Every business now wants to undergo digital transformation because of the lessons that the pandemic left. The key to any digital transformation lies in the data-first approach. Companies can create risk models and business innovations based on digital intelligence using this approach. In addition, it helps reduce the complexity of the data, which helps save time and effort while producing the revenue of a business.
The Importance Of Data First Approach In Digital Transformation
Firstly, the data-first approach gives businesses a competitive advantage to move faster than their competitors. For instance, by drawing a comparison of the performance of Speed Test and Cox based on data, a firm can decide the tool which requires more marketing efforts to improve the revenue. Studies indicate that companies which use data first approach in digital transformation increase their chances of exceeding the revenue goal by 10%. In addition, these companies are further resilient to data loss and help increase employee job satisfaction. Also, their chances of beating their competitors with innovations increase by 20 folds.
In the dynamic marketing world, businesses often rely on fragmented platforms and channels for collecting various data. A few of the data are static, while the others are real-time; regardless, it can help businesses to grow. The data-first approach helps create alignment in all aspects of digital transformations. Consequently, it allows enterprises to plan right and strategize their business models.
The Challenges Of The Data First Approach
Starting with a data-first approach is challenging for many businesses because it is tough. Most of the challenges come from the cultural shift within the company because of the data transformation resulting from the data-first approach. In addition, other challenges of the process include prioritization of the correct data, the collaboration between the team members, the starting steps of the data first approach and the tools required to engage in it. Despite the challenges, it is critical to have a data-first approach because of its massive benefits.
How To Get Started With Data-First Approach?
The first step to getting started with a data-first approach includes defining the digital transformation for the company. Every business has its own set of goals and priorities. Moreover, even though the ultimate aim of a business is to earn more profit, the process of reaching the goal is distinct for different businesses. Therefore, it is important to define a company’s digital transformation based on its objectives and milestones.
The second step includes creating a robust plan to help achieve the digital transformation. One should formulate the project based on key metrics, data points and insights. A proper data strategy and a tech enablement plan are also required for the same because we are talking about digital transformation here. Monitoring the data can help businesses to create the right plan for the company.
Thirdly, the leaders should create a data-first ecosystem within the business. To create a data-first ecosystem, employers need to upscale the employees’ digital skills. It is possible to achieve this through different employee training methods. In addition, collaboration between the various stakeholders is a must to work on the digital infrastructure. Cross-functional collaboration is more helpful in this scenario. Finally, the foundation of the ecosystem lies in using the right technological resource to get started with the data-first approach.
Monitoring Of Data-First Approach
After the rollout of the data-first approach for digital transformation, frequent monitoring of the process is crucial. Monitoring the data-first approach helps businesses to identify the level of data maturity in business transformations. The first stage includes limited centralized data. In order to step to the second stage, companies need to engage in data transparency and governance. In the third stage, the business is cloud-enabled, and the implementation of data lifecycle management happens.
The key feature of the fourth stage includes engagement with multiple public clouds, data portability and automation. Finally, companies reach the last stage of maturity with the implementation of AI and Machine Learning across the business for making the necessary decisions.
Even though digital transformation using the data-first approach is daunting at the initial level, it is possible to simplify the process. The first step towards it involves breaking the goal into identifiable steps followed by proper prioritization of the actions. It is then followed with measurable but consistent improvement according to the requirement. Businesses can further enhance this process by ensuring a digital culture to define the role of data within the organization.