In the previous post, we examined some of the characteristics of early application systems, through the lens of the tools employed to build and operate them, and the impact of these characteristics on the organizations that used them.  Clearly, limitations of the available technologies imposed constraints of how and how fast companies could adapt and transform to reposition themselves in the markets in which they operated, exploit opportunities and respond to business threats. 

The systems and the way that they were designed, implemented and integrated into the organization and operations of the companies that use them should be looked at as elements of a complex system of causes and effects in which changes in the business environment engender the need for revised systems and evolving technologies create opportunities to which the enterprise must respond.  The ability to understand and manage the resonance between outside-in business drivers (evolution of business models and changes in the competitive landscape) and inside-out drivers (evolution of technology-driven capabilities) is a critical success factor for today’s enterprises.

The ability to transform rapidly depends on the ability to revise and automate processes, which depends on the ability to design and build systems quickly.  The need to change rapidly brings with it the probability of error and omission so, therefore, there is a need to balance potential competitive benefits with the costs and risks of building the wrong things or building them in such a manner that they ultimately do not operate reliably or serve the strategic imperatives of the business.   Overall, what has happened over the past 25 years or so has impacted every aspect of the relationships among these considerations.

Systems: Under the Hood Now

As opposed to the architecture that I described in the previous post, today’s applications are composed of innumerable components, distributed independent data repositories and complex communications networks and protocols.  Separation of responsibilities and statelessness, design characteristics that minimize interdependence or coupling among components are common goals.  Orchestration, coordination among the components to assure that services are provided reliably and coherently, is a requirement that must be addressed in design and implementation.  Incorporation of external services and capabilities from open-source libraries, enabled via Application Program Interfaces (APIs) facilitates rapid delivery of rich functionality, much of it data-driven and implementing artificial intelligence and machine learning-based capabilities.

The evolution of technology and methodologies for implementing and delivering application systems have created substantial competitive issues for enterprises and their IT organizations.  Some companies still have an enormous investment in and dependence on systems developed more than 20 years ago.  No one wants to write off and replace depreciated assets that are still performing needed functions and no one wants to take on the risk of replacing them, especially when they may be poorly documented, not particularly well-understood and dependent on a shrinking pool of talent with experience in the technology in which they were implemented.  Such systems do need to be updated from time to time and the risk of operating them only increases as they grow older and older.

This TechTarget article addresses some of the issues facing companies that continue to operate mainframe systems, which constitute most of the ‘dinosaurs’ still running, indicating a general trend toward replacing them.  When monolithic systems were first built, vertical scaling was almost all that was available to add capacity when it was required.  Vertical scaling simply means “get a bigger computer with more memory and faster processor(s).”  It is, in general, a discontinuous and expensive way to grow.  If a system can support n users, then n + 1 will require an additional machine, raising the cost of servicing them to twice what it was until the user base grows toward the limit of the larger configuration.

Today’s componentized architectures inherently favor horizontal scaling, which is accomplished by adding capacity in parallel and sharing the load across multiple processors.  In the cloud environment capacity is managed automatically and dynamically, spinning new servers up as needed and shutting them down as demand ebbs.  The user pays only for servers while they are running, producing high reliability and significant cost savings.  In fact, serverless computing, known as Function as a Service (FaaS), in which no particular server (virtualized or actual) is dedicated to performing computing tasks is becoming increasingly common. AWS Lambda is a prime example of FaaS.

Usage Scenarios and Context Today

Disintermediation and user self-service are goals and requirements of modern application systems.  It is simply unacceptable, today, for a company to fail to remove unnecessary human impediments between itself and its customers, vendors, business partners, employees and associates and their goals and requirements.

A common option is to provide information or services that would traditionally be provided through a remote application simply as an API that an external user can call and incorporate into his environment as best suits his company’s needs.  Thus, what were applications are now services, a seminal theme of today’s architecture.

The lean startup process of establishing and growing a business, even a new business unit within a larger company, is predicated on minimizing investment in unnecessary operating capabilities, specifically because going to market with an immature operating model is antithetical to the ability to design operational infrastructure, to say nothing of dedicating financial resources to it.  Simply put, few startups succeed for any length of time and none that do look like what they were originally expected to after they undergo a few inevitable rounds of evolution.

Ultimately, two very important aspects of what is possible today drive approaches to technology-driven business evolution—velocity and granularity.  The ability to erect systems with advanced capabilities and attach them to enormous sources of data with remarkable speed, coupled with the ability to put them into production in a nascent but usable state and evolve them in place in discrete steps result in the ability to change the tires while the car is driving down the highway.  This has profound implications and impacts across almost every product and service produced and delivered in the economy of the US and world markets.

Juxtaposed with this are many corporate infrastructures rife with now-outmoded, yet still-operable foundational components in companies that had focused relentlessly on minimizing redundancy for many years.  The result of this was large shared-services organizations with substantial pools of dedicated assets and core applications that are relied on by many different business units.  This can become a substantial drag on their ability to reorganize or effectuate acquisitions or divestitures, events which are increasingly common today.

The need to keep things running under the pressure of doing more with less has resulted in outsourcing, loss of in-house expertise and eliminating the staff needed to effectuate any transition, to say nothing of something as important and broad in scope as the digital transformations that most established corporations are facing today.  A number of industry analysts and strategy consultancies have opined on the issue of how to deal with this and one thing some of them have advised is bimodal IT, an approach in which some of the IT capabilities are focused on older technologies and systems built in them while the remainder is focused on mastering the latest and greatest and cutting a new path.  To put it bluntly, many analysts think bimodal IT is a terrible idea (see this Forbes article) and I agree with them, for reasons I will address later.

The Challenges

In the end, the scope of the challenges is coming into focus and includes opportunities and threats, risks and rewards:

• Aging systems represent a significant drag on agility, engendering excessive costs and requiring an aging and diminishing pool of support staff to run.
• Past efforts to minimize redundancy and share resources among business units has made it more difficult to separate them from one another and complicates reorganization or divestiture when it is advantageous.
• The advantages in speed, agility and cost reduction available through adopting modern technology, architecture and cloud-based implementation are creating increasing strategic pressure on enterprises that don’t employ them. Companies not burdened with outdated information technology are at a significant advantage.
• How to execute a transformation from legacy infrastructure to embrace current tools and practices is a fraught one. Facing the challenge, deciding how much to bite off and how quickly to proceed can be an existential challenge.

In the final post of this series, we will explore these issues.

BIO:

Howard M. Wiener is Principal of Evolution Path Associates, Inc., a New York consultancy specializing in technology management and business strategy enablement.  Mr. Wiener holds an MS in Business Management from Carnegie-Mellon University and is a PMI-certified Project Management Professional.

He can be reached at:

howardmwiener@gmail.com
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