Enterprise Operations Require a Specialized Intelligence Platform
Our operational intelligence platform is designed to meet the needs of teams running operations in large enterprises. It monitors business events in real-time and alerts users to risks and opportunities in the context of client relationships and financial outcomes. Acting as the hub for information from diverse sources, OpsVeda promotes an intuitive, easily customizable interface.
Information Hub – Process Agnostic Data Store
To gain a holistic view of operations, businesses need to gather information from diverse systems across the distributed supply chain. OpsVeda uses an open data model build with Process Agnostic Data Store* (PADS) technology to easily compile this data. By allowing the integration of multiple operations into process chains, OpsVeda makes it possible to monitor a transaction end-to-end without manually piecing together spreadsheets, or using multiple applications.
From penalties linked to order delays, to customer-specific requirements, to the auto-cancellation of unconfirmed orders, there is a lot riding on operational timeliness. Our data connectors transmit changes to transactions to the Information Hub immediately. Our fast, highly-optimized, in-memory computation engine is capable of processing hundreds of millions of rows of data in seconds, ensuring that the user learns the business implication of a change immediately.
OpsVeda ingests operational data and leverages machine learning to analyze and identify patterns. Over time, this increasingly automates the detection of exceptions and the prediction of outcomes. Based on factors like the availability of stock, customer priority, and current fill rates for a customer, OpsVeda can make recommendations that assess the potential impact of a decision on client relationships, financial outcomes, and long-term growth.
End-user Self-service with “Canvas”
For teams running operations, time is money. The business user does not have the luxury of waiting for technical support to set up a report or dashboard. OpsVeda Canvas enables self-service data discovery and promotes a user-friendly interface. With Canvas, business users can load their own data into the OpsVeda platform, blend streaming operational data with new data-sets, leverage a wide catalog of charts to create powerful visualizations, and set up access privileges to share the data visualizations across a broader audience.
Storyboards – One Workbench for the entire COO organization
Using highly intuitive tools, business users can design storyboards in OpsVeda that represent transactions, exceptions, and their status. They provide broader insight into a business’ financial performance and long-term growth trajectory. Storyboards can be personalized for different types of users in your organization, such as sales, customer service, and manufacturing teams. Through the Exception Builder, users can set and alter parameters used to separate transactions that have exceptions from ones that do not. OpsVeda’s fine-grained permissions capability enables everyone to simultaneously take their cues from the same data set. From the COO to the worker bee, everyone operates and collaborates with the same information.
Operations involves a number of moving parts managed by people from different teams and companies across the supply chain. Hundreds of daily decisions require the collective insight of people on every corner of the globe. Because insights are more valuable when shared, OpsVeda enables collaboration through in-app messaging and annotation features. Messages and annotations are linked to a distinct transaction or group of transactions, so that everyone remains on the same page.
Data Connectivity and Sources
Security & Scale
For us at OpsVeda, the security of your data is of paramount importance. The one-way encryption of passwords, strong password policy enforcement, single sign-on with SAML / Kerberos, SSL encryption for data in-transit, and three layers of encryption on DR storage, SAS 70 standards, are but a few of the measures we take to ensure security, confidentiality, and privacy. In terms of scalability, in-memory processing of all data ensures that users get analysis in real-time, regardless of the volume of data. Running on AWS provides the elasticity for seasonal peaks.