AI-Driven Value Management E-Book

Craig LeGrande

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 339

Veröffentlichungsjahr: 2024

Beschreibung

Unlock the power of generative AI to transform your enterprise B2B sales and marketing strategies

In AI-Driven Value Management: How AI Can Help Bridge the Gap Across the Enterprise to Achieve Customer Success, authors Craig LeGrande and Venky Lakshminarayanan reveal how artificial intelligence can revolutionize B2B value management. This book lays out a first-ever strategic blueprint for cost-effectively scaling value management programs. Value management is the art and science of orchestrating all the business functions in your company to envision and create exceptional value for your customers – and in the process enhance your pipeline, revenue and renewals. It's designed for business leaders who are looking to harness AI to gain a competitive edge and boost pipeline, revenue and expansions, effectively solving the problem of expensive scaling in business-to-business sales and marketing.

Dive into the core of AI-empowered Value Management (AI-VM) through a detailed exploration of a comprehensive AI-driven value management blueprint. This guide uses real-world success stories and cutting edge AI technology solutions to illustrate how businesses can combine people, processes, and technology to execute value management at scale, enhancing efficiency and effectiveness.

In this book, you'll:

• Learn from the successes and strategies of leading companies like Salesforce, ServiceNow, and Amazon Web Services
• Discover the AI-VM Blueprint, an integrated framework that lays out strategic, operational, and technological guidelines for deploying AI-driven value management
• Equip your team with actionable insights and tools to innovate and implement AI in your sales, marketing and customer success strategies effectively

AI-Driven Value Management is essential reading for B2B professionals eager to leverage AI for business growth. If you are a business leader, manager, or professional aiming to integrate AI into your value management practices, this book will provide you with the knowledge and tools you need.

Leseprobe

Table of Contents

Cover

Table of Contents

Title Page

Foreword

Introduction

What's Inside

Who Should Read This Book

CHAPTER 1: Introduction to AI-Driven Value Management

A Brief History of Value Management

Modern Corporate Governance—Raising the Bar on Capital Investments

Your Guide to Achieving 8X Company Revenue Outcomes

Notes

CHAPTER 2: The Current State of Value Management

Understanding the Fundamentals of Business Value

Understanding the Customer Life Cycle

Notes

CHAPTER 3: Building the Future Value Management Program

The Game Changer: Artificial Intelligence

Introducing a Blueprint for AI-Value Management

CHAPTER 4: AI-Driven Value Management for Marketing

Empowering B2B Marketing with AI-Enabled Value Management

The Current State of B2B Marketing

The Current State of Value Management in Marketing

What's Next: Value Management Marketing Powered by AI

Notes

CHAPTER 5: AI-Driven Value Management for Sales

Getting Started with Value Management for Sales in Start-Ups and Small Companies

From Art to Craft to Practice: How Value Management Programs Support Mature Sales Organizations

What's Next: AI-Driven Value Management for Sales

Note

CHAPTER 6: AI for Sales Operations

Understanding the Responsibilities of the Sales Operations Team

Adding AI to Sales Operations to Quickly Scale Value Management Programs

Making the Business Case for Value Engineering Programs: The ROI of ROI Programs

CHAPTER 7: Empowering Your Sales Partners with AI-Driven Value Management

De-risking Partner Relationships

AI-Enabled Partner-Based Value Management (AI-PBVM)

Value Management for Three Types of Ecosystem Partners

Conclusion

Notes

CHAPTER 8: AI-Driven Value Management for Customer Success

What Is Customer Success and Why You Should Care?

