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The Four Laws of Digital Transformation | @CloudEXPO @Schmarzo #AI #DX #IoT #SmartCities #DigitalTransformation
Digital Transformation is about innovating business models, not just optimizing business processes
By: William Schmarzo
May. 15, 2019 01:45 PM
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
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
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
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.
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
Law #3: It’s About Creating New Digital Assets
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
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 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.
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.
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