing from its most valuable consumers.
Allstate's Accident Forgiveness feature was perfectly designed to appeal to the most responsible drivers in the market. This feature allowed an Allstate customer a limited number of at-fault accidents over time that could be “forgiven,” meaning the accident would not raise the driver's insurance premiums the way most other auto insurance policies would. The Accident Forgiveness offer was incredibly appealing to good drivers, for they were willing to pay a slight premium for protection against the risk of unexpected rate increases. Moreover, drivers who had frequent accidents over a relatively short period would quickly see their monthly premiums rise and would never realize the type of benefit their low-risk counterparts gained from Accident Forgiveness. Additionally, low-risk drivers were less likely to leave Allstate because they were earning Deductible Rewards® – or period-over-period rate decreases as a reward for a clean driving record – each year they went without an accident.
Allstate's “Your Choice Auto Insurance” became the most successful new auto insurance offer the company had ever introduced at that point.5 Soon after the new offers were introduced, The Wall Street Journal reported that Your Choice was having a significant impact on sales: “Anita Sally, an Allstate agent in Bartlett, Tenn., says her sales of Your Choice products are up 20% to 30% over sales of Allstate's standard product.”6 Ultimately, “Your Choice” was so successful in the car insurance market that the concept was also extended to home insurance.7
Beyond the precision behind proprietary insights like those that Allstate leveraged, we also use precision in the context of making the best resource allocation decisions in order to win in the market. Actionable demand insights have helped our clients optimize decisions about where to invest to generate attractive returns and where to avoid spending. Allstate saw this firsthand with the decision to target customers who were seeking higher quality rather than the lowest price, which facilitated the decision to design and launch successful “Your Choice Auto Insurance” offers to win with those customers rather than wasting resources chasing cost-conscious customers.
In many cases, these precise new insights are either identified through, or enabled by, the use of Big Data. This data-driven precision has generated actionable insights that have spurred countless clients to invest in exactly those products or services that are most valued by their key customers while avoiding the wasted spend from adding costly features that those same customers do not value. In addition, for products sold through retail stores, more precise insights into demand allow businesses to determine which stores have the highest potential for selling their products and which stores should be avoided. One approach for identifying the highest potential retail stores for a given product is to map all 117 million U.S. households8 to the stores where they shop using Nielsen data or other proprietary data sets. The level of precision possible can even determine exactly where within a specific store a given product should be sold and how it should be merchandised. A more refined understanding of demand can also be the catalyst for the development of an entirely new business model instead of simply adapting old models to fit new targets.
The guiding principle is to focus on what we call “precision that pays,” or proprietary customer insights that explain the drivers of customer preference and why they really choose the products and services they buy. The right level of precision helps guide the best possible resource allocation decisions while avoiding unnecessary waste. Ultimately, “precision that pays” can increase sales while lowering costs, as the case studies in this book will demonstrate.
A Challenging Growth Environment
We believe greater precision will be needed as the rapid, often dramatic changes taking place in today's business environment make the challenge of achieving profitable growth going forward more difficult than ever. Among the major drivers of these significant shifts are a slowing economy; globalization; demographic changes; digital disruption to traditional business models; other new technologies, such as 3D printing, nanotechnology, and robotics; evolving consumer trends; and changing competitive dynamics. Any one of these factors alone might pose challenges to an individual firm's growth prospects, but taken together, they create major barriers. As Mary Meeker points out, in a business environment with “margins for error declining,”9 success will require greater precision than ever before.
One of the most significant impediments to corporate growth is the stagnant economic environment that the United States and many other countries are experiencing. Unfortunately, the U.S. economic forecast continues to have bleak short-term prospects, with low growth coupled with increasing uncertainty. The Conference Board projected U.S. GDP growth of 2.2% in 2018,10 which is far below the historical average from 1948 to 2010 of 3.31%.11 Long-term projections forecast lower levels of GDP growth as a “new normal” for the U.S. According to the PricewaterhouseCoopers (PwC) report “The World in 2050,” published in 2015, average real GDP growth for the U.S. from 2014–2050 is projected to be only 2.4% annually.12
In many parts of the developed world, prospects for economic growth are even lower than the U.S. forecast. The same PwC report projects average real GDP growth per year for the European Union at 2.0% for the period from 2014–2050. Notably, key developed markets, including Germany and Japan, are expected to experience GDP growth rates of only 1.5% and 1.4%, respectively. GDP growth rates for both Germany and Japan will be pulled down, in part, by negative population growth rates of −0.4% and −0.5%, respectively, according to the PwC report.13
Meanwhile, the rapid growth experienced by many developing markets, especially China, has cooled over the past decade. Over the past 20 years (1996–2015), real global GDP growth averaged 3.8% per year according to the International Monetary Fund's “World Economic Report” from April 2016.14 During that same period, China experienced average GDP growth of over 9.4%, based on data from The World Bank.15 As recently as 2007, China had achieved annual real GDP growth of over 14%.16 However, even China is forecast to regress closer to the global mean with projected annual GDP growth of only 3.4% for 2014–2050, according to PwC.17 Meanwhile, global GDP growth for 2014–2050 is forecast to decline by almost 25% to about 3.0% annual growth .18
Generational Shifts in the U.S
One of the drivers of the low growth forecast for the U.S. is a major demographic shift.19 Consumer spending currently accounts for over two-thirds of the U.S. economy,20 which is an outcome of the economic growth seen in the U.S. post–World War II, along with the rapid population growth during that period that became commonly known as the “Baby Boom.”21 Throughout the Baby Boom, generally considered the period from 1946 to 1964, the U.S. population increased by an average of about 1.8 percent per year.22 In contrast, the U.S. population grew by only 0.7 percent from July 2015 to July of 2016, according to the U.S. Census.23 The last time that U.S. population growth rates this low were recorded was in 1937 as the U.S. suffered through the Great Depression.24
Starting in 2015, Baby Boomers were no longer the largest living age group in the U.S. Instead, the Millennial generation, which is considered by the U.S. Census to have been born between 1982 and 2000,25 surpassed the Boomers in terms of number of people.26 Looking forward to 2020, the U.S. Census Bureau predicts that there will be 81 million Millennials and about 71 million Boomers.27 As Millennials grow as a percentage of the total U.S. population, they will also grow in terms of purchasing power. Household spending attributed to Millennials is projected to eclipse the spending represented by Boomer households starting in 2018 or 2019.28 By 2020, Millennial households in the U.S. will spend over $1.8 trillion annually while Boomer households are expected to spend under $1.6 trillion per year.29 All of this evidence shows that, after this inflection point, the U.S. will transition from a Boomer-driven economy to one driven by Millennial spending.
