By Umme Sutarwala - April 04, 2022 3 Mins Read
Established enterprises in almost every market category are under pressure to transform into digital organizations, with disruptive startups on one side and IT behemoths on the other.
One of the most imperative issues confronting today’s businesses is digital transformation. The necessity to employ digital technology to design and implement new business models compels companies to reassess their current capabilities, structures, and cultures in order to determine which technologies are pertinent and how they will be implemented in organizational processes and commercial offers.
Despite the numerous digital and analytics reforms taking place throughout the corporate landscape, few businesses are seeing the desired returns. According to the McKinsey Global Survey on the subject, the success rate is dangerously low. Approximately eight out of ten respondents indicate their companies have started digital transformations in past years, but just 14% claim their efforts have resulted in and maintained performance gains. Furthermore, just 3% of people say they have completely succeeded in maintaining their shift.
This layer is where organizations can truly leverage the power of data, create end-to-end integrated apps, allow AI algorithms to learn and adapt fast, and reproduce success across several business cases.
This is where domain expertise collides with cutting-edge digital technology, and digital transformation projects generate new ideas. Businesses may use this layer to swiftly test their ideas with the help of the engineering and business teams. The incorporated office automation and workflow algorithm can reside on top of the application layer. It should be tailored to the organization’s process in order to facilitate cooperation between different clients.
Businesses host their Data Lake, AI engine, and service engine on the platform. Building a data foundation, implementing a service-oriented architecture, and enabling AI capabilities are all feasible projects.
End-to-end, the data foundation should be cohesive and integrated. Businesses handle data collection, transformation, cleansing, validation, and modeling here, as well as providing consolidated, unified data services and data products. These will be their data assets that will be controlled.
Shared business abilities can be used across functions in a service-oriented architecture. They should be pre-built building blocks with data models that are tailored to the specific company.
Finally, in sales planning, fulfillment, logistics, and other areas, the AI engine should give cutting-edge AI skills in optimization, prediction, and intelligence.
Finally, the channel layer encompasses all external components that users or customers may view and engage with. The channel layer can provide numerous applications that are currently lacking, such as supplier relationship management, a B2C e-commerce platform, and a B2B marketplace, with good support from the platform layer and domain application layer. Applications will become more nimble when this layer is transformed, allowing them to meet the growing expectations of internal and external stakeholders.
All three levels are likely to be included in a successful digital transformation roadmap, although they don’t have to be planned in that sequence.
Umme Sutarwala is a Global News Correspondent with OnDot Media. She is a media graduate with 2+ years of experience in content creation and management. Previously, she has worked with MNCs in the E-commerce and Finance domain
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