Understanding the Customer Success Workflow

Better Together: Combining Customer Success and Value Management

The Challenge of Integrating Value Management and Customer Success

Touchpoints: Where Value Management Meets Customer Success

AI: Changing the Customer Success Game

The Future of AI-Powered Customer Success

Notes

CHAPTER 9: One Value Motion: The Power of Unified Value Management

The Journey to a Unified Enterprise

The One Value Motion Playbook

The AI Value Assistant: Customer Insights at Your Fingertips

Building Your AI Value Assistant

Note

CHAPTER 10: Delivering Business Outcomes with AI-Powered Value Management

Boosting Revenue Throughout the Customer Life Cycle

How AI-VM Can Drive Revenue: A 10-Year Forecast

Capturing More Value from Your Partner Ecosystem

Driving Cost and Time Savings

CHAPTER 11: A Final Note to the Reader

Glossary

Acknowledgments

About the Authors

Index

Copyright

End User License Agreement

List of Tables

Chapter 2

Table 2.1: Features vs. Value: Two Kinds of Messaging

Table 2.2: Helpful hints for building a business case

Table 2.3: The business value of solar

Chapter 4

Table 4.1: GenAI product marketing assistant use cases

Table 4.2: GenAI demand-generation assistant targeting use cases

Table 4.3: Revenue marketing assistant hook use cases

Table 4.4: Value intelligence AI event use cases

Table 4.5: Individualized participant experiences AI use cases

Table 4.6: Event/trade show booth AI use cases

Table 4.7: Corporate marketing assistant event use cases

Chapter 5

Table 5.1: Business case effort decomposition

Table 5.2: Business case responsibilities

Table 5.3: Putting together the pieces of a business case

Table 5.4: AI capabilities for sales use cases

Table 5.5: AI value consultant digital assistant

Table 5.6: AI capabilities for value management account activities

Table 5.7: AI process automation for business cases

Table 5.8: Key use cases for AI digital assistants

Table 5.9: AI capabilities for value management training content

Chapter 6

Table 6.1: AI sales operations use cases

Table 6.2: Investment Costs of Value Programs

Chapter 7

Table 7.1: Top-tier AI-PBVM use cases

Table 7.2: Mid-tier AI-PBVM use cases

Table 7.3: Lower-tier AI-PBVM use cases

Table 7.4: System implementers (SIs) value management digital tools

Table 7.5: VAR AI digital assistant use cases

Table 7.6: Technology alliance partner AI digital assistant use cases

Chapter 8

Table 8.1: Upskilling CSMs: The starting point for creating effective busine...

Table 8.2: Impact of value management and AI on KPIs

Chapter 9

Table 9.1: Value management programs across maturity stages

Table 9.2: Business capability framework example

Table 9.3: Comprehensive AI business use cases

List of Illustrations

Chapter 1

Figure 1.1: Subscription mania: Estimated growth of digital subscription eco...

Figure 1.2: The value management life cycle

Chapter 2

Figure 2.1: The value management life cycle

Figure 2.2: The Value Opportunity stage

Figure 2.3: The Value Target stage

Figure 2.4: The Value Realization stage

Figure 2.5: The Value Expansion stage

Chapter 3

Figure 3.1: AI's rapidly evolving landscape

Chapter 4

Figure 4.1: B2B marketing organizational structure

Figure 4.2: McKinsey's view of managing marketing partnerships (internal and...

Figure 4.3: The four phases of product marketing

Figure 4.4: Example of a value tree from a past client's product positioning...

Figure 4.5: The future of product marketing with AI-driven value management...

Figure 4.6: Future state ABM KPIs

Figure 4.7: Next-generation account-based revenue strategy

Figure 4.8: Demand-gen programs powered by AI

Chapter 5

Figure 5.1: Sales’ value management responsibilities across the customer lif...

Figure 5.2: Value Management Starter Kit & Maturity Assessment

Figure 5.3: Business case skills by role and distribution

Figure 5.4: Business value teams—current state of enterprise deployment

Figure 5.5: Quantum leap in ability to scale value management

Figure 5.6: AI-VM enabled value management for sales

Chapter 6

Figure 6.1: Sales operations and business value operations responsibilities...

Chapter 7

Figure 7.1: Enterprise B2B company: partner ecosystem example

Figure 7.2: AI-enabled partner-based value management (AI-PBVM)

Figure 7.3: Partner channel categories

Chapter 8

Figure 8.1: Maximizing customer lifetime value through customer success and ...

Figure 8.2: Customer success and value management organizational challenges...

Chapter 9

Figure 9.1: Functional silos prevent a unified value management experience a...

Figure 9.2: One Value Motion Playbook

Figure 9.3: “One Value Motion” team charter example

Figure 9.4: One Value Motion journey map

Chapter 10

Figure 10.1: AI-VM-based customer retention impact

Figure 10.2: AI-VM 10-year customer base impact

Figure 10.3: AI-VM channel sales revenue impact sensitivity

Figure 10.4: Value engineering activities: percentage of capacity legacy vs....

