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The New Digital Edge – Everything about Digital Transformation and Our Approach

  • By Cygnet.One
  • October 6, 2022
  • 5 minutes read
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Every digital transformation is going to begin and end with the customer, and I can see that in the minds of every CEO I talk to.

Marc Benioff, Chairman & Co-CEO, SalesForce

Digital transformation – what and why?

Digital transformation- The definition

Digital transformation is the process of using technology to create or improve the existing digital landscape addressing and improving business processes, customer needs, sales, and marketing requirements.

It can be applied to Greenfield or Brownfield ecosystems. There is potential to leverage improvement with continuously changing market needs that are not just restricted to technology or competition.

Why digital transformation?

Value for business is at the heart of any digital transformation, these value drivers are customers, partners, and processes driving businesses.

With the pandemic and its ever-evolving variants, the need of such transformation has increased by manyfold reasons being constraints introduced, but businesses still need to keep a focus towards it, irrespective of environmental constraints involving human intervention be it back office, sales, customer representatives, or marketing.

For most organizations, covid was a revelation, as the pandemic hit businesses hard, due to their digital ecosystem’s inability to meet their existing customer needs, ease of onboarding, etc. processes that slowed down and dragged businesses which impacted revenue and sales. A slower response from customer support resulted in poor customer satisfaction. The business was not able to fulfil orders resulting in poor customer experience are a few of the sightings which made businesses think to improve their IT and Non-IT processes acting as a key drivers for digital transformation.

Need for any digital transformation starts when a business starts feeling sluggish in terms of “Low or slowing down of revenue, people and process inefficiency, customer churn, older or poorly performing IT systems, integration issues, unavailability of right data at right time due to siloed business verticals, etc.”

What is digital engineering & why does engineering follow digital transformation?

Digital transformation starts with the need to improve the pointers mentioned below, but it will end up most of the time in an engineering activity unless it is just a human process inefficiency, but even at the time to address human inefficiency if the landscape allows businesses move to process automation tools for redundant processes, which in turn improves process efficiency and reducing cost. Key areas during reengineering involve and solely depend on the problem one is trying to solve, which can be one or multiple from listed below:

Approach to the digital transformation journey

Here is the list of the lifecycle of a digital transformation program & how it needs to be approached methodically.

1 – The first phase of any digital transformation starts with the following:

2 – Vision for transformation as “THE END GOAL”? Understand the where, what, why, who, and how architecture is done, else you may end up doing things that aren’t adding enough value for businesses.

3 – Identify and articulate business scenarios. This will help in identifying if we are meeting the vision of the “THE END GOAL”

This describes the fundamental organization of a business embodied in:

Business scenarios also help the highest value-generating area and what needs to be picked up first. The value streams should be created as part of the business scenario articulation refer to the sample below.

Value stream Example

Source: The open group architecture framework

Document Business scenarios using Activity, Class & use case models, which will be a good starting point for your business and engineering team alignment.

4 – Basis the business and value understanding, start documenting the data dictionary & architecture for AS-IS and TO-BE, this will help in migration strategy and data points won’t be missed during modernization & migration.

5 – Along with data, in a landscape of a legacy application, a data dictionary should be aligned and interwoven so that during engineering/modernization there is a good understanding of what should be touched and what should be left as it is.

6 – Once the data definition is available move on to application architecture, when in the transformation journey, try to have standards like TMF which is for Telecommunication, ONDC for the e-commerce India landscape, OMG for finance and pharma vertical and likewise, this helps to create a futuristic and application which is in line with market standards.

7 – Once the application architecture is in place along with data, think about the actual technology aspect (Hardware, Software, Network, On-Prem or SAAS, etc.), an important point to note business drives technology, but drivers for change are more often found in evolving technology capabilities

8 – Next, think about a Roadmap for transformation covering build vs buy decision-making, what will be milestones for value streams & priority, if you want to go with COTS or use an open source etc., and also what can be generated as reusable components and what cannot?

  • Are reusable components available then put them as a base during the roadmap definition
  • Demarcate milestones for the digital transformation journey
  • Decide by now If an incremental approach will be appropriate or an in approach

As a part of the digital transformation roadmap closure, finalize Data Dictionary, Application, Technology, and Feature sets, and have a clear identification of your TO-BE landscape.

Enterprise Applications and SAP

Approach to engineering and implementation

Things by now will look clearly understood by stakeholders and now move to actual implementation and migration plan (which is the most ignored activity in most transformation projects and sometimes not understood well till the last phase, what will go where? Migration is the most important reason for transformation projects failing, as the business will need their data as it was supposed to be?)

Implementation will have multiple incremental deliverables depending on if you are using Scrum, Kanban, etc. as methodology.

Typical artifacts & standards to be in place with KPI before starting implementation along with quality gates clearly articulated, to avoid late discovery of code & quality issues.

  • Coding standards
  • Code quality reports
  • Performance strategy covering Performance benchmark-KPI
  • Testing strategy (unit/performance/regression etc.)

DevOps need to be part of an integral part of the implementation and involved beforehand to ensure the following pointers are well in place before you start development

  • GITOPS strategy, Code Repository
  • Infra provision (DevOps, infra, etc.)
  • Monitoring/Observability, metrics measurement

You will keep iterating with your implementation cycle ensuring you are fulfilling milestones.

Digital transformation is a journey that should be incremental in nature and digital engineering should be in place to fulfil this journey and ensure both go in tandem to fulfil the need of businesses and reach the end goal for the purpose-driven organization.

As a new or existing running business, you need to keep evaluating your processes and IT landscape, try to identify what is working for you, and what is not, and at the right time take the necessary steps to get on track and emerge as a leader in your respective business domain.

“Problem cannot be solved, which is not understood well, cygnet’s team of experts will not only help you understand your digital transformation problem but also help in resolving this problem with its engineering capabilities”

Let Cygnet Digital be your technology partner in growth and innovation. Reach out to us today!

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Cygnet.One is a technology consulting and development company, that co-creates business growth strategies and delivers partnership value through the Power of Digital. We specialize in leading technologies such as Cloud Computing, AI/ML, and Blockchain with a focus on innovation and agility.

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