Are you Ready to WARP into the NextGen Business Insights Service Center?

Today we live in a world where everything and everyone is connected. People to machines, machines to machines, even animals to machines; everything seems possible and it is happening right now. In this connected world, data is floating from one place to the other, with an increasing belief that it can be leveraged to create business value. On its own, this data already has value, but combined with other data, the impact is potentially overwhelming. But the road ahead is not easy and often unclear. 
All data is relevant. It is not only about big data. Small data is also important. One tweet can make a difference in your digital interactions. The challenge however is in knowing which data is relevant or can be relevant in time. What data should be selected from the dispersed data sources available both inside and outside the corporate borders?  Adding to that complexity  is how to leverage the existing investments in technology, like enterprise datawarehousing and business intelligence. But there are many more issues waiting for a solution, for example: “I have multiple views of key master data like customer, vendor, products, resulting in extra costs of maintenance, support” or “What data should we retain and/or which data could we archive?”. Overall, organizations seems to struggle with bringing down the complexity and cost of the data landscape, while at the same time there is an increasing need for leveraging the value of this same landscape. In other words: how to save money on data, while making money from data?
Understanding above mentioned dilemma is one thing, acting on it quite the other. This has triggered many managers in asking the question: what does that next step look like? In order to properly understand what data can do for your organization, and what the roadmap looks like, first you need to better understand where you are. Understanding the maturity of your current data landscape is crucial; it is the centre on which anything balances and turns. Also how you look at the maturity of data, the perspective or lens, is very relevant. For example, looking from a cost perspective might drive you in one direction (like offload to Hadoop or data archiving), while addressing the need for customer intimacy leads to different paths (Like NO SQL for unstructured Social media data in combination with Customer Value Analytics).
Capgemini can help customers make an informed, metrics based decision, on their data roadmap using our Data WARP© solution . This 6-8 week assessment methodology helps measure the maturity of all the components of your data landscape using four specific lenses or views: Transformation, Insights, Managed Services and Platform.

  • Transformation lens; focuses on the alignment between business and IT. How can they deliver relevant insights while using new technologies like Hadoop?
  • Insights lens; focuses on analyzing the data and creating relevant insights to be delivered at the right time and place, at the point of action.
  • Managed service lens; looks at the low cost, high-performing delivery of your development and maintenance.
  • Platform lens: this looks at your cloud readiness. Are you ready for a platform or even Insights-as-a-Service?

As an output of our Data WARP, we provide 3 fact based deliverables, that enable the organization to take an informed decision about the next step in the data landscape:

  • Rationalization Design: your data landscape maturity mapped to the components of our Capgemini BISC framework (Business Insights Service Center);
  • Transformation Roadmap: how a possible BISC implementation could be done in various stages;
  • Business Case: business & IT benefits you will realize through an BISC implementation.

A best practices reference framework like the BISC can help you master your data (industrialized factory delivery services) and generate insight (innovative strategic services), but as a first step towards this BISC can be the Data WARP. This tells you how to get to the optimum data landscape (transformation map), what it will look like (rationalization design) and how your organization will benefit from it(business case). In all – a clear path to next generation insights enabled by business-ready data.

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