The digital transformation market is expected to grow exponentially in the next few years. We can view 2020 as a marker that led to the immediate need for massive digital transformation. In the two years that have followed, many companies have completely transformed the way they do business and embraced the digital world. No one wants to be left behind in the digital transformation race.
Every business wishes to grow exponentially in the digital transformation world. As per the latest statistics, the digital transformation market size in 2021 was evaluated at USD 608.72 billion. By the end of 2022, the market size value is estimated to reach USD 723.77 billion. From 2022 to 2030, the digital transformation market is expected to increase at a compound annual growth rate (CAGR) of 23.5%.
The significance of data as an organizational asset is now more than ever. The need to digitize has given rise to implementing data first strategy amongst organizations. The data-first approach is where digital transformation can be focused to solve traditional business challenges and deliver sustainable business growth. With the implementation of Data Science, AI, ML, Data Engineering, and Data Analytics, businesses can unlock the potential of data like never before.
How does the data-first approach prove to be effective in dealing with traditional business challenges?
The data-first approach is necessary to digitally transform and tackle different business challenges. Let us see how the approach is effective in combating traditional business challenges:
Low-risk levels, early rewards
The global pandemic has accelerated the need for digital transformation amongst businesses. However, providing remote data access securely and reliably becomes risky. This solution delivery method is complex when seen from an organizational change management perspective.
Taking the data-first approach enables businesses to see results quickly while minimizing the risks associated with the transformation. There is harmonization in the whole business system, where you can establish authoritative master data resources within the organization.
Implementation of new service and product ideas
Nowadays, businesses look for expansion to mark their presence in various domains and industries. They are extending confidently into new domains by using data and artificial intelligence. For instance, banking systems leverage data extensively to identify security risks and understand customer requirements.
Like retail banking, investment banks invest hugely in big data for smarter trading decisions. Analyzing crucial data also helps in understanding the current market. While extending into new domains, business priorities and demands keep on shifting. Implementing a data-first approach helps businesses to meet these new demands and challenges.
Dedicated focus on data
The harmonized data model experienced a complete shift in perspective after introducing the data-first approach. The traditional system consolidation project used a business plan as a central approach. Here, in the data-first approach, the complete focus is on the data and the data itself.
With data in focus, your business will need a specific talent pool, comprising data experts and analysts. These professionals excel in developing and strategizing various business approaches and procedures. The business process-focused team has expertise in various technical and technological process implementations.
Property and real estate management is a great example to explain this point. Many real estate firms use a data-first approach for better trend analysis, property analysis, and understanding of the overall market and customers. They are also streamlining the maintenance processes with this approach.
Contended workforce and sustainable business
Data-first approach helps in building future-proof workforce strategies for businesses. It provides a holistic and clear insight into the existing workforce and talent pool, various technological competencies, and much-needed future skills.
By implementing the approach, there is a significant improvement in operational efficiencies leading to sustainable business growth and development. It helps to improve data security and minimize unnecessary company expenditures. Businesses develop the flexibility to support ever-evolving and new business requirements. A data-first approach improves agility and responsiveness and delivers value quickly.
Conclusion
Technological evolution with analytics and cloud computing has marked its presence rapidly. Organizations not working on their data strategy and related processes may find it difficult to survive in the current competitive market.
One of the biggest challenges of a data-first strategy is the dynamic nature of data. It is not easily accessible, traceable, or secure. It flows through the organization in a structured and unstructured manner. Generally, companies go for technology without considering data, business needs, and goals. They adapt business as per technology rather than investing in the right technology for their goals.
The data-first approach is significantly changing the analytics and data landscape. Businesses gain a competitive edge over their business rivals by incorporating new components into their data strategy for digital transformation.
