The Role of Data Analytics in Digital Transformation

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The imperativeness of digital transformation has become more prominent in post pandemic new normal economy to deal with various disruptive factors threatening organisational efficiency and sustainable value creations. The digital transformations help organisations to increase efficiency, greater business agility with the ultimate objective of unlocking of new value for stakeholders like employees, customers, and shareholders.

Organisations drive Digital transformation by embedding technologies across the business functions and verticals to drive fundamental change and bring a cultural shift to deliver indelible customer experience in rapidly evolving customer behaviour patterns and market dynamics. It also overhauls the way an organisation operates impacting on systems, processes, workflow, culture etc., It overhauls an enterprise’s traditional sales, marketing, and customer service operations.

This transformation brings into prominence the critical role data and analytics play in an organisation’s digital transformation as it affects each level of an organization and brings together data across areas to work together more effectively echnology, and necessary infrastructure to be more agile and competitive to create high levels of engagement of suppliers and customers. This could mean adopting digital technologies to revamp or change the processes which will enable the organisation to analyse customer behaviour and attributes to hyper-personalize its product/service offerings and provide a better customer experience compared to competitors. This requires a consistent focus on relevant data and analytics because the two are key accelerants of any digital transformation agenda and initiatives.

decisions based on the quality data. The interdependence of data and analytics can be seen from the fact that data provides the information, analytics provide the insights that lead to informed decision-making. Using data and analytics as the thread that carries organisational digital transformation process—before starting and throughout allows the management to overcome key modern business problems that can be regarded as impediments to successful data initiatives.

Digital Transformation requires effective Data Strategy and Data Management Plan. Data Strategy largely highlights the usage of data to support business goals and analyse business problems to drive business forward in a digital economy. It provides insights to the organisations to understand the customers and their needs intimately well. 

The following pertinent questions any aspiring organisations need to explore before embarking on digital transformations:

⮚ How can the organisation gather and apply data to support their business goals and solve business problems, and ultimately drive the business forward in a digital economy?

⮚ Where is this data sourced from and is it of good quality? Will it provide adequate insights enabling the organisations to better understand customers and their needs?

⮚ What processes are required to ensure the accessibility of reliable data?

⮚ What technology will enable the storage, sharing, and analysis of data?

Analytics add value to the data. Analytics plays critical role in analysing raw data to draw out meaningful, actionable insights to draw conclusions, make predictions and drive informed decision making. It is imperative for the Organizations to use data analytics with proactive, future-casting capabilities otherwise they may find business performance lacking because of their inherent lacking ability to uncover hidden trends, patterns and gain other valuable insights.

There are four types of analytics, Descriptive, Diagnostic, Predictive, and Prescriptive. The chart below highlights the levels of these four categories. All these four categories are compared on a scale of Value and complexity. It reflects the amount of value-added to an organization versus the complexity it takes to implement.

As one embarks on analytics journey, it is important to understand the four types of analytics and how they work together to deliver value. Starting with Descriptive analytics to answer what has happened, to understand why it happened through Diagnostic Analytics.

Once this is accomplished, a Predictive analysis can be applied to understand what will happen next, leading to Prescriptive Analytics to recommend the next best activities to employ.

However, the best type of data analytics for any organisation depends on their stage of development. Most organisations are using analytics which only churn out insights to make reactive and not proactive business decisions.

More and more forward looking and tech savvy organisations are adopting sophisticated data analytics solutions with AI or machine learning capabilities to make better business decisions and help determine market trends and opportunities.

Therefore, it is highly critical to have insights about the market and customers for business success. In today’s digitized world, organisations need a sophisticated data analytics solution that integrates the best of analytics and data management capabilities to access the data and analyse the information organisation need when and where they need it quickly and easily. Leveraging information to take proactive decisions and actions beating the competitors are key to organisational success and sustainability.

Some of theprograms offered by Westford Uni Online, such as MBA in Global Business Management with Marketing Intelligence and Big Data and MBA with Business Analytics offer extensive insight into the study of Data Analytics that has been playing a significant role in the trend of digital transformation. These internationally accredited programs offering UK quality education and degrees are serving as a pathway for professionals to contribute to as well as create successful business models that will remain sustainable in the future.

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