What is Digital Transformation ?

In a nutshell, Digital Transformation is simply an organization’s ability to effectively map and re-calibrate Strategic Objectives/ Initiatives (Products, Services, Marketing, Support, internal Process/Tools/Standards/Methodologies, & Business Models) to utilize the latest “Digital” (aka Technological) capabilities, better aligning with today’s industry, global, and customer demands.

While CIO.com notes :

“Nearly 2,600 CIOs Gartner surveyed last year said they devote 18 percent of their budgets to digital transformation, a figure set to increase to 28 percent by 2018, Gartner analyst Andy Rowsell-Jones told CIO.com.  Going digital often means significant challenges and consequences, … adding that companies are overhauling their business models and allocating more of their IT budgets to catch digital disruptors.”

The REALITY is that only 11 per cent of companies surveyed are digitally mature According to a 2016 report from analyst firm Forrester.

The other realization is that .. as many as 84% of Digital Transformation projects FAIL !

(as published by Forbes along with several others).

! Don’t forget the Business Transformation !

As we will describe in more detail below, many of the greatest challenges related to Digital Transformation aren’t always related to the technology.    Lack of Leadership, strategic prioritization, uniform messaging, disjointed Operating Models, cultural dogmas, and resistance to change tend to be obstacles that frequently interfere with successful delivery.     

Shifts in Culture, Organization, Process, Tools/Technology, and Required Training are some of the most significant prerequisites that are often overlooked (and become obstacles).    They need to be planned, mapped out and communicated “up front” as part of any transformative strategic initiative (many times these become “afterthoughts” when it’s too late and transformation is coming off the rails).

As Edwards Deming (the man who led / defined the TQM movement, and the foundation for SixSigma) notes :

“The prevailing style of management must undergo transformation. A system cannot understand itself. The transformation requires a view from outside…

.. The first step is transformation of the individual… It comes from understanding of the system of profound knowledge. The individual, transformed, will perceive new meaning (purpose) .. , to events, to numbers, to interactions between people.”

Two key points to take from these quotes  :

• Leadership with a Holistic view of the entire system (from the outside in) is critical to understanding inter-relationships as well as how the requirements align with strategic objectives.
• His comments regarding the individual are finally gaining traction via the realization that self-directed Agile teams can offer dramatic benefits to an organization, while at the same time inferring that BOTH top-down AND bottom-up approaches can and should be utilized.

For more information regarding E. Deming, his Key Principles, and how continuous improvement methodologies relate to Enterprise Architecture & Digital Transformation, see my article :  Enterprise Architecture 101 : From Frameworks & Methodologies.. to Continuous & Agile Cloud Enablement

What Key areas are the focus of Today’s Digital Transformation ?

.. and How do those Technologies relate to “Disruptive” Business Impact ?

• Mobile Device Access   –  The pervasive explosion of Smart Phones has become the TOP way to access the internet, MORE than both desktop computers and/or laptops/tablets.

• Mobile App Development    – The rapid growth in SW Development, utilizing Java/ Javascript, node.js, JSON..

• User Experience (UX) optimizations can offer dramatic benefits

• Social Media   –  Explosive growth in the average person’s use of Social Media platforms such as Facebook, Snapchat, Twitter, .. which today carry some of the largest volumes of internet traffic.    THIS repository of unstructured data is becoming a goldmine that any digitally adept organization needs to leverage beyond marketing, to utilize as one of the best gauges of consumer demand, product needs, customer sentiment analysis, and feedback for canary testing.

• Streaming Media, IoT, & Smart Homes/Cities   – Content on-demand has started to eclipse even Cable TV viewing, which started out with YouTube, today has blossomed with Netflix.. who does carry the largest segment of internet traffic, along with Amazon Prime, and other players.   Add to that, the next wave of streaming data that comes from the ever growing “Internet of Things“, which can include any type of network/internet connected device which offers transmission (streaming) of data.  Today’s devices include everything from traditional badge readers, smartphones, and cameras, but are rapidly expanding to biometric devices or even self driving cars.    Many of these devices provide autonomous (artificially intelligent) operation, data collection, and unique telemetry/data which can offer a competitive DISRUPTIVE advantage to those that get to market first.

