8 Laws of Digital Transformation to Drive Your Business Growth 8 Laws of Digital Transformation to Drive Your Business Growth
Digital Transformation is the creation of a continuously learning and adapting, AI-driven, and human-empowered business model that seeks to identify, codify, and operationalize actionable customer,... 8 Laws of Digital Transformation to Drive Your Business Growth

Digital Transformation is the creation of a continuously learning and adapting, AI-driven, and human-empowered business model that seeks to identifycodify, and operationalize actionable customer, product, and operational insights (propensities) in order to optimize (reinvent) operational efficiency, enhance customer value creation, mitigate operational and compliance risk, and create new revenue opportunities. 

This article is an excerpt from the book The Economics of Data, Analytics, and Digital Transformation by Bill Schmarzo – A comprehensive book that helps you build a continuously learning and adapting organization with the potential to extract increasing levels of businesscustomer, and operational value from the amalgamation of data and advanced analytics such aAI and Machine Learning. 

In this articlewe’ll pull together all the aspects of digital transformation. To help guide organizations along their digital transformation journey, I have come up with these “Digital Transformation (DX) Laws”; laws based on repeated observations that describe or predict a range of natural phenomena. These “Digital Transformation Laws” come courtesy of several customer engagements; engagements where organizations are pursuing digital transformation but get waylaid by unexpected obstacles along that journey (picture the “Jason and the Argonauts” movie…the original not the awful remake). 

DX Law #1: It’s About Business Models, Not Just Business Processes 

Digital Transformation is about reinventing and innovating business models, not just optimizing existing business processes 

Solely optimizing existing business processes is a “paving the cow path” mindset, where organizations simply apply new digital technologies to replace existing human-intensive operational processes, without taking into full consideration where and how new sources of customer, product, and operational value can be created. And while “paving the cow path” can yield marginal improvements in your business model (a Horizon 1 effect that we will discuss later in the chapter), marginal improvements won’t win the day from a business model reinvention and digital transformation perspective. 

Figure 1: Digital Transformation Means Business Model Reinvention 

DX Law #2: It’s About Digital Transformation, Not Digitalization  

Digital Transformation is about reinventing your customer engagements and business operations with continuously learning AI capabilities to derive and drive new sources of customer, product, service, and operational value.  

Digital Transformation is more than just digitalization, which is the integration of digital technologies such as web-based apps, mobile devices, and sensors into existing operational processes. digitalization enhances or replaces human-centric processes with digital technologies, such as transmitting current patient health and wellness data to the cloud using mobile devices, apps, and sensors on a real-time, granular basis instead of requiring patients to physically travel to a care facility on an as-needed basis and have their vital health and wellness numbers manually recorded by a nurse (see figure below).

Figure 2: Digitalization versus Digital Transformation 

DX Law #3: It’s About Speaking the Language of Your Customers  

Digital Transformation is about empathizing, ideating, validating, and quantifying the creators and inhibitors of customer value; it’s about reinventing your business model to expand upon, exploit, and monetize those sources of customer value creation while eliminating the inhibitors of value creation. 

Let’s say that you are in the retail industry and looking to identify opportunities to combine digital technologies with customer usage insights (propensities) to eliminate barriers to customer value creation. That retailer would want to invest the time to empathize, ideate, validate, and quantify the sources and impediments of value creation for their customers. Figure 8.4 provides an example of how a retailer could reinvent the customer value creation process by emphasizing the sources and eliminating the inhibitors of value creation. 

DX Law #4: It’s About Creating New Digital Assets  

Digital Transformation is about creating new digital assets—Analytic Profiles and analytic modules—that leverage customer, product and operational insights (propensities) to drive granular decisions and hyper-individualized prescriptive recommendations.  

Organizations need to build new digital assets—Analytic Profiles (or Digital Twins) and composable, reusable, continuously learning analytic modules—that codify the customer, product, and operational insights (propensities) that provide the fuel for the organization’s digital transformation. 

