While there are benefits to be gained, like using the market buzz to reduce the time taken to change product features or the product mix, enabling targeted promotion and prompting shorter analysis cycle time, the picture around Big Data adoption is still fuzzy — as is usually the case with any new emerging technology.
Big Data appears to be a technology-driven movement and its strategic importance requires special focus and attention during its adoption, owing to the following:
- The technology to support Big Data is evolving rapidly and will take some time to mature.
- The effective utilization of Big Data requires a change in mindsets regarding the way it is used. While other technologies help solve problems like streamlining the inventory management process or providing an online system enabling the order shipment tracking on a real-time basis, Big Data helps find the problems that require attention. For example, the combination of factors that causes defects in the manufacturing process, or the factors contributing to the sales differential between two stores.
- While the three Vs (Volume, Velocity and Variety) have been regularly used to define Big Data, the use of technologies that support Big Data are not confined only to the way the three Vs are defined. Their usage has a much broader scope when correctly analyzed from the organization’s perspective.
A key factor in the success of any new program is the way it is approached from the inception itself. Any Big Data program that requires the integration of data with strategic planning is going to be critical and will carry heavy penalties in case of failure. The right framework to enable the adoption of Big Data analytics within the organization must be adopted.
The critical components of this framework include the following:
- Data discovery
- Analytics discovery
- Tools and technology discovery
- Infrastructure discovery
A Big Data adoption program should be viewed as a holistic program that is driven iteratively over a period of time by critically examining the assumptions made in earlier iterations, and weighing the business benefits derived from the results as well as the level of maturity / stability achieved with respect to broader business strategic objectives. The different phases (mentioned above), when carried out on a continual basis, will help establish a robust Big Data analytics environment that supports the strategic decision-making process by augmenting it with data-centric analysis and predictions.
The Emerging Big Returns on Big Data: How are companies investing in Big Data and deriving returns from it? We surveyed 1,217 companies in nine countries across the globe. Of these companies, a little more than half (643) said they had undertaken Big Data initiatives in 2012. Read TCS 2013 Global Trend Study.
TCS' Big Data Solutions and Services | View Infographic