• BigData / DMSA / Analytics / AI-ML- The ability to aggregate all forms of “unstructured data” and align it with structured data to generate ACTIONABLE business “INSIGHTS” that can be monetized or provide important customer feedback to align with business strategy.   Data Management Solutions for Analytics (DMSA) is today’s Gartner terminology for vendors that have embraced this realm with fully integrated frameworks and solutions for turning unstructured/structured data into Analytic insights.    Today, many of these systems/services are being augmented with AI/ML to offer “predictive” analytics, and or Autonomous Database operation (such as Oracle’s 18c DB coined as the “Self Driving DB”).    *See Gartner’s 2017 Magic Quadrant for DMSA*

* Cloud-Enabled Architectures

(Public/Hybrid/ Private Deployments of Infrastructure- IaaS, Platform- PaaS, and/or SW as a Service- SaaS)   

As noted in previous posts, the pressure of decreased profit margins have forced companies to look inward and more closely examine Total Cost of Ownership (TCO), Return On Investment (ROI), along with underlying reductions in Capital Expenditures (aka, CAPEX) [Facilities/Datacenters, On-Premises Computing Infrastructure, Support/Maintenance, SW licensing costs, and related resources required to Manage/Operate, .. where Cash Flow analysis and Cost of Capital are at the center of the conversation].    Cloud computing has come to the scene to address several of these priorities, centering around agility, cost, and operational considerations as noted below.

NIST defines cloud computing as :

“A model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.”

As I’ve discussed in several other articles, Cloud Enablement comes in many forms as Deployment Models (Co-Located / Private / Public / Hybrid environments), utilizing various Service Models (Infrastructure / Platform / SW as a Service), each with an ecosystem of integrated Service offerings (IaaS: VM/Containers/Network/Storage , PaaS: aPaaS/DBaaS / iPaaS/ FaaS.. Platform Services, SaaS).

The critical FORK in the road comes in determining your organization’s Cloud Vision, and defining that Strategically (and sometimes Tactically) to establish Strategic priorities that can become targeted corporate initiatives (for establishing success stories to fuel further adoption and cultural transition).   Note that certain requirements & capabilities are only possible within one specific type of deployment environment – such as Private or Public Cloud, while others require specific capabilities only available with a certain vendor’s portfolio.    However, most large enterprises are realizing that a “multi-cloud” vendor model, utilizing hybrid cloud deployments (combining the best of Private & Public cloud capabilities) is becoming a reality (ensuring no immediate disruption of Mission Critical platforms on-premises, while enabling rapid/agile and cost effective Public cloud integration and/or migration of less critical environments).

Some of the toughest decisions are determined for you based upon some of the following :

• SLA’s (response times/latency, Workload Isolation/tenancy, Bandwidth/ Throughput/ IOPS, RAS-Uptime & Availability guarantees, ..among other requirements such as those for Disaster Recovery)
• Regulatory Compliance (Security, Data Location / copies / retention, etc)
• Current State Environment (Legacy HW, OS, RAS-Reliability/Availability/Scalability, Code/Languages, Custom Integration, Storage characteristics, Data Formats, Databases, Replication, Virtualization, Services, ..etc)
• Future State Requirements (Growth/Scalability, Architectural objectives -such as MicroService or FaaS integration, Cloud-Enabled IaaS Capabilities– such as BareMetal vs VM vs Container vs Serverless, Future State Architecture capabilities for PaaS services – such as Streaming event hub, IoT, and BigData with integrated platform predictive analytics, ..etc).

