The information technology (IT) infrastructure in traditional organizations, particularly in the insurance industry, typically contains three components: 1) the legacy system, e.g. IBM mainframe for storing transactional data; 2) the distributed system, e.g. Microsoft Azure or Amazon Web Services for data governance and usage; and 3) the custom-made application system for analytics and reporting. In most of the organizations these three parts are still functioning as three disjoint pieces which I tried to depict pictorially in the image above. From my experience as a hands-on Data Scientist in a large insurance company I can tell with reasonable confidence that this is a serious problem. This setback simply means that the attempts of process automation are basically the automation of units but not the entire system. The industry needs an advanced technology that can thread all three units together to exploit automation in its fullest power.
What I call the Master Technology Solution (MTS) is an intelligent process where data collection, acquisition, preparation, data governance as well as the execution of advanced analytics and reporting will be one seamless progression where one can start from 1) extracting data in the legacy system, then 2) push data to the distributed system through ETL processes for profiling and governance etc., and finally 3) generate and host machine learning models, reporting, and maintaining versioned results in the application system. To me the desired tool of integration would be the one, such as the MTS, that can be leveraged to have accelerated solutions to all types of business problems.
In any corporate environment a coherent and seamless integration of technology, data, and business solutions is needed to enable data scientists, business analysts, or managers to contribute to the improved decision making. Despite the phenomena of data overload, outstanding advancement in Artificial Intelligence (AI), emergence of highly sophisticated Business Intelligence (BI) tools, it is still extremely challenging to identify one technology solution that is currently available in the AI or BI market or in the advanced technology space that can address data, analytics, and reporting issues starting all the way from the legacy system and subsequently connecting the distributed system as well as the application system in a coherent manner.
Although a unison of three components is absent in most of the organizations, some corporations are successful in combining the latter two components. However, these corporations still use human resources to connect to the legacy system. Therefore, despite a success by the few, the current scenario represents a clear obstacle in process automation for the majority. The reality of such limitation needs to be addressed and the industry must find the best way to eliminate human dependencies in the process workflow.
