Big Data as a Force for Disruption

Big Data Infrastructure

Big Data as a Force for Disruption

Vicky Falconer, Big Data Solutions Lead, Oracle Australia @vrfalconer


Big Data has the potential to create entirely new business models, services and products; it promises an exciting future

Intel

In previous blogs, we’ve seen how data is increasingly regarded as a form of business capital for creating new products, services and working practices. Indeed, a global survey conducted by Oracle in collaboration with WSJ Custom Studios found that 90 percent of executives said they consider the ability to garner insight from data vital to their company’s future.

It’s clear that businesses are aware of the value that data holds for them. By effectively managing and integrating big data and using analytics to interrogate information and create insights, businesses can bring dramatic and positive changes to their operations.

Vicky Falconer

Vicky Falconer, Big Data Solutions Lead, Oracle Australia

Of course, the uses cases will vary across different industry sectors – risk and fraud in financial services, the ‘next best offer’ in retail, or fraud analytics in government — but there is usually a main driver for big data projects, falling into three categories that follow-on from each other.

The second category is business model efficiencies. Examples include getting a better understanding of customers and enabling the next best action; driving down the cost of asset management; and bringing about better fraud analytics and risk models.

It’s common to see stage one as kick starting a big data programme with the second and third stages the logical progression of these. However, the disruption stage is increasingly seen as critical to the future of an organization, as it could mean getting ahead of competitors. It’s essentially ‘disrupt or be disrupted’.
To show how this plays out, let’s look at some examples of how businesses and industries are approaching big data with disruption in mind.

Generating new value from data

By making use of big data tools, existing datasets can sometimes be re-used for an unintended purpose. A number of retailers and financial service companies are taking this approach to create innovative new products and services.

  However much potential big data has, it’s true to say that one of the main challenges of embarking on a big data project is to find the use case and building a business case to support that. 

Customer science company, Dunnhumby, is a great example of creating a new business based on deep, rich and historic datasets from shoppers. The company helps retailers generate insights and build personalized experiences to help build brand loyalty.

Dunnhumby initially found it difficult to consolidate and analyse the huge amounts of data in its possession, meaning it also struggled with performance. By using the Oracle Exadata Database Machine and Oracle Advanced Analytics, the company was able to reduce time for key deliverables while enabling new analysis options.

In the financial services sphere, one Oracle customer is looking to create data products through the use of the ‘data lab’ concept to provide repeatable processes to deliver multiple new products to market.

The data platform

With some retail companies already offering customer insights to a range of other sectors, such as insurers, airlines and petrol retailers, a logical progression is to develop data platforms to provide this insight to third parties.

 The final, and potentially most interesting category, is utilizing data and algorithms to enable businesses to disrupt their existing business model or even the industry sector in which they operate. 

Retailers that traditionally operate on low margins could therefore use big data capabilities to drive higher margin value out of data that was previously seen as an overhead. In theory, this could enable a retailer to also become an advertising channel that provides deep customer insight.

The data platform also has a role in manufacturing. One global manufacturer has adopted the platform approach to create a global knowledge store through which its different divisions share company information on technology, markets and structure. This approach means that the data associated with each new product can add to the overall knowledge base and further fuel innovation across industrial sectors.

Channeling the power of algorithms

The use of big data to generate algorithms could lead a raft of uses cases, including personalized recommendation engines; machine learning for fraud and anomaly detection, and image analysis to detect empty car spaces or illegal parking. The NHS Business Services Authority in the UK has started to deploy projects such as these to identify significant savings within NHS dental services.

 There will be countless other ways in which big data can create disruption in the future, giving the exciting prospect that companies wanting to diversify or revitalize their business, will be able to reinvent themselves through the use of data. 

One use case currently being floated is the idea of city authorities using big data to model traffic flows and manage congestion in a dynamic manner across all roads not just toll roads. Dynamic pricing could then be utilized to manage the flow of traffic.

For example a driver could check a mobile app and select the amount they are willing to pay for the journey to take a certain amount of time. The app could then provide a route that would make this journey time possible, and charge the driver accordingly.

Alternatively, as congestion worsens on major roads, drivers could be informed by the app that the cost for the next 60 minutes is rising and that they can take an alternative route that will cost less, meaning the congestion is eased.

The uses cases described above are just the tip of the iceberg when it comes to the potential of big data to disrupt business models — and even entire vertical sectors.
There will be countless other ways in which big data can create disruption in the future, giving the exciting prospect that companies wanting to diversify or revitalize their business, will be able to reinvent themselves through the use of data.


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