Other decisions to be made come after Discovery and examination of Current State Environments (such as Application Portfolio Analysis) to determine Migration Options and Alternatives :

• Rationalize (Phase out/ End-Of-Life and/or consolidate) Applications/Databases/Environments
• Replace (eg. Move to packaged Off-The-Shelf SW and/or migrate to Public Cloud SaaS alternatives)
• Lift & Shift (move intact environments / VM’s onto a cloud platform, typically unchanged VM-> VM)
• “Modernize” or Re-Factor Applications (re-design for Cloud enablement)
• Cloud Native / Cloud-First Approach (Re-Write Applications IN / ON Cloud Platforms, which includes many automated DevOps/CI/CD tools and platform integrated capabilities/services)

*See my other Cloud Architecture articles for a more detailed analysis of Cloud Enablement.

The 4th Industrial Revolution (aka Industry 4.0)

Many of the trends described above are converging as one collective disruptive force, most notably in manufacturing, such as large automotive assembly.    However, the same convergence of automation, robotics, SW & AI is disrupting other areas, ranging from pharmaceutical development/manufacturing.. to the broader realm of Supply Chain Management, warehousing, and/or package delivery.

Wikipedia describes this as “the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing^[1][2][3][4] and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution.^[5]“

Targeted, “Adaptive” and Agile Strategies are one of the Keys to DX Success

Which wave to ride ?  Red Ocean or Blue Ocean Strategies

For any organization, identifying markets and battle-grounds for products and services is the ultimate strategic decision when formulating Business Models.

in 2005, W. Chan Kim and Renée Mauborgne, wrote the book “Blue Ocean Strategy” which wikipedia notes :

“Based on a study of 150 strategic moves spanning more than a hundred years and thirty industries, Kim & Mauborgne argue that companies can succeed by creating “blue oceans” of uncontested market space, as opposed to “red oceans” where competitors fight for dominance, the analogy being that an ocean full of vicious competition turns red with blood.“

This is always the panacea, to create a new market or finding a niche market-space to infinitely sell your products within.  However, the reality is that when you “create” any market, the adoption and customer education will always lag if not part of a larger on-going (competing) paradigm shift or more traditional way to accomplish the same objective (where resistance to change and behavior modification can be a greater task than any attraction of new benefits).  Because of this, Blue Ocean Strategies pose more of an up-front risk, with longer-term rewards (though in part, Digital Transformations can become the same “crap shoot” if not studied, analyzed, planned and managed properly).

Bi-Modal Approaches to DX ?

Francesco Paola, CEO, Solinea makes a good point regarding Gartner’s “Bi-Modal” practice of utilizing 2 separate styles to manage activities/projects, noting :

“Our opinion—and indeed, that of anyone who has successfully guided an enterprise to agile—is that dividing IT into one bucket labeled “stuff that works” and another labeled “stuff that might be better one day” is dangerous.”

While a Bi-Modal approach might be the most realistic and cautious “old-school” style of dividing and conquering with “Predictable” vs. “Exploratory” activities and projects, overall agility and speed of INCLUSIVE and “positively” DISRUPTIVE Transformation may be stifled.

My general recommendation is that most organizations should initially utilize some level of cautious “Bi-Modal” approach, where RISK and EXPOSURE can be mitigated, while Transformative successes are rapidly promoted as reference use-cases.. to iteratively re-assess and transform “Predictable” areas & activities into Transformative ones (as part of an “ADAPTIVE” Agile Continuous Improvement mantra, factoring in real-time KPI’s & realigning where/when it makes sense).

Continuous Improvement is being embraced more ubiquitously

Continuous Improvement aspects of past (Lean, Six Sigma..) methodologies have gained a foothold in several areas, notably with the recent visibility and momentum of Agile DevOps & Scrum/ Kanban, offering many benefits, in addition to the following  :

1.  Providing infinite / incremental increases in product capabilities and quality of Products / Services
2.  Offering a growing pool of Re-Usable components, Standards, Architectures, and Process (SW libraries, API’s, System/Container Images, etc.).
3.  Shorter project development, Testing & Integration cycles =  Lower Time/Effort/Cost to Develop/Extend  + Faster Time To Market

** For a more comprehensive overview on this topic, see article:

• Enterprise Architecture 101 : From Frameworks & Methodologies.. to Continuous & Agile Cloud Enablement

• Agile / Rapid Methodologies & Tools that offer Continuous Improvement and Faster Time To Market  (Agile DevOps, Scrum teams..)

