How Engineering Transformation Can Facilitate Digital Transformation

By Rekha Kodali

The ability to adopt change faster, scalability and repeatability are the key challenges in digital transformation initiatives, which often magnifies the time, cost and associated risks in achieving the desired outcome.

Engineering transformation is essential for institutionalizing technology thought leadership and best practices (across people, process, information and technology perspective) to help improve enterprise agility, adopt new ways of working, reduce cost to serve and thereby enabling additional investment driving enterprise-wide innovation.

In this blog, we will look at how engineering transformation, which includes next gen app engineering and next gen collaboration, can influence faster digital transformation.

1       INTRODUCTION

Digital transformation involves increase of the next gen app development. This has lot of challenges like a huge learning curve, lack of reusability etc.

Enterprises need a low code Next Generation Engineering Platform, which is an abstracted as-a-service computing and orchestrated delivery ecosystems, to address the above challenges.

The next generation ecosystem platform provides abstracted and standardized environments that enable on-demand self-service and automates the repeatable tasks from initial planning through provisioning to deployment by orchestrating various processes and tools and by integrating with enterprise’s existing systems.

Next gen app Engineering Platform provides standardization of common practices, work across the SDLC to enable value-add service that enables teams to create solutions much more quickly.

Engineering Transformation Challenges: Enterprises shifting to the path of faster application delivery, need modernization of their today’s architectures, applications, technologies and platforms with changes in the culture and structure of their delivery organizations.

    • Complex Development Environment
    • Difficulty to bring in Agility and innovation
    • Not know whom to reach out to
    • Time Consuming Learning Paths
    • Lack of standardisation

An approach to Next Gen Engineering Transformation: Transformation to Next Generation Architectures includes Adoption of Cloud Native, Digital, APIs and Micro services and enable Continuous Delivery & DevOps Transformation.

To enable an advanced approach to developing applications, creating an adaptive, composable app creation process and be future ready we need a next generation application development platform. This would ensure velocity, acceleration in development as well as innovation.

  • A platform which is intelligent and learning alongside the factory operations.
  • A process by which people can update and improve the knowledge, access it, and improve it.
  • A culture in the team of sharing, and learning, Gamification, Responsiveness and ratings

The main features of such a platform are given below which includes:

  • Self-Service: This would include AI enabled Bot to enable employees for self service
  • Assembling APIs: This would enable a number of personas to create applications easily without a deep knowledge in the technologies.
  • Self-Service: Enables developers / architects to consume services and build applications in a much faster way by bringing in AI Capabilities. This consists of knowledge hub, Best practices, Academy and Collaboration tools, Communities, Assistants and Bots: This helps in easier collaboration and community participation helping in improving developer productivity. An AI Knowledge Framework for Collaboration: Captures all of the organically built knowledge across the Whole journey across Repositories, communities, tools, blueprints People, knowledge and tools.
  • A repository of tools which are recommended for developers to be as productive as possible for each different Pattern/Use Case all in one place. This enables storing all reusable assets / apps. It has cognitive capabilities inbuilt to suggest the right artifacts to the developers be it best practices, guidelines, checklists, code snippets, APIs, reusable apps This improves the productivity of the developers. An element of gamification helps in motivating users to contribute to the Knowledge Hub.
  • Assembling APIs/Applications:
    • Assembling applications becomes easy with the use of AI cognitive capabilities and Bots.
    • Knowledge Hub – Reusable Building Blocks – Patterns and Practices, APIs and solutions help in capturing patterns and best practices across the SDLC helping reusability of patterns and best practices
    • Learning Services help in harvesting learning and best practices and guidelines.
    • Platform Services – Common services can be managed by the central team so that product or application teams can focus on building the business logic for specific products or applications etc.
    • Artificial Intelligence: This plays a pivotal role across the SDLC by bringing in cognitive capabilities like Intelligent Search, Q&A bots

Next gen app engineering platform: Enterprises need a Next Generation, which is an abstracted as-a-service computing and orchestrated delivery ecosystems, to address the above challenges.

The next generation ecosystem platform provides abstracted and standardized environments that enable on-demand self-service and automates the repeatable tasks from initial planning through provisioning to deployment by orchestrating various processes and tools and by integrating with enterprise’s existing systems.

Next gen app Engineering Platform should provide standardization of common practices, work across the SDLC to enable value-add service that enables teams to create solutions much more quickly.

A comprehensive platform, which can take care of the above aspects, is explained in the following section:

Next Gen App Platform consists of:

  • Reusable Building Blocks – Patterns and Practices helps in capturing patterns and best practices across the SDLC helping reusability of patterns and best practices
  • Platform Services – Common services can be managed by the central team so that product or application teams can focus on building the business logic for specific products or applications
  • Developer Ecosystem, Self-Service: Enables developers / architects to consume services and build applications in a much faster way. This consists of knowledge hub, Best practices, Academy and Collaboration tools, Communities, Assistants and Bots: This helps in easier collaboration and community participation helping in improving developer productivity. An AI Knowledge Framework for Collaboration for storing all reusable assets / apps. It has cognitive capabilities inbuilt to suggest the right artifacts to the developers be it best practices, guidelines, checklists, code snippets, APIs, reusable apps. The developers using the AI Framework are assisted by smart bots. This improves the productivity of the developers. An element of gamification helps in motivating users to contribute to the Knowledge Hub.

To enable an advanced approach to developing applications, creating an adaptive, compostable app creation process and be future ready, Democratized Tools will support businesses to assemble Application Experiences. Organizations will use democratized design and development tools, augmented by artificial intelligence (AI), to draw on business capability marketplaces and custom development to create business application experiences. Integration will be an essential enabler of new application experiences. At runtime, assembled application experiences will operate on a hybrid integration platform that provides governance, security, interoperability, scale and adaptability.

Rekha’s core competency, accumulated over 22 years of professional experience, includes enterprise architecture and Microsoft technologies. She has designed large solutions on a multitude of technologies and acquired various industry-recognized certifications, which include TOGAF 9.0, Azure AI, IASA, Azure and other Microsoft certifications. She has co authored and published a book ‘Developing Cloud Native Applications in Azure using .NET Core’