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.”
(as published by Forbes along with several others).
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 :
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
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.
“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 :
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 :
*See my other Cloud Architecture articles for a more detailed analysis of Cloud Enablement.
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 and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution.“
For any organization, identifying markets and battle-grounds for products and services is the ultimate strategic decision when formulating Business Models.
“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).
“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 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 :
** For a more comprehensive overview on this topic, see article:
* 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 :
(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.
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.
(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, ..).
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 :
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 :
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.
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).
From the Interactive Design Co :
From CIO Magazine :
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.
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) :
A high level example of what the Oracle EA Process entails is described as : (see diagrams below for reference)
Gartner has published multiple variations of “Maturity Models” (which all originated from the original CMU CMM, as detailed in my Enterprise Architecture & Methodology Blog) :
*Click for a larger Image, and read the full article at the link above for a deeper understanding.
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