​* DevOps CI/CD Tools & Methodologies  :   * See my article DevOps 101 : From Waterfalls to Agile Cloud-Native Development with CI/CD *

One of the most underestimated, and mis-understood elements of Cloud enablement and Business Digital Transformation, is that without first embracing and creating an Agile and automated framework for Development & Operations, the rest of Cloud Adoption is simply “window dressing”.    If done right, the area of DevOps is THE enabling foundation and integrated framework of process + tool automation (-> CI/CD) that supports many if not most of a company’s Cloud adoption benefits.

* FOSS (Free & Open Source SW) tools, packages, frameworks, and Repositories are offering an abundance of freely interchangeable SW components and/or complete solution stacks (eg.  Docker Containers & Images/bitnami, Github repo’s, ..).

* Public Cloud Providers & Services [ IaaS (Infrastructure Services) & PaaS (Platform Services) as described above ] :  offer the ability to rapidly provision & stand-up Infrastructure (CPU’s, Memory, Storage, Network) and/or Platform services (DB, BigData, Java, IoT, ..) on-demand via a remote secure VPN or direct connection (with the click of a mouse and a credit card #/account).    In most cases, this not only lowers the TCO by eliminating CAPEX (Capital Expenses), but also lowers the overall cost to Configure, Integrate, Manage, and Operate via lower monthly OPEX (Operating Expense) costs.   

* API Repositories offer a breadth and depth of easily integrated distributed application and service extensibility via remotely accessed interfaces (typically REST – Representational State Transfer + HTTP / JSON).

Coupled with “Cloud Native” Microservice development (and/or Application Re-Factoring/ Re-Architecture), enabling more rapid development cycles by re-using already existing “standard” API’s across a broadly available services landscape, as shown in the following diagram from Bessemer Venture Partners :

Business Process “Agility” via Scrum Framework

(an extension of Agile SW Development methods that have been extended successfully beyond SW development, with much recent adoption and publicity breaking large projects into manageable pieces via “sprints” and “sprint retrospectives“).

Scrum “teams” will establish prioritized lists of activities/milestones they decide to work on as “sprints” for 1-4 weeks (even 24hr sprint activities).   The objective is to rapidly accomplish success or failure so that progress forward with many small incremental advances will both offer continual improvement, as well as provide more rapid failures & lessons learned vs. at the end of a long enterprise project or development effort when failure can be catastrophic.

Agile DevOps CI/CD “Continuous Integration” and “Continuous Deployment” methods & tools are going main-stream

• Beyond the smaller pockets of business DevOps, this area has been a recent area of focus in PaaS (Platform as a Service) offerings for all large-scale Cloud providers.    The objective is how to best integrate, register, encapsulate, and Orchestrate the complete DevOps CI/CD lifecycle, vs. cobble together and custom-integrate several toolsets and disjointed processes (between Development and Operational aspects).

Faster Development -> Production Deployment = Faster TIME TO MARKET !!

At this point, Jenkins has taken the lead (built on TOP of a Docker foundation of rapidly deployable/reusable Containers/ images), but as mentioned in my Agile DevOps/Cloud-Native article, several competing alternatives are available.

Cloud Adoption can Require Radical Transformation of IT & Operations :

.. from IT as a Corporate “Cost-Center” to a “Profit-Center”

For the better part of the past ~15 years, IT has been trying to shake the reputation as a “Cost Center”..

(given that up to ~80% of IT budgets can be spent simply on maintaining existing systems/environments, keeping the lights on) vs. as “Profit Centers” for new Investments to Increase Productivity, Insights, and Time To Market.

In addition to reducing Capital Expenses, many companies have decided to transition any “Cost Centers” on the balance sheet to PREDICTABLE monthly / annual Operating Expenses (aka, OPEX) and in the process, exploring other options that don’t require facilities / datacenters, owning, nor Operating the assets (further reducing the staff required to manage).   While the early ~2000’s was led by Professional Services, Outsourcing, then Hosting providers, the convergence of technological advances in both HW & SW now offer extremely attractive alternatives utilizing “Cloud-enabled” Architectures based upon very cost-effective Deployment Models (Public, Hybrid, Private) and Service Models (IaaS, PaaS, SaaS).