Figure 10.5: SaaS company AI-VM value engineering team productivity savings...

Guide

Cover

Title Page

Foreword

Introduction

Table of Contents

Begin Reading

Glossary

Acknowledgments

About the Authors

Index

Copyright

End User License Agreement

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AI-Driven Value Management

How AI Can Help Bridge the Gap Across the Enterprise to Achieve Customer Success

Craig LeGrande

Venky Lakshminarayanan

Foreword

Technology is advancing faster than I have ever seen in my 20+ years in technology. And although AI may seem like a new thing, technology leaders like IBM have been using it for a while. Computer scientist John McCarthy coined the phrase “artificial intelligence” in the 1950s. After that, in the 1960s IBM's CEO Thomas Watson, Jr.'s work centered on automating tasks, one of the hallmarks of today's AI. The 1970s were defined by statistical models and probability; while not exactly AI, elements certainly feed into them. Then in 1996, during the ultimate battle of human versus machine, an IBM computer called Deep Blue beat World Champion Garry Kasparov in chess. When I joined IBM in 1999, work was being done on rules-based engines and analytics, a precursor to IBM Watson, an AI computer that beat two Jeopardy champions in 2011. And since then, consistent progress every month and every year has brought AI to the forefront—leading IBM to introduce watsonx in 2023.

One thing is for certain: AI may not replace managers, but the managers who use AI will replace the managers who do not. It is the sure path to productivity, which is the sure path to growth. As I meet with clients daily, I have found a pretty successful formula for AI adoption to drive value: Foundation Models + Data + Governance + Use Cases.

Having model choice is really important. Sure, large language models have caught everybody's attention because of their direct consumer application. But for business, different models will be better at some tasks than they are at other tasks. The best model will depend on the industry, domain, use case, and size of model, meaning most will use many smaller large language models versus one larger model. Models pretrained on domain-specific data produce better results for businesses than general-purpose models. And with the right governance, companies can be assured that its workflows are compliant with ever-changing government regulations and free of bias. With this AI-driven value management system in place, business outcomes are achievable in record time.

Getting to the right outcomes starts with alignment of the leadership team on strategic intent. Having a long career leading large, high-powered sales teams, my experience tells me that the gold standard is building an aligned sales organization that can articulate the business value of product portfolios, first and foremost. Scaling this capability across products, regions, industries, and sales organizations can be challenging. To do so, AI will be a game changer as companies deploy AI to transform their internal functions, including go-to-market. Early wins are being seen as companies rely on AI-powered automation to optimize spend, improve operations, and drive greater financial returns.

In AI-Driven Value Management, you have a pragmatic handbook for understanding the magnitude of AI's potential to transform the way companies market, sell, and drive client success. Both Craig and Venkat have had a front row seat for this change, and hence they can be your tour guides in what is to come.

The world's best days are yet to come if we allow technology to flourish responsibly.

—Rob Thomas

Rob Thomas is Senior Vice President Software and Chief Commercial Officer, IBM. He leads IBM's software business, including product management and design, product development, and business development. In addition, Rob has global responsibility for IBM revenue and profit, including worldwide sales, strategic partnerships, and ecosystem.

In his over 20 years at IBM, Rob has held roles in IBM Consulting, IBM Microelectronics, and IBM Software. In 2007, Rob joined IBM's software business, focused on data and analytics. He held a variety of roles, including product engineering and business development, leading IBM's transition from databases to delivering broader analytical capabilities, investing in open source, and eventually artificial intelligence. Rob has overseen numerous acquisitions by the firm, representing over $12 billion in transaction value.

Introduction

This book is the culmination of 50 years of the authors' combined professional experience working in diverse roles as buyers, sellers, and builders of information technology systems. Over that period, Craig LeGrande and Venky Lakshminarayanan have seen big wins, big mistakes, and big lessons learned in the world of value management.

As a management consultant at Accenture and as a business value consultant at Cisco Systems, Craig mastered the art and science of showing the real impact of technology to executives. Selling based on hype or vague assumptions, he quickly discovered, was the fastest way to lose their interest. Says Craig: “Clients kept nagging me with questions like, ‘How will your solution actually drive that kind of impact?’ and ‘Can my company really achieve those results?’”

