At a time when information is dubbed the oil of the 21st century and analytics is the combustion engine, effectively dealing with big data is crucial.
The web is full of examples of organisations that have used big data and analytics to optimise their business operations and make better, faster and more informed decisions. They have built analytics frameworks on their existing data to get more insights about their business, helping them to manage financial risk, improve the supply chain, design new products and launch more impactful marketing campaigns. The fact is that today’s most successful organisations are those that have a deeper grasp of their data.
While a large number of companies have already started embracing the benefits of big data and analytics, there are still a significant proportion of companies who are finding it difficult to leverage big data technologies and build a data driven organisation. They are finding it difficult to identify exactly which kinds of data that they should collect and how they can get value out of that data. This is complicated further by the rapidly changing big data ecosystem.
It has become important for business leaders to start taking a pragmatic approach towards big data adoption. They should start with defining a core set of data governance guidelines to define the requirements for big data that will help them choose the right data and manage multiple data sources adding to the data veracity. They should also start building the analytical capabilities that will help them to start realising insights from data. The most important part of big data adoption is that management should initiate and drive an organisation-wide transformation programme to ensure that big data insights are being applied and generating effective frontline action.
The future for a successful organisation will depend on how they are treasuring the data of their client facing systems and their ability to build know-how for targeted marketing and business insights. The companies failing to capture this value will find themselves losing against their competitors. Businesses need to understand that competitive data is like gold dust – they need to process millions of tonnes of dust to find the almost invisible gold strands.