This shift has driven phenomenal growth in the adoption of Cloud Architectures, which in turn has fueled the rapid expansion of vendor R&D, in turn delivering capabilities and optimizations at an extremely rapid pace.   Today the focal point of strategy / roadmaps for nearly all vendors is centered around “Cloud Enbablement” (Oracle OCI, Amazon AWS, Microsoft Azure, Google, IBM, ..).

Hybrid and Multi-Cloud deployment models will be a new reality for most enterprises

Most enterprises will encounter pockets of Enterprise workloads where requirements will dictate Public cloud services don’t meet all of their requirements for :   Compliance/Regulatory Security, SLA -Mission Critical Performance/Latency, Access/Control of the platform, and/or inability to Integrate with On-Premises platforms.

** For a fairly comprehensive overview of Cloud Enablement, see my other article :

• Cloud Architecture 101: The Road to Cloud Services (IaaS/PaaS/SaaS) & Deployment Models (Private, Hybrid, Public)

Multi-Cloud  is here to stay (to eliminate lock-in & leverage Costs & Benefits between providers)

The Cloud Operating Model brings with it a Business Transformation of IT

One critical area that needs to be planned for in advance is how Cloud-enablement and Digital Transformation ultimately shifts the Business Operating Model of IT : supporting End-users, Lines of Business, AppDev, Admin & Operations teams (See my other article regarding how this relates to the 4 key areas :   Control, Security, Latency, & Cost).

The transition to Cloud requires a Business Transformation of IT to a Cloud Operating Model and potentially a radical shift in IT Operations.   For companies that are closing entire datacenters and migrating the majority of Infrastructure + Application Environments to Public Cloud providers, this transition can be VERY disruptive.  The list below specifically reflects impact to areas/environments migrated to Public Cloud providers, and not necessarily for remaining On-Premises Private/Hybrid Cloud deployments :

• Movement from CAPEX acounting (HW procurement/provisioning) to OPEX (monthly subscription models for IaaS/PaaS/SaaS..), and the many ramifications.

• Reorganization of IT to transition Roles & Responsibilities (with potential down-sizing or shift to partners/providers for related resources).
• Transitioning IT from being a central Provider of Technology (Tactics) to a Strategic Partner where the focus needs to be on enabling enabling Strategic capabilities (Higher level solution Architecture, Multi-Cloud Service Broker, Service Catalogs, ..)
• Dramatic re-training (Cloud Architecture, Cloud Admin/Operations, ..)
• Departure of traditional activities :  IaaS config/admin (physical HW provisioning / rack/config, OS, network, Storage..) and PaaS Service setup (DBaaS, BigData, etc..) is transitioned from IT to the Cloud Provider, and in many cases to the Lines of Business for Service Configuration and Administration (decentralized Agile DevOps, DBA’s, SaaS, ..).
• A shift of Service / Support (Desk) ownership and transition to more of a Service & Support “Broker” (or proxy between Lines of Business and Cloud Providers and/or Partners).
• Creating Centers for Enablement (C4E) vs. Centers of Excellence (defining and Governing rigid standards, see next bullet)
• Loosening the reins somewhat on Centralized “Standards” and Reference Architectures (given DevOps autonomy as self-directed teams with end-to-end ownership of Dev->Test-> Prod deployment).

The Convergence of Data (and it’s significance as an under-utilized asset)

“Data is the new Oil” .. refers to an asset that is only valuable AFTER it has been Refined 😉

One significant realization that has progressed over the past decade has moved from “Content” being king.. and Structured “Data Mining”, ..to understand the true value is in leveraging the aggregate by Converging/Correlating all related types of Data.    Businesses have realized that one of their most underutilized assets within any organization has been unstructured (formerly ignored) data, that can work to fill in the gaps as part of a Corporate BigData/Analytics framework.

