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25 January 2017

The Key Principles of Data-Driven Business Transformation

Posted by: Vishal Adsool

Digital Transformation is no more just a buzzword. IDC predicts that by the end of 2017, two-thirds of the CEOs of Global 2000 companies will have digital transformation at the center of their corporate strategy. Today’s age of disruptive innovations and constantly evolving economics have made organizations, small as well as large, take their Digital Transformation initiatives seriously. Only then they will be able to sustain, grow, and lead in the future.

Today, Big Data and Analytics are at the center of digital transformation promising the companies to completely transform the way they do business, interact with their customers, and manage their internal processes. Data-driven strategies are increasingly becoming important to create competitive differentiation.

To achieve the desired business impact, organizations need to focus on two important aspects – One, a clear strategy and vision as to how and where to use data and analytics and use the right technology framework, tools, and technology.  There needs to be an integrated strategy for data sourcing, data modeling, and transformation within the organization.

Through a well-planned and well-executed data-driven transformation, enterprises can:
·      Gather and analyze a wide range of structured and unstructured data and leverage that for better business planning, budgeting, and decision making
·      Effectively predict more accurate outcomes instead of relying on old financial reports, traditional forecasting methods or mere gut feeling
·      Gather real-time insights into the opportunities and threats and take decisions based on the changing market events and economic movements
·      Make better business decisions based on the crucial financial and operational information and competition
·      Effectively measure success or failures of various business decisions and tweak the business strategy accordingly
The key principles of Data-driven Transformation are –
#1 Define the objectives
The clearly defined business objectives must drive the data-driven transformation. Only after finalizing the objectives, one can design the roadmap for leveraging the right data and technology. Through appropriate alignment of data, technology, and business, the right processes and business models can be changed.
#2 Choose the right data
Today, a vast amount of data is being generated and gathered and the volume of information is growing at an extreme pace. The Internet of Things (IoT) is bringing in unprecedented volumes of data with it. Unless the businesses have the right strategy to break the data silos and manage the new velocity of data, it will be impossible for them to leverage the data and get the actual views of their business environment. Businesses need to leverage the new technologies to select and gather specific data sets which are important for their business needs.
#3 Build the appropriate analytics models
While data is extremely important, what is even more critical is the analytics model which can allow the business managers take the right decisions and optimize the outcomes. The right way to build the most suitable analytics model is to define the desired business outcomes and build a model that can improve the business performance.
#4 Build data culture
One of the crucial factors for the success of data-driven business transformation is to build a data-driven organizational culture. The members of the organization and the relevant stakeholders need to understand and be convinced on how to leverage data. To influence the culture change, the Chief Data Officers can help the members of the organization understand how the data can help in different styles of decision making, how stakeholders can engage with the data, and how measurable business outcomes can be achieved through the data and analytics initiatives.
#5 Measure success and failure
To ensure that the data initiatives deliver the desired business impact, it is important to constantly and critically measure the success and failure. The focus needs to be on insights as a crucial KPI.
#6 Care about data privacy and security
If the data is not handled by taking care of the critical aspects of security and privacy, it can expose the business to not only bad and unreliable decisions but also to other severe threats. Data security and privacy, therefore, should be of prime significance. It is also important to ensure that the contractual, compliance and regulatory guidelines with respect to data are adhered to.
#7 Provide actionable insights  
The data-driven insights are useful only when the insights are actionable. The members of the organization should be able to take tangible actions from the data – and that too, in a timely manner. Unless the insights are provided to the “point of action”, it is difficult to gain the real value from the data and analytics.
If you find that your business is not sufficiently leveraging the data, it is time to consider data-driven transformation seriously. As we saw, while the use of big data and analytics techniques is important, the success of the initiative depends heavily on the solid foundation, systems, processes, and of course, people.



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