Often, Craig was surprised by the lack of solid evidence to back up the claims of technology companies and consultants. “Many vendors exaggerated the benefits to the point that CFOs and CIOs would laugh at the numbers,” Craig says. “It became clear to me that the only way to sell effectively was to build trust, stick to conservative estimates of business impact, and share real-life success stories.”

When he left Cisco, Craig's first client was Oracle, who at the time was going head-to-head with software giant SAP in the enterprise resource planning (ERP) space. The company's CEO, Larry Ellison, had encouraged his sales team to develop a library of key performance indicators (KPIs) to definitively prove the benefit of Oracle's products. Partnering with Oracle to develop that messaging and support their sales teams was the launching pad for Craig's next career move—founding Mainstay with the mission of helping companies quantify and communicate the true business value of technology.

Venky Lakshminarayanan followed a similar career path. A couple decades ago, he was fortunate enough to find himself at the intersection of business and technology in Silicon Valley, which had become the epicenter of massive technology-led business transformations. He cut his teeth at PwC, working on large, multiyear projects involving ERP, supply chain, and customer relationship management (CRM) software solutions.

Back then, enterprise technology was all about selling product features—purely functional capabilities that we often referred to as “speeds and feeds.” “It seemed like good customer testimonials were the only way to demonstrate business value,” Venky says. “As I shifted into sales roles, I often wondered what that single factor is that could help us consistently win deals.”

While Venky and his colleagues won a lot of deals, they also lost some. After one promising sale escaped their grasp, a CIO told him, “Your solution was probably the best, but we couldn't articulate its business value to our CFO.” That was Venky's lightbulb moment. “I realized then that business value is the real currency—the driving force—of the tech industry. That's what led me to join Mainstay,” he recalls.

Although the practice of value management was by and large a novelty when he arrived at Mainstay in 2010, the boutique consulting company was already breaking new ground in value management, evolving it into a science with predictable business outcomes. “I had the chance to work with global technology providers and their customers to understand and articulate the ROI of their investments,” he says.

Later, while at ServiceNow—a Fortune 500 company that's been named one of the world's most innovative companies—Venky worked with an incredible team to build a companywide value management program that boosted pipeline, revenue, renewals, and customer expansion. Now, as chief revenue officer and president at Cron AI, a pioneer in autonomous technology, he is once again pushing the boundaries of what's possible with a value-based selling approach. “Quantifying and communicating value is still at the heart of everything we do,” he says. “I believe value management is essential for every customer-facing function.”

What's Inside

This book unveils the transformative role artificial intelligence can play in helping enterprise B2B companies build a thriving value management practice. It tackles the challenge of how to scale business value activities across all customer-facing business functions—minus the exorbitant costs—and equips business leaders with AI-integrated strategies to secure a competitive edge and generate significant revenue growth.

We show how AI can help businesses bridge the gap between its sales, marketing, and customer success teams, empowering them to communicate value in an integrated fashion, driving consistency and uniformity throughout the customer life cycle. To help companies implement this new value management strategy, this book provides a playbook for what this future should look like, how to get there, and its impact on business-to-business companies.

AI-Driven Value Management is your guide to designing a unified marketing and sales program across all customer-facing business functions. Inside, you will find a clear and actionable blueprint for achieving scalable, impactful business outcomes through advanced AI-powered value management strategies.

We argue that companies that adopt an AI-driven value management (AI-VM) approach can finally achieve the holy grail in customer relationships—a single, unified value management framework that we call One Value Motion. These companies will be able to articulate their solutions' customer outcomes and show customer success throughout their life cycle clearly and with remarkable precision.

We believe the use of AI-Driven Value Management strategies and tools will deliver transformational revenue growth for B2B enterprises across industries. In fact, we have already shown how companies with strong value management programs, augmented by AI, can double sales leads, double win rates, and reduce customer churn by half—leading to an overall 8X overall revenue improvement.

When companies combine the power of AI with modern value management tools and technologies, current barriers to revenue and customer growth, such as cost, resource constraints, and operational friction, can be eliminated—making these results easier and faster to achieve. We are confident that the AI-VM strategies, use cases, and real-world stories in this book will provide leaders with the tools they need to successfully harness AI-driven value management in their industries.

Who Should Read This Book

Whether you're a business leader, seasoned professional, or a curious business and technology enthusiast, you are sure to benefit from this exploration into the future of value management and artificial intelligence.

