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How AI Will Benefit Small Businesses in 2019

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Previously in Part I “It’s Not Digital Transformation; It’s Digital “Business” Transformation – Part I” we introduced two fundamental digital transformation techniques to help organizations identify where and how to drive their digital transformation journey:

·     Fundamental #1: Identifying Sources of Value Creation. A methodology for identifying the sources of value creationis customer-centric perspective (think “outside-in”) that focuses on identifying, validating, valuing and prioritizing the sources of customer (and market) value creation. To accomplish Fundamental #1, we will leverage a Design Thinking technique called the “Customer Journey Mapping” (see Figure 1).

Figure 1: Customer Event Mapping: Identifying Sources of Value Creation

·     Fundamental #2: Identifying Engines of Value Capture. A methodology for identifying the engines of value captureis a production-centric perspective (think “inside-out”) that focuses on identifying and prioritizing the organizational capabilities or functions necessary to capture the sources of value creation. To accomplish Fundamental #2, we will leverage old school Michael Porter’s “Value Chain Analysis” (see Figure 2).

Figure 2: Value Chain Analysis: Identifying Engines for Value Capture

In part II of the series on the Customer Journey Digital Transformation, we are going to discuss the missing middle layer – the “How” we are going to link the Sources of Value Creation back to the organization’s Engines of Value Capture.

The Missing “How” Layer: Digital Solution Architecture

We need a “How” layer that defines how the organization is going to create, refine, and re-use its digital assets (data, analytics and apps) to digital transform its internal, production-centric “What” (Value Chain Analysis) layer in order to capture more of the customer-centric “Why” (Customer Journey Mapping) sources of value creation (see Figure 3).

Figure 3: Digital Transformation Value Creation Mapping

In the previous blog titled “The Customer Journey Digital Transformation Workbook,” we introduced a workbook to identify those components that comprise the “How” layer around a customer event(see Figure 4).

Figure 4: Customer Journey Digital Transformation Worksheet

As a reminder, for an end consumer, an event could include buying a house, planning a vacation, taking a trip, or having surgery. For a business customer, an event could include running a marketing campaign, developing a new product, creating a partner relationship or expanding into a new market.

For each customer event, we need to capture some important over-arching event information including:

·     The event “Objectives.” Why is the customer undertaking the event? What does the customer hope to achieve from the execution of the event? What are the expected financial, operational or personal benefits from the event?

·     “What does Success Look Like?”from the customer perspective. When the event is completed, what does the customer want to have accomplished? How should the customer feel about the event after event completion.

·     The customer’s potential “Impediments to Success.” What are the situations or constraints that might impact the success of the event? What are the potential sources of customer frustration during the event?

The workbook methodology then identified the digital assets necessary to support each stage of the customer journey – from “Epiphany” (when the customer first becomes aware that they want to undertake this event) through “Execution” and finally through “Expiration” (when all activities and emotions associated with the event are completed).

Those digital assets were:

·     What are the keyDecisions that the customer needs to makefor each stage of the customer journey?

·     What are the Metricsor Key Performance Indicators(KPIs) against which progress and success in each stage will be measured?

·     What are the predictions and Recommendationswe want to deliver to the customer in support of their key decisions? How can we leverage predictive and prescriptive analytics to undercover customer, product and operational insights might improve the effectiveness of the customer’s key decisions?

·     What are the key Business Entitiesaround which we want to capture analytic insights; the entities around which actionable analytic insights can help to improve the effectiveness ofcustomer’s key decisions?

·     What are the Customer Experiencerequirements for creating a more compelling, differentiated Intelligent Apps; that is, what “intelligent apps” (insurance policies, travel itineraries, financial accounts, job resumes, college transcripts, tax returns, credit cards, medical records, passports, drivers’ licenses, work visas) can we build to support, integrate, and continuously learn from each customer interaction along the customer journey?

And while I may not be crazy about the name “Digital Solution Architecture” for this “How” layer, it does capture the key digital transformation requirements that need to be enabled in the “How” layer. Plus, I reserve the right to change the name later (see Figure 5).

Figure 5: The “How” Layer

The “aha” moment for me from doing this Customer Journey Digital Transformation exercise with the students at the University of San Francisco and again with the students at the National University of Ireland (NUI) in Galway was the “intelligent app” idea. The students easily identified what they would want to have (whether on a website or in a mobile app) with which they could interact that would learn more about their objectives, desires and areas of interest in order to deliver more relevant recommendations.

Digital Transformation Summary

Digital Transformation drives both the customer journey and business value chain transformations, but the transformations are driven from the perspective of the customer because that’s the source of value.  Think about the Cap’n Crunch example covered in the blog “Is 2018 the Tipping Point in Digital Transformation?.

Amazon identified the sources of value (having the Cap’n Crunch show up when I want it) as well as the sources of frustrations (e.g., driving to and from the grocery store, wandering the store looking for the Cap’n Crunch, standing in line to pay), and then transformed both the customer journey (“Hey Alexa, order me this!”) as well Amazon’s internal processes – or engines of value capture (logistics, procurement, order entry, distribution, inventory management, etc.).

Figure 6: Digitally Transforming the Customer Journey

What I find interesting about the “Digital Solution Architecture” layer is that we have literally created the “Digital Twin” equivalent for a Customer Event, including the intelligent apps (AppDev) requirements necessary for the successful completion of the customer event.  Figure 6 represents all the layers pulled together into a single graphic.

Figure 7: Digital Transformation Value Creation Mapping

My hope is that the “Digital Transformation Value Creation Mapping” eventually (through continued testing and feedback with both clients and students) becomes as useful and actionable as the Big Data Business Model Maturity Index (see Figure 7).

Figure 8: Big Data Business Model Maturity Index

The Big Data Business Model Maturity Index has benefited from years of customer and student engagement to become more refined and ultimately more actionable in providing a roadmap to help organizations become more effective at leveraging data and analytics to power their business models. We need a similar roadmap for helping organizations digitally transform their business models and business operations.

By Bill Schmarzo

Bill Schmarzo

CTO, IoT and Analytics at Hitachi Vantara (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”. 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.


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