Injecting new Life into your Old Enterprise Data, without Boiling the OCEAN of Data

Imagine if you could “SuperCharge” your Enterprise CRM (Customer Relationship Mgmt), ERP (Enterprise Resource Planning), or SCM (Supply Chain Management) Data.. so that it becomes infused with real-time metrics or new “indicators” ?

By taking, Transforming, and “Layering” UNSTRUCTURED data, (and correlating) on top of your Enterprise STRUCTURED data, this is how “BigData” Analytics performs it’s magic.    The new “Unstructured” data can come from ANY sources , aggregating any data that might hold the potential for value/insight : from Social Media pages, Weather/News feeds, Mobile App data, Customer Browsing/Log Files, Online coupons, IoT sensor/instrumentation data from automobiles or health monitoring devices, to GPS enabled apps, ..).

For CRM, this might enable insights regarding specific customer experiences or feedback that you weren’t aware of previously, that you could link to targeted Marketing or Sales campaigns.. potentially resolving issues with Products or customer satisfaction.   The possibilities are endless.

At the same time, capturing ALL data .. and hoping it talks back to you, without some effort in the transformation/reduction/filtering process, is a bit of wishful thinking, and can waste a lot of time & effort (the fast-track to BD/Analytics failure).

By Validating “Actionable Insights” as early as possible, you will be reducing the amount of effort, time, and cost dramatically.   

Artificially Intelligent (AI) analytics with Machine Learning (ML) capabilities is becoming an integral part of all future products as shown below.

Using Data Analytics to develop “Actionable Insights” as your Compass :

“Adaptive” Business Culture is at the core of DX Success

  Setting Realistic Expectations and Contingency Planning / Prep for the Inevitable “bumps in the road” ..

Create a Culture & Atmosphere of COLLABORATION & Continuous Improvement

• Re-Examine the Business & Operating Models via “Value Stream” mapping & analysis.

• Solicit Feedback from ALL areas (internal & external) & offer Transparency in return
  • (Blind Strategy or “hollow” Vision Statements are DOOMED to Failure, no ivory tower exceptions)
• Live & Die by your Own Rules ;  Operate as you expect your customers to.
• Empower Teams & Champions (to ADAPT & tackle projects with agility / autonomy)
• Showcase, Celebrate, & Reward Successes (the best way to reinforce positive behavior & set expectations)
• Grow & Expand Skill-sets via Training and Mentoring (Business / Process / Technology)
• Practice Accountability (while recognizing that we Learn MORE from Failure than we do from Successes)

Embracing Customer Needs & Feedback to Improve the Customer Experience vs. trying to modify their behavior

From the Interactive Design Co :

From CIO Magazine :

Disrupt.. without being (too) Disrupted

**The Most Common reasons WHY Digital Transformations FAIL** :

• #1 Reason :  NOT having Leadership & directives coming from the TOP (CEO & Board)
• “Resistance To Change” is the default behavior with any endeavor where people are involved.   Without getting too deep in the psychological weeds, the greatest fear that people have is “Fear of the Unknown”.    Without a comfortable (regular) & “Predictable” set of future events & outcomes, people fear the worst possible outcomes and dig in their heels to resist.   To overcome this resistance, Sr. Mgmt must calm fears and depict the “shared benefits” (POSITIVE Outcomes), methods, roadmaps, and timelines in as much detail as possible (aka, WHY the future will be better if we proceed down this path..).
• Internal Politics – The Inability to tear down Walls and Work as ONE collective team with SHARED goals/objectives.   Just as in the item above, logic goes out the window and personalities compete for selfish personal objectives.
• Strategic Decisions being made in a Vacuum (or based on personal Bias or Preferences)

Old HABITS are Hard to Break ..

As eluded to in the section above, if Strategic direction is “set in stone” and doesn’t incorporate the feedback of those in the organization with their finger on the “pulse” of the industry and/or customers, then it’s DOOMED to Failure.   You’d be AMAZED how many large corporations & strategies are doomed to this type of failure.. all based upon “Ivory Tower” blind objectives being set without making an informed decision, many times based upon past preferences/practices or old corporate direction/directives.

