Big Data

The 4 Laws of Digital Transformation

Bill Schmarzo By Bill Schmarzo CTO, Dell EMC Services (aka “Dean of Big Data”) August 30, 2017

My discussions with organizations looking to “digitally transform” themselves is yielding some interesting observations. I expect that when these discussions move into the execution phase, we will start to create some “Laws of Digital Transformation” that will guide organizations digital transformation journey. So with that in mind, let me start by proposing these “4 Laws of Digital Transformation”.

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

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

Organizations are looking to leverage these digital assets to create new “economic moats.” Warren Buffett, the investor extraordinaire, popularized the term “economic moat.” “Economic moat” refers to a business’s ability to maintain competitive advantages over its competitors (through process and technology innovation and patents) in order to protect its long-term profits and market share from competing firms.

As highlighted in the McKinsey Quarterly article titled “Competing in a World of Sectors Without Borders,” organizations are embracing digital transformation to knock down traditional industry boundaries and disrupt conventional business models (see Figure 1).

Figure 1:  Digital Transformation Driving New Ecosystems and Business Models

Figure 1:  Digital Transformation Driving New Ecosystems and Business Models

 

While organizations that are looking to “digitally transform” themselves need to look long term, they can, and should, apply their digital assets to optimizing today’s key business and operational processes with machine learning and artificial intelligence capabilities.

Law #2: It’s About Eliminating Barriers Associated with Time and Distance

Digital Transformation is about coupling digital technologies with digital assets in order to eliminate time and distance barriers in your business model. 

Let’s say that you are in the retail industry and looking to identify opportunities to combine digital technologies with digital assets to eliminate time and distance as barriers to your business model. The scenario outlined in Table 1 provides an example of that process.

 

Customer Need:  Order More Cap’n Crunch Cereal
Traditional Business Model Digitally Transformed Business Model
Scour the Sunday paper and look for Cap’n Crunch coupons Yell from your kitchen table:  “Alexa, order me two boxes of Cap’n Crunch”capn
Search local grocery stores with Cap’n Crunch on sale
Get dressed to go out into public (can’t just wear underwear to the store)
Carve out the time to get in the car and drive to the store
Stop at the gas station to re-fuel your car that you daughter never fills up!
Aimlessly drive around the grocery store parking lot trying to find an open parking spot
Trek through the labyrinth of aisles in the store to find the Cap’n Crunch
Stand in line waiting to pay for your Cap’n Crunch
Patiently wait for your credit card transaction to be accepted at check out
Trudge through the hot parking lot trying to remember where you parked your car
Fight traffic to drive back home
Lug your boxes of Cap’n Crunch into the house

Table 1: Traditional versus Digitally Transformed Business Models

The scenario in Table 1 isn’t just optimizing the ordering process. The scenario in Table 1 requires the complete re-wiring of the organization’s business model and value creation process: from demand planning to procurement to quality control to logistics to inventory management to distribution to marketing to store operations to customer experience.

There are a multitude of opportunities for organizations to couple digital technologies with digital assets to remove time and distance barriers across the organization’s value creation model. Let’s go old school (“there’s no school like old school”) and check out the blog “Michael Porter’s Value Chain Creation Model” to start that brainstorming process (see Figure 2).

Figure 2: Michael E. Porter “Competitive Strategy: Techniques for Analyzing Industries and Competitors

Figure 2: Michael E. Porter “Competitive Strategy: Techniques for
Analyzing Industries and Competitors

Law #3:  It’s About Creating New Digital Assets

Digital Transformation is about creating new digital assets (data, analytics, and insights about customers, product, operations and markets)

Organizations need to create new digital assets around customer, product and operational insights. Organizations need to capture the analytical and behavioral insights about their customers, products and operations including tendencies, inclinations, predispositions, propensities, biases, preferences, trends, performance and usage patterns, associations and affiliations.

But these new digital assets can’t be built all at once.  Organizations need a thoughtful process for building out these analytic and behavioral insights one use case at a time.  See the blog “Analytic Profiles: Key to Data Monetization” for more details on how to leverage the Data Lake and Analytic Profiles to build out your organization’s new digital assets (see Figure 3).

Figure 3:  Leverage Analytics Profiles to build New Core Competencies

Figure 3:  Leverage Analytics Profiles to build New Core Competencies

 

These customer, product and operational data and analytics are corporate assets like we have never seen before. These digital assets never wear out and never depreciate. In fact, the more that you use these digital assets, the more their value increases. And these digital assets never deplete so they can be used across an infinite number of use cases at no additional cost.

Consequently, organizations need an entirely new approach to properly manage and leverage these digital assets. My recent University of San Francisco research paper “Applying Economic Concepts To Big Data To Determine The Financial Value Of The Organization’s Data And Analytics Research Paper” lays out a process for not only determining the economic value of your data and analytics, but also how to use these new digital assets to fuel your digital transformation process.

Law #4: It’s About Predictive Intelligence

Digital Transformation is about predicting what’s likely to happen, prescribing actions and learning from the results faster than your competition. 

Digital transformation is about creating an organization that continuously explores, tests and learns. Every customer engagement is an opportunity to learn more about the preferences and behaviors of your customers. Every product activity is an opportunity to learn more about the performance and usage of your products. Every employee, supplier and partner engagement is an opportunity to learn more about the effectiveness and efficiencies of your operations.

components

Leading organizations do this at scale, continuously exploring new ideas and testing new concepts in order to fuel the continuous learning cycle. Leading organizations master the “Art of Failure” where the “fail fast but learn faster” mentality permeates the entire organization. These organizations embrace the power of “might,” because if organizations don’t have enough might moments, they won’t have any break-through moments.

In the end, these organizations look to build “smart” or “intelligent” products, services and processes that self-monitor, self-diagnose, self-correct and self-learn; that strive to continuously refine and fine-tune the organization’s digital transformation journey.

Bill Schmarzo

About Bill Schmarzo


CTO, Dell EMC Services (aka “Dean of Big Data”)

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Dell EMC’s Big Data Practice. As a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

Read More

Join the Conversation

Our Team becomes stronger with every person who adds to the conversation. So please join the conversation. Comment on our posts and share!

Leave a Reply

Your email address will not be published. Required fields are marked *