DX Law #5: It’s About Transitioning from Predicting to Prescribing to Autonomous  

Digital Transformation is about predicting what’s likely to happen, prescribing recommended actions, and continuously learning and adapting (autonomously) faster than your competition. 

Digital Transformation is about creating an organization that continuously explores, learns, adapts, and relearns. Wash, rinse, repeat. Every customer engagement is an opportunity to learn more about the preferences and behaviors of that customer. Every product interaction or usage is an opportunity to learn more about the performance and behaviors of that product. Every employee, supplier, and partner engagement provide an opportunity to learn more about the effectiveness and efficiencies of your business operations. 

Figure 3: Analytics Maturity Curve: From Descriptive to Autonomous Analytics 

DX Law #6: It’s About AI-driven Autonomous Operations and Policies  

AI can enable more granular, relevant operational and policy decisions by continuously learning and adapting based upon most current environment situations…with minimal human intervention. 

Policies are the foundation for any successful organization. They document the organizational principles, best practices, and compliance guidelines that aid decision-making in supporting the consistent and repeatable operations of the business. But most organization’s policies are static, documented like a series of static if-then rules that are difficult to manage and even more difficult to update based upon changing business, economic, societal, cultural, and environmental conditions. 

What if organizations could replace those static if-then types of policies with AI-based, continuously learning and adapting algorithms that learned and evolved based upon the constantly evolving state of the environment in which the business operates? The result would be an organization as nimble as the market and the world conditions dictate and would super-charge the organization’s digital transformation. 

DX Law #7: It’s About Identifying, Codifying, and Operationalizing Sources of Value  

The heart of Digital Transformation is the ability to identifycodify, and operationalize (scale) the sources of customer, product, and operational value within an environment that is continuously learning and adapting to ever-changing customer and market needs.  

Digital Transformation knows no artificially defined industry borders. It seeks to uncover intimate and actionable “customer” insights no matter where that customer might be on their personal journey and use those customer insights to reinvent the organization’s value creation processes (see figure below).

Digital TransformationFigure 4: Digital Transformation Value Creation Mapping 

DX Law #8: It’s About the 3 Horizons of Digital Transformation  

Create an Aspirational Vision to focus and prioritize the organization’s immediate and long-term investments in customer, product, and operational value creation.  

Unfortunately, most organizations do 2 things very poorly— prioritize and focus. Too many organizations “peanut butter” their precious transformational resources across too many “strategic” initiatives. Organizations don’t fail due to a lack of “strategic” initiatives; organizations fail because they have too many. Which brings us to the final Digital Transformation Law and its importance in setting that Aspirational Vision towards which to direct and focus the organization’s precious digital transformation resources and investments.  

Digital TransformationFigure 5: 3 Horizons of Digital Transformation 

In 2000, McKinsey & Co proposed the “3 Horizons Portfolio Management Framework” as an approach that allows companies to manage a portfolio of projects for current and future growth. Then in 2015, Geoffrey Moore wrote his management strategy book “Zone to Win” that proposed a management framework to prioritize projects with the goal of sustaining the current business while investing in future businesses. 


Evolutions are nice and safe (unless you are a dodo bird). Revolutions, on the other hand, totally disrupt business models while seeking to disintermediate competitors’ customer relationships and reinvent industry value chains. To survive the revolution, organizations must seek to reinvent how they create new sources of customer, product, and operational value. If you want to exploit the “8 Laws of Digital Transformation,” organizationally, that means:  

– Transitioning from siloed business functions to interdisciplinary collaboration.
– Moving from seniority-based, leader-driven decision making to data and analytics-driven decision-making at the front lines of customer engagement and operational execution.
– Transforming from a rigid and risk-averse culture, to an agile, experimental, learning, and adaptable culture.
– Becoming value-driven within the frame of customer journey centricity. 

About the Author 

Bill Schmarzo, The Dean of Big Data is a University of San Francisco School of Management Executive Fellow and an Honorary Professor at the School of Business and Economics at the National University of Ireland-Galway where he teaches and mentors students in his courses “Big Data MBA” and “Thinking Like a Data Scientist”.  

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