• Conflicting Strategies – Overlapping or Opposing Strategic Objectives
• Poor Planning –        (eg. Timelines not based upon past experience or enough review/research, Understaffing, etc)
• NOT establishing adequate Digital KPI’s to measure progress & success effectively (Business Value, ..).
• .. the typical reasons

What’s the best process to follow for DX ?

*Utilize and Leverage the Leadership and Experience of a person or team (partner) that has already successfully tackled similar endeavors.

Embrace and utilize an Enterprise Architecture Framework and Process

Note that while Corporate Standards, Process, and Methodologies can be incorporated and utilized, a holistic Enterprise Architecture Framework ensures a comprehensive process that leverages industry best practices.

(See the following article for a thorough examination of the alternative EA frameworks) :

• Enterprise Architecture 101 : From Frameworks & Methodologies.. to Continuous & Agile Cloud Enablement

A high level example of what the Oracle EA Process entails is described as :    (see diagrams below for reference)

1. Establish an Architecture Vision (composed of : Strategic Business Objectives, Initiatives, and Future Requirements)
2. Define and Discover Current State Environment / Architecture(s) – Issues/Needs, Compelling Events, Technology, etc.
3. Design a Future State Architecture (that maps the appropriate technology to achieve the desired Business Objectives)
4. Create a Strategic Roadmap (with a phased Implementation Plan)
5. Recommend any Tactical (Short Term) Interim phases (eg. Stabilization, or short-term functional or capacity expansion)
6. Develop the appropriate EA Governance required (eg. Steering Committees, Compliance/Policy teams, etc)
7. Develop a viable Business Case (Map the FSA back to the Business Benefits, Profitability, TCO, ROI, TTM, Capacity, Capabilities, ..)
8. … Kick-Off & Execute, Measuring Digital KPI’s to track the Progress & Success (vs. Business Value, Cost, feedback, ..)
9. Celebrate Successes, Learn From Failures, & ADAPT ! .. Continuously Re-Using & Improving

Measuring your Organization’s Success with “Transformative” KPI’s

• Develop Digital KPI’s to track the progress with Sr. Executives throughout the organization

  • Track “Traditional” metrics (Cost, Timelines, Customer Feedback/Satisfaction, ..)
  • Develop New “Transformative” KPI’s such as :
    • Maturity Index Guage (see below)
    • Return on “Innovation”
    • % Revenue from New Digital Channels
    • # new Projects/Technology/Innovations
    • # New Customers/logo’s
    • # New Capabilities
    • % Chg/Increase in Customer Interaction/ Feedback
    • Reduction in TIME to Market
    • ..etc.

• Use a “Capability Maturity” Index as one “Gauge” to visually Identify and advocate progress toward Organizational Milestones.  (see examples below)

Gartner has published multiple variations of “Maturity Models” (which all originated from the original CMU CMM, as detailed in my Enterprise Architecture & Methodology Blog) :

Insightful research from MIT Sloan researchers, identifies a 3-phased approach as an Innovation Measurement Framework :

*Click for a larger Image, and read the full article at the link above for a deeper understanding.

MIT Sloan also surveyed several hundred enterprises on how well they compared on Digital Business Transformation :

For greater insight regarding the Success & Failure of Digital Transformation, see the following additional vantage points :

• Article by CIO.com that examines : 10 Successful Business Transformation efforts
• HBR article by Jeffrey Immelt Re: Inside GE’s Transformation

• HBR Article :  Why So Many High-Profile Digital Transformations Fail
• INC.com Article :   Why GE Digital Failed

To contact the author directly :

•  Twitter/ DirectMsg: @toddjobson  https://twitter.com/toddjobson
•  or LinkedIn :   https://www.linkedin.com/in/todd-jobson-a29b38a7/

All content and comments made are that of the author, and not of current nor past employers.

Copyright© 2017-2020 Todd A. Jobson & TechThought.org ; All Rights Reserved *