This book will be a valuable resource for everybody from C-suite executives to sales, marketing, and customer success leaders to day-to-day practitioners of value management. It will serve as a useful handbook for any customer-facing executive who sells technology solutions to businesses. In fact, you'll find useful stories, lessons, and advice from many of these leaders in the pages ahead.

CHAPTER 1Introduction to AI-Driven Value Management

The rise of value management as an established business practice has been decades in the making. Yet it remains an evolving and dynamic field, as our businesses continue to modernize and digitize in surprising new directions.

As a result, long standing dogmas for selling products and services to business customers are being shattered in the process.

In this chapter, we'll briefly explore how value management came to be as a successful enterprise selling strategy and then more recently as a driver of marketing campaigns, customer loyalty programs, and partner ecosystems. We'll look at how more companies today are demanding better returns from their business investments, and we'll examine the tectonic shift in customer relationships that is forcing sellers in nearly every industry to deliver tangible and recurring business value to the buyers of their products.

Finally, we'll introduce the game-changer: Artificial intelligence (AI) in all its forms and its potential for bringing the selling power of value management to more parts of the business, at lower cost, and at unprecedented speed and scale. We conclude with this book's bold thesis: That combining the power of AI with a state-of-the-art value management approach can empower businesses to realize 8X revenue outcomes.

A Brief History of Value Management

In the late 1940s, managers at the emerging industrial powerhouse General Electric (GE) were searching for ways to maximize business value by optimizing how the company deployed its scarce raw materials and human resources.1 The methods developed by GE were refined into a formal methodology and the term value management was born. Since then, value management has steadily grown in popularity, becoming a highly useful sales technique for many companies seeking to sell complex, high-cost products and services to customers in a wide range of industries.

In recent decades, the practice has continued to attract followers among business-to-business (B2B) companies, especially in the high-technology arena. We've seen the emergence of this trend firsthand working for large systems implementers and high-tech companies since the late 1990s. Without realizing it, we found ourselves on the front lines of the tech wars, helping our clients take advantage of the latest value management methods. By then, information technology (IT) had risen to the status of strategic investment for more and more enterprises, and the chief information officer (CIO)—finally—had gained a seat at the executive table. With large sums at stake, corporate leaders began asking an obvious question: Exactly how much business value are we going to get from these massive technology investments?

To keep their customers happy and their sales surging, technology vendors were determined to answer that question. Many chose to hire teams of management consultants (sometimes referred to as business value consultants or business value engineers) to get a monetary handle on the business value of their products and thus gain access to executive buy-in. These teams specialized in translating technical specifications and product features into the language of business outcomes. The customer value assessments they produced—commonly called business cases—soon became an integral part of the sales cycle for the company's most valuable prospects. The consultants often worked closely with sales leadership and the executive team to help customers justify large-scale technology investments and support their customers' capital investment process.

By the 2010s, the practice of value management had become a widely accepted sales overlay, a team of specialists supporting the sales team. The success of these teams in closing the largest and most strategic deals started attracting new converts in product marketing and in customer success organizations. These business functions were interested in building value messaging “upstream,” where it could inform the customers early in their decision-making process, as well as “downstream,” where it could drive subscription renewals, broaden the customer life cycle, and boost revenue streams.

However, in recent years, many value management initiatives have hit a budget wall. Stubbornly high costs—especially the expense of using highly paid business value consultants—have been a barrier to growing value management programs or expanding into other functions. Fragmented organizational structures—and their associated politics—can also make it difficult to expand these initiatives to other functions, such as marketing, professional services, and customer success. What's more, although more companies have access to robust digital tools to streamline customer research and analyses, they are often deployed in piecemeal fashion and fall short of reaching the overall goals of these platforms. Taken together, these costs and inefficiencies can create structural impediments to scaling value management programs across the enterprise and enabling companies to capture the potential of end-to-end value management.

Then, seemingly overnight, the world changed. The arrival of generative artificial intelligence (GenAI) in the form of ChatGPT and a plethora of other AI technologies and apps sent shockwaves through the digital economy and sparked a full-fledged cultural phenomenon. There appears to be no limit to AI's potential to radically disrupt the way companies do business, from designing and manufacturing products exponentially faster to providing customer service that is uncannily human.

