Architectures for Digital Transformation

Corporations investing in digital transformation must leverage different architecture domains in the planning stages of their projects to react to digital transformation initiatives. Companies that are using and making available their enterprise and business architecture roadmaps within their organization understand a lot better the power of business architecture to communicate adequately with their business and IT stakeholders and deliver customer-driven initiatives in conformity with the organization’s strategies.

In today’s highly competitive digital landscape, organizations depend on information technology and software products to differentiate themselves. Enterprises must meet a whole number of stringent requirements, concerning high productivity, quality assurance, multi-functionality, simplicity in use, and of course, competitive price. These factors entirely depend upon the architecture of the software system. In essence, the architecture of the software system plays an imperative role as it represents a set of structural components and design solutions. It is the architecture that makes a software product capable of fulfilling the tasks it was designed for.

The below depicts the canvas for starting a digital transformation journey.

A business capability is a particular ability or capacity that a business may possess or exchange to achieve a specific purpose or outcome.

Critically, a business capability delineates WHAT a business does without attempting to explain how, why, or where the business uses the capability.

It creates a business view understood both by Technology and Business.

An example of a business capability is Loan Product development, and the process would be develop loan product.

A business capability map is essential to develop a business capability.

Architecture domains can be broadly classified as

1. Solution Architecture
2. Technology Architecture
3. Data Architecture
4. Application Architecture

Solution Architecture

Solution architecture (SA) is the practice of designing comprehensive solutions to address specific business problems or fulfill particular business needs. It involves creating a blueprint or plan for integrating various components such as software, hardware, networks, processes, and services, into a cohesive and effective system.

Key artifacts of Solution architecture

1. Data-centric solution Architecture diagrams -Reporting and Analytics
2. Application-centric solution Architecture diagrams -CRM

Example use case: -A financial institution that wants to better protect its customers' accounts and transactions. Solution architecture can help address this business problem by designing a comprehensive fraud detection system.

Enterprise Architecture

This architecture ensures that the right business problem is solved in the right way. Enterprise Architecture (EA) has long been recognized as a critical enabler of business transformation and optimization.

The Architecture Development Method (ADM) is the core process that guides through the phases of developing, implementing, and maintaining an enterprise architecture. The ADM is a cyclical and iterative process that allows to adapt to changing requirements, stakeholder feedback, and emerging technologies.

Architecture Deliverables are the outputs of the architecture work that document the architecture decisions, models, views, and specifications. They are organized into four categories: Baseline Architecture, Target Architecture, Transition Architecture, and Architecture Requirements. Each category has a set of deliverables that correspond to the phases of the Architecture Development Method (ADM).

Example use case: - Addressing the challenges of an Insurance Company facing digital disruptions from tech enabled competitors. This requires implementing a new IT architecture to leverage data analytics and AI.

Data Architecture

A data architecture describes how data is managed--from collection through to transformation, distribution, and consumption. It sets the blueprint for data and the way it flows through data storage systems. Without common standards for data integration and data management, organizations will struggle to derive meaningful results from their data.

Example use case: -Modern data architecture powers a myriad of business use cases today such as fraud alerts on personal bank account activity and IOT (telematics) based transportation improvements.

Key Artifacts of Data Architecture

1. Logical data models
2. Physical data models
3. Conceptual Data models

The underlying principle of Data Architecture:-

The difference between technology and business architecture.

This is a key concept to understand and as it implies Technology architecture is technology focused and business architecture is business focused.

The below is the conceptual framework that divides the two architectures.

Architecture principles

Architecture principles can be broadly classified in the following 4 categories

1. Business principles
2. Data principles
3. Application principles
4. Technology Principles

Conclusion

A good approach to architecture can enable Organizations to drive market-driven innovations such as personalized offers, real-time alerts, and predictive maintenance. Many Organizations require careful re-architecting of the existing data platform and infrastructure, including both legacy technologies and newer technologies previously bolted on.

Major global cloud providers such as Amazon (with Amazon Web Services), Google (with the Google Cloud Platform), and Microsoft (with Microsoft Azure) have revolutionized the way organizations of all sizes source, deploy, and run data infrastructure, platforms, and applications at scale through re inventing the strategies and business capabilities.