Solutions

It is essential for enterprises to understand what is driving revenues and where to spend revenues. We can combine internal enterprise data and external market data to guide future decisions. In addition, it is always a struggle to figure out what is a healthy R&D budget or, for example, the appropriate marketing-to-revenue ratio to ensure long-term revenues without excess spending. We can also provide extensive help with questions of this nature.

The complexity in supply chain optimization lies in the number of moving parts and in the volatility of the moving parts. It is deeper than only a massive optimization problem to balance inventory levels, to schedule shipments, etc. It also involves predicting and forecasting key indicators such as demand. Supply chain optimization is also about properly sharing and leveraging information across different business units and departments, which enable them to work collaboratively towards common optimization goals.

Enterprises routinely conduct Root Cause Analysis to get to the bottom of unexplained events, which are typically not desirable and are to be avoided in the future. It is highly likely that the underlying causes and drivers of such events are subtly embedded in the enterprise data. The scope for a given Root Cause Analysis is very versatile; to name a few, inventory shrinkage, financial forensics, operation delays, etc.

Errors in enterprise databases are ubiquitous. The errors can occur at the data entry stage, during a database operation, while migrating to a new data storage facility, etc. Independent of what the error source is, we have built technology that can learn the characteristics of data errors and the characteristics of correct data by randomly propagating through large data sets. Then, we can pinpoint with high accuracy all the possible errors in enterprise databases.