Companies seeking to build an enterprise value management program will be prime beneficiaries of the AI revolution, adding incredible speed, automation, and economies of scale to what are currently highly manual, error-prone, and costly processes. To introduce the opportunity of AI, let's look back at how far we've come with this technology.

The Evolution of AI

As early as the 1950s, rule-based or classical AI was developed for symbolic manipulation and logic to mimic human decision-making. The 1980s saw the advent of neural networks, which introduced the concept of learning from data by simulating the interconnectedness of neurons in the human brain. And since the early 2000s, with the availability of computing power at lower and lower costs, we've seen rapid strides in predictive AI or machine learning. This has enabled us to build algorithms that learn from data to make predictions or decisions without being explicitly programmed.

Though it has been around for more than a decade, GenAI burst into the limelight in 2023. GenAI can generate new content such as images, text, or music, often indistinguishable from human-created content. Another emerging area of interest is agentic AI, also called autonomous AI, which can act independently, making decisions and taking actions in complex environments without human intervention. The AI capability that can create scale for value management today is a combination of predictive AI and GenAI.

For now, GenAI is in its infancy. But we already can envision how and what this new technology can do to generate a new wave of opportunity for value management. As companies struggle to extend their value management programs to the whole enterprise, GenAI offers a practical solution that any B2B company, following a set of proven strategies and techniques, can master.

This book provides that blueprint. It begins with examples of currently successful value management programs and shows how GenAI solutions can take these programs further, empowering more parts of the business and unlocking significant new revenue opportunities. This book also draws a road map highlighting key phases of an ideal deployment that ensures successful business outcomes and minimizes common traps that we've seen delay or stall previous value management initiatives.

HOW GENERATIVE AI POWERS VALUE MANAGEMENT

Wikipedia defines GenAI as “artificial intelligence capable of generating text, images, videos, or other data using generative models, often in response to natural language prompts.” GenAI's role in OpenAI's blockbuster ChatGPT is just one example of how this technology is redefining society. It is now finding its role in a myriad of business applications, including marketing, sales, and more recently, value management programs. For example, if integrated well into a company's existing sales workflow, GenAI capabilities can help a B2B seller to:

Automate email responses and actions

Summarize documents, text, and videos

Document question and answer (Q&A)

Analyze and aggregate data

Visualize data (e.g., charts, infographics)

Convert text to speech

Inform/provide Q&A for images and charts

Convert text to images

Convert text to collaborative workflows

Convert text to code actions

Analyze sentiment

Translate communications

Review and summarize documents

These AI capabilities and thousands more can be customized to match the unique workflows of different industries and integrated into existing sales operations. Its potential for automating and accelerating critical tasks can help reduce costs and enable organizations to successfully scale value management programs throughout the enterprise.

WHAT IS VALUE MANAGEMENT?

Simply put, value management is the art and science of orchestrating the business functions within your enterprise to maximize business value for your customers. It encompasses a range of practices aimed at identifying, creating, and sustaining value throughout all aspects of the business. True value management requires all parts of the enterprise to come together around a common vision and purpose. Consequently, a unified value management program is the best way for B2B providers to grow their revenue and maximize customer loyalty.

Modern Corporate Governance—Raising the Bar on Capital Investments

Over the past few decades, corporate boards have tightened the reins on how their companies are operated and what investments they make. As a result, the practice of corporate governance, especially for large public institutions, has matured significantly. Boards of directors and top executives have implemented robust and highly structured investment committees and policies to ensure maximum return on invested capital. In many ways, these modern investment-management structures have served to “pull” B2B companies toward adopting value management programs. These large enterprises, in turn, have encouraged their vendors to adopt value management programs to help them build return on investment (ROI) business cases and provide other analyses needed to meet their investment requirements.

The authors witnessed this firsthand, living and working at the intersection of technology and business for the last three decades. Over this time, we've seen the magnitude of technology investments skyrocket in every industry, becoming the single largest capital investment for most companies.

To better manage their budding portfolio of tech investments, company executives raised the bar on what projects could get funding. They started asking top managers to show the actual return on investment for new projects before greenlighting them. Many established a program management office (PMO) to identify, assess, and manage large IT investment opportunities as part of their overall capital investment planning process. As the Project Management Institute (PMI)® reports,2 this “evolved PMO” was a “full-service PMO that supports and aligns strategic, tactical, and operational considerations.” Investments codified and prioritized by this management body were then reviewed and approved by the board of directors.