Several interrelated economic and demographic factors will weigh on the U.S. economy during this transition. First, the U.S. middle class continues to shrink. From 1971 to 2015, adults in the U.S. middle class, defined as households with an annual income between $41,000 and $125,000, has dropped from 61% of adults to 50% of adults.30 At the same time, the two lowest U.S. income brackets have increased by 4 percentage points, from 25% to 29%, and the two highest U.S. income tiers have grown by 7 percentage points, from 14% to 21%. Given these trends, along with the fact that consumer spending represents about two-thirds of U.S. GDP, a vibrant, growing middle class and the millions of purchases that these consumers make every day are absolutely critical to driving GDP growth.31
Millennials are just entering what should be their peak earning and spending years. In the U.S., income and spending both tend to increase until age 34 before peaking from ages 35 to 54. Starting at age 55, income and spending begin to decline.32 The oldest Millennials are just turning 35, but the spending and economic growth this generation should be driving may be delayed as Millennials delay the many major life milestones, including marriage, starting a family, or buying a home, that often trigger significant spending.
One of the reasons Millennials may be delaying key life stages and the spending they typically trigger is the crushing amount of student debt they have accrued. In the span of just a few years, from 2005 to 2012, the average amount of student debt among Americans under 30 almost doubled from $13,340 to $24,897.33 By 2016, the average graduate had over $37,000 in student loans, and as a generation, Millennials are carrying the majority of the staggering $1.4 trillion in U.S. student loan debt.34 No wonder the wedding has to wait.
Marriage among Millennials does provide a case in point for how dramatic these generational changes have been. In the 1970s, 80 percent of Americans aged 30 or younger were married.35 Today, 80 percent of Americans aged 45 or younger are married because most Millennials have significantly delayed marriage versus prior generations. In fact, it is more common for Millennials aged 18 to 34 to live with their parents than to live with a spouse. Compare this to 1975, when the majority of 18- to 34-year-olds, fully 57% of them, lived with their spouse.36
The fact that Millennials have delayed leaving home and starting households of their own has slowed housing starts and dampened the housing sector, which is a major part of the U.S. economy as a whole. As officials from the Federal Reserve Bank of San Francisco reported, “The recovery in the housing sector has been even slower than for the overall economy. In particular, the pace of housing starts remains subdued by historical standards. This muted recovery can be traced in part to the slow pace of household formation, especially among young adults. In turn, the share of young adults living with parents has grown in recent years.”37
Whether or not Millennials will spend at the level of prior generations, as they hit the traditional peak earning and spending years, is an open question. What is not being questioned is the fact that Boomers, who are retiring in record numbers, will begin spending less.38 By 2060, the number of Americans aged 65 and older is expected to more than double, from about 46 million people today to over 98 million in 2060.39 According to Derek Thompson of The Atlantic, “Of the many significant forces shaping the U.S. economy – including globalization, automation, and housing supply – none is so inevitable and invisible as the sheer march of time for today's adults. In the 1950s, at the height of the U.S. manufacturing supremacy, less than 10 percent of the country was older than 65. That share will double to 20 percent by 2050.”40
The Age of Disruption
In addition to an increasingly difficult growth environment, many established companies and industries are facing new types of competitors, often from nontraditional players, as industry disruption becomes the norm. Online models and technology have been broadly leveraged to disrupt major industries, including retailing, media, financial services, and automotive, among others.
In the retail industry, Amazon and other online retailers are changing the face of the nearly $5 trillion U.S. retail industry.41 Long gone are the days of the general store and its motto, “If we don't have it, you don't need it.” The virtually unlimited selection, incredible convenience, and increasingly rapid product delivery of online shopping has put pressure on traditional “brick and mortar” stores of all types, including department stores, specialty retailers, and increasingly, grocery stores. Amazon's acquisition of Whole Foods in June of 2017 certainly seems to underscore how serious online retailers are about growing in grocery.42
Online retail sales have more than doubled from 2010 to 2016, going from $153 billion to $387 billion or from about 4% of total sales to 8% of total retail sales.43, 44 More importantly, the percent of consumers who researched their purchase online but then bought it in a physical store has jumped from 24% in 2010 to 58% in 2016.45 While retail sales as a whole increased at a rate of about 3.4% per year from 2010 to 2016, the portion of sales that was either digitally influenced or completed online grew by 17% per year. At the same time, traditional store-based retail sales with no online research or any type of online involvement declined by over $1 trillion from 2010 to 2016.46
