Real time data service for enterprise
WHY (Problem)
Real business innovation in supply chain requires maximizing return on data as your assets. Very frequently this is the key constraint to speed, scale and accuracy that leaders envision. For over a decade now industry has been mesmerized new technologies promising to easily organize enterprise data and serve them on demand. Especially for any work in the operational supply chain horizon most of these technologies and approaches fall short of promise. Data is stale, put together without context and understanding of what it represents. This limits innovation by making POC, new algorithms, data integration to external SAAS system cumbersome.
WHAT (Value)
Productivity
Reducing innovation cycles by 50%+ by delivering data in clean, fresh custom form
Time to Value
Complexity:
Decision quality
Enabling true self service reporting for all your operational roles releasing productivity
Keeping your large transformational programs like ERP upgrades or Advanced Planning systems implementation on track (90% of the programs fail to do so)
HOW (Solution)
Through years or experiments, research and iterations, HyLogic has put together a well-functioning technical stack that enables real time data engineering and management. We have prepared it to be resilient, accurate and well organized to serve multiple (in some cases 200+) consuming applications at the same time. The differentiator of our solution is that it’s not a set of tools put together, but also technical a know-how how to operate and maintain it - achieving extraction, transformations and data provisions at speed of seconds. We do not see such solutions available in 99% large enterprises we work with. Its only a hope and dreaming strategy that yet another “toy” will perform at scale and security we can offer. Availability of such solution in your company will have instant adopetion and in turn democratize the data, reduce the constraints to try new approaches, to envision replacing operational supply chain roles with ML or other algorithmic methods.
