Five ways to capture Value from Big Data

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Five ways to capture Value from Big Data

Value of Big Data

The primary reason why Big Data has developed rapidly over the last years is because it provides long-term enterprise value. Value is captured both, in terms of immediate social or monetary gain, and in the form of a strategic competitive advantage.

Due to its wide range of applications, Big Data is embraced by all types of industries, ranging from healthcare, finance and insurance, to the academic and non-profit sectors. There are various ways in which value can be captured through Big Data and how enterprises can leverage to facilitate growth or become more efficient. Each of these drives the ʻdigital transformationʼ of organizations and have a long-term effect on the way the enterprises will have to be designed, organized and managed.

Enterprises can capture value from Big Data in one of the following five ways:

1) Creating transparency

Using the data of an organization to determine future decisions makes an organization increasingly more transparent and breaks down the silos between different departments. Big Data is analyzed across different boundaries and can identify a variety of inefficiencies. In manufacturing organizations, for example, Big Data can help identify improvement opportunities across R&D, engineering and production departments in order to bring new products faster to market.

2) Data driven discovery

As enterprises create and store more and more transactional data in digital forms, more performance data becomes available. Big Data can provide tremendous new insights that might have not been identified previously by finding patterns or trends in data sets. In the insurance industry for example, Big Data can help to determine profitable products and provide improved ways to calculate insurance premiums.

3) Segmentation and customization

The analysis of Big Data provides an improved opportunity to customize product-market offerings to specified segments of customers in order to increase revenues. Data about user or customer behavior makes it possible to build different customer profiles that can be targeted accordingly. Online retailers, for example, can tailor the product offering on their websites to match the current customer and increase their conversion rates.

4) The power of automation

The underlying algorithms that analyze Big Data sets can be used to replace manual decisions and labor-intensive calculations by automated decisions. Automation can optimize enterprise processes and improve accuracy or response times. Retailers, for example, can leverage Big Data algorithms to make purchasing decisions or determine how much stock will provide an optimal rate of return.

5) Innovation and new products.

Big data can unearth patterns that identify the need of new products or increase the design of current products or services. By analyzing purchasing data or search volumes, organizations can identify demand for products that the organization might be unaware of. Universities or colleges, for example, might study their website traffic and search volumes to forecast class enrollment and allocate teaching resources accordingly.

Besides the five ways described above, there are many other potential business gains or ways to capture value with Big Data. Many examples and business cases in this area already exist and more are designed almost every day. The main challenge for existing enterprises is then to translate this business value into tangible benefits. Our next post will therefore further discuss how to formulate a Big Data strategy.

By | 2018-07-31T08:18:45+00:00 July 31st, 2018|Categories: Big Data, Fundamentals|Tags: , |0 Comments

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