AaaS part I: Decision making and the Data to Insight conversion rate
AaaS part II: The Tool-approach is something for the past
AaaS part III: Analytics-as-a-Service is the current best practice

We at Capgemini have delivered Analytics-as-a-Service (AaaS) to our most data-driven clients for some while now – and every week new clients are asking for AaaS. With the attributes of scalability, no upfront capital expenses, only pay for what you use and available on-demand, AaaS is a winning strategy – for all parties. The most obvious difference to traditional analytics solutions is the way you pay for it. However, let us look beyond the numbers and study the underlying business culture and why AaaS is a game-changer.
A common theme among our clients is the struggle to improve the data to insight conversion rate. The hurdles are found at all levels of the organization including IT, business and leadership. 

Comments on the struggle to improve the data to insight conversion rate.

This is not headline news; we have heard it all before. Still, the business and decision-makers are thirsty for analytical insights. The traditional processes for software delivery, procurement and system management, do not generate a robust business case that positively impacts both business and IT. The initial investment (CapEx) is generally high for introducing new technologies from the analytics arena. Once the new technology is in place further direct and indirect costs will add to the IT-budget due to increased complexity of the IT-landscape (OpEx). With this background I understand that organizations struggle with acquiring a competitive data to insight conversion rate

In the third and final post in my Analytics-as-a-Service series, I will outline how AaaS is improving the data to insight conversion rate and how it will result in almost instant value to the business.