The growing adoption of the new and improved PMO changed how many large companies procured new technologies and spurred the establishment of more rigorous investment standards. This had serious consequences for technology vendors: it meant that in order to close deals, they would have to provide their would-be customers with clear economic justification for their products and services.

Rethinking Customer Relationships

Selling to customers became even more challenging as more B2B companies began transitioning from product-based companies to software as a service (SaaS) companies. In simple terms, SaaS companies sell subscriptions to their software, with users paying a recurring fee; product companies require a one-time payment for indefinite use of their products.

Realizing the profound significance of this shift, we wrote Competing for Customers (Pearson FT Press, 2016). It was clear to us that as the subscription economy became mainstream, sellers would need to connect with their customers at a deeper level and forge more enduring relationships. In other words, they would be forced to become customer-first companies.

This meant SaaS companies would need to rethink how they engaged customers—at every level. Instead of being rigidly focused on closing deals, they would need to think more holistically by tracking and engaging customers throughout their life cycle—an extended relationship that spans initial awareness of a company's brand all the way to contract renewals.

It's been proven that taking a customer-first approach pays off. Companies that adopted this model delivered 35 percent better stock performance compared to the S&P 500 over an 8-year period, and nearly 80 percent better stock performance compared to late adopters of products.3

Since our book was published, the digital subscription economy has grown even faster than imagined. In fact, Swiss banking giant UBS predicts the subscription economy revenue will hit $1.5 trillion by 2025, and Statista reports that key market segments such as cloud computing are expected to double in size from 2020 to 2025, reaching $536 billion (see Figure 1.1).4 As we detailed in Competing for Customers, customers in the subscription-based economy command greater leverage over their vendors, since switching costs are relatively low and sellers need to make good on their promises to retain their business.

The Road to Customer First

However, what we failed to appreciate at the time was just how difficult it would be for companies to transform themselves into a customer-first company. The book explored different ways to help companies bridge the gap—for example, by launching a new business function known as a customer success organization. This new corporate function would focus on ensuring that customers realized—in measurable ways—the business benefits promised by the seller. Since the book was published, thousands of companies have stood up similar organizations and successfully reduced customer churn as a consequence.

Figure 1.1: Subscription mania: Estimated growth of digital subscription economy worldwide

Customer success teams were off to a good start in helping realize value for their customers, but mostly their scope was too narrow, focusing mainly on reducing day-to-day technical and operational issues. Too often, these teams neglected to address the bigger task of value realization—that is, helping customers to track and quantify the achievement of their overarching business goals, such as greater sales, market share, and brand awareness.

Value management has never been more important in a market where customers devote an increasing share of their budgets to enterprise technologies, where buying cycles are longer and more complex, and where subscription-based business models are requiring vendors and customers to renew their original sales agreements every two or three years.

VM PRO TIP

To ensure customer success, and close more deals and renewals, technology sellers need to provide clear line of sight into how their technology solutions will deliver measurable business value for their customers.

The growing popularity of value management is not just a technology-industry phenomenon. Virtually all large enterprise investment decisions are being put through the same prioritization gauntlet. Other industries impacted include manufacturing, financial services, life sciences, automotive, utilities, government agencies, and many more. In order for B2B companies to outcompete in a subscription economy, they will need to create meaningful differentiation in the market. They can do this by adopting modern value management practices that achieve three basic outcomes:

Provide clarity around the promised value before the purchase

Grow pipelines and win deals

Demonstrate realized value post-purchase to secure successful renewals and expand share of wallet

Resource Barriers

The road to becoming a value-centric customer-first company hasn't always been easy—or cheap. Indeed, many value management leaders have funded massive corporate programs to get there. Historically, implementing value management has been a resource-intensive exercise that takes years to mature.

At the core of the value management program has been the business value consultant. This is an expert who leads the effort to build value models—the financial and strategic template used to quantify and communicate the product's value for the customer—and create business cases to help provide economic justification for the investment. As you can imagine, these consultants spend a lot of time conducting research and analysis, building models, and doing collaborative reviews. Much of the work is manual, tedious, and difficult to automate.

