BIG DATA IS a big business opportunity. It can be both disruptive and transformative.
Businesses of all sizes need to understand its considerable potential to keep ahead in this constantly changing market.
In the emerging field which refer to under the umbrella of Big Data, technology officers are finding new ways to reuse and extract value from information as many aspects of our everyday life increasingly become computerised.
The concept of a connected car is changing how that industry operates, for example. The new Tesla is a combination of an electric car and a smart phone, and customers are expecting the digital experience to continue from one to the other. For existing car manufacturers to compete, they will need to adapt to the transformation.
Every business can benefit from exploiting their data to deliver value in all areas of their operations, but most of them have little idea how to do this. As a relatively new and rapidly evolving field, businesses face many challenges in using Big Data technology.
Here are five key steps in building a big data analytics strategy – and examples of how they have already been implemented successfully:
1. Understand your business objectives
What are you trying to achieve for the business? Cost efficiencies? New business opportunities? A clearly articulated business vision is critical, together with associated goals and milestones. You should identify and prioritise opportunity areas.
Example: In 2015, Philips focused on the convergence of their consumer, medical and cloud-based technologies to enable data sharing and analysis, resulting in more effective, lower-cost integrated health solutions.
2. Put data at the heart of business decisions
Use data to drive decision making and keep the organisation ahead of the competition. This could start with a focus on critical business decisions and grow to include everyday actions where data analysis can make a difference.
Example: Farm machinery manufacturer John Deere is using the data from sensors in its farm equipment to help farmers manage their equipment, decrease downtime and improve fuel efficiency.
3. Encourage a data-driven culture
It is important to have an executive champion for Big Data, such as a chief data officer (CDO). But it is also important to drive adoption, create awareness and demonstrate practical relevance of data analytics for all areas of the organisation, not just in IT.
Example: Usama Fayyad was the first person to hold the title of CDO for Yahoo. In 2014 he was appointed to the same position for Barclays in London, where he is responsible for delivering their Big Data technologies for insights across the Barclays Group globally.
4. Make corporate data easier to discover and access
Simplify the process of discovering and accessing data within the organisation. Encourage business units to make their data available in easy-to-use formats and with self-service platforms for use by others within the organisation.
These efforts can be called many names, such as a ‘data hub’, ‘data lake’ or the emerging trend of ‘data spaces’. But the goal is simple, to bring your data together in a single place.
Example: A common trend now in many data-driven organisations, especially in the financial and insurance sectors, is to build a ‘customer data hub’ where information is gathered on all customers. Their analysts now spend more time extracting useful insights than trying to find the relevant data.
5. Leverage the business data ecosystem
The business benefits of sharing and linking data across domains and industry sectors is becoming more and more obvious. Look for opportunities to work with partners to combine your data for mutual business benefit.
Example: Going back to John Deere, that same sensor data can be linked to data on weather, soil conditions and fertiliser usage to optimise and predict crop production. This has opened up partnerships with other companies in the agri-data field.
Dr Ed Curry is a research leader at the Insight Centre for Data Analytics and vice president of the Big Data Value Association, a non-profit group set up to make European companies more competitive through data-driven innovation.
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