Not surprisingly, value management consultants can be expensive. Typically, they are experienced professionals who have worked for top management consulting firms, have earned MBAs, and spent years in the industry cultivating relationships with executive-level buyers. For most companies, using value management consultants to support every sales opportunity would be inordinately expensive, especially for enterprise-level companies that field thousands of sales reps and an even larger set of partner sellers.

Thus, as companies seek to reap more benefits from value management by supporting more opportunities and customer accounts, they invariably run into a resource barrier. Fortunately, there is a way out of this dilemma by using new strategies, processes, and technologies, including AI, to scale value management efficiently and affordably.

Scaling Out Value Management

Since Competing for Customers was published, we've seen huge strides in the evolution of information technology. Key developments include:

Advanced SaaS applications that have introduced best-of-breed workflows and tools for marketing, sales, and customer success

Business processes supercharged with a wealth of analytics and insights from large datasets that help companies forecast, track, and measure how customers use products to capture benefits

New value-automation platforms that provide fast, standardized ways to model, quantify, and communicate value to buyers

Together, these advances have opened the door to new opportunities for accelerating value management programs and more quickly delivering customer success. A number of forward-thinking enterprises—we'll look at several in the chapters ahead—have launched high-profile initiatives to leverage these advancements, allowing them to cost-effectively scale value-based programs, empower more business teams, win more sales opportunities, and retain more customers.

Recently developed value management platforms—soon to be empowered by GenAI—are helping these innovators standardize tasks and accelerate business case development. Enterprise sales teams using the platform's value tools can create integrated value-management workflows that help any sales team match the work of experienced value management consultants. What's more, the platform allows organizations to extend value management practices to groups adjacent to sales, such as marketing and customer success, and ultimately bring the advantages of value management to every part of the business.

Introducing the Value Management Life Cycle

The following chapters will detail the blueprint for creating an AI-powered value management program. The core goal for value management is to answer the following four simple questions for the customer:

What value

can

I get?—Value opportunity

What value

will

I get?—Value target

What value

did

I get?—Value realized

What

additional value

can I get?—Value expansion

This is the structure of how we'll take you on the journey. First, we will lay out how value management touches the customer in each of these life cycle stages and highlight the current challenges companies face as they try to build these capabilities. We'll then highlight how a company can leverage best practices, automation tools, and AI solutions to overcome these challenges and realize revolutionary company outcomes (e.g., revenue lift, margin expansion, reduced customer churn). The life cycle of the value management journey is illustrated in Figure 1.2.

Figure 1.2: The value management life cycle

Your Guide to Achieving 8X Company Revenue Outcomes

The book is a guide for anyone interested in delivering a best-in-class value management program, including CEOs, sales, product, marketing, and customer success leaders, as well as experienced value management practitioners. No matter where you are in your value management journey, this book gives you the blueprint to build a company-wide unified value management program by integrating GenAI to drive exponential increases to your bottom line—a result we call 2-to-the-power-of-3, or 8X, business revenue outcomes.

“2-TO-THE-POWER-OF-3” COMPANY REVENUE OUTCOMES

Companies implementing our AI-driven value management approach are seeing a quantum leap in revenue growth as well as measurable improvements across a gamut of sales, marketing, and customer success metrics. Based on our research, we conservatively estimate that B2B businesses that adopt our blueprint can expect to achieve what we call2-to-the-power-of-3 revenue growth outcomes: 2X pipeline, 2X revenue, and 2X LTV (customer lifetime value) expansion with lower churn and higher upsell and cross-sell rates.

The following chapters will dig deeper into this value formula and explore what it can mean for B2B companies across industries.

Notes

1

   “Strategic Value Management,” PMI, Michel Thiry, PhD, PMP, PMI Fellow, (

https://www.pmi.org/learning/library/strategic-value-management-business-benefits-8699

).

2

   Giraudo, L. & Monaldi, E. (2015). PMO evolution: From the origin to the future. Paper presented at PMI

®

Global Congress 2015—EMEA, London, Project Management Institute (

www.pmi.org/learning/library/pmo-evolution-9645

).

3

Competing for Customers

(Pearson, 2016),

Figure 1.1

, p. 12.

4

   “Market size of the digital subscription economy worldwide in 2020, with a forecast for 2025, by segment”, Statistica, 2024 (

https://www.statista.com/statistics/1295064/market-size-digital-subscription-economy-worldwide-by-segment

).