Investment management firms rely on many sources of data to manage their business processes and make daily decisions. As the amount of data in an organization grows so do the questions that arise regarding the genesis of data, its availability and accuracy, and business rules supporting its lineage. Data consumers demand transparency into these critical processes and many of the legacy investment data management systems fail to easily provide the answers.
In this blog, I discuss three solutions Grandview Analytics implemented in support of our Managed Data Service which is powered by our proprietary data management and reporting platform, Rivvit.
Data management challenges
Many firms lack the tools necessary to properly maintain up-to-date documentation related to data policies, procedures, and technical specifications. Historically, operational personnel documented policies and procedures in word documents while analysts created spreadsheets to manage a data dictionary that tracks data sources, fields and definitions, calculation methodologies, source hierarchies, and process controls. In a world of agile development, this documentation quickly becomes outdated. No single person can keep up with the constant change which makes it nearly impossible to answer basic “current state” questions without initiating a project.
Most investment operations also lack the technology to adequately track cross-functional processes due to silos that result from lack of enterprise oversight. These same firms typically find themselves in constant fire drill mode because their data technology never catches up to their business needs. It is a vicious cycle that results in the implementation of sub-optimal, tactical solutions that are often necessary to solve an immediate problem while strategic solutions are put on the back burner. The ultimate impact is the inability for financial controllers and data officers to have a comprehensive understanding of the data dependencies and workflows across complex, multi-step processes with many touch points because critical data sets are not centralized.
Email is not the answer
Without the proper technology to track real-time status and up-to-date documentation, organizations tend to rely on email that is often responded to after a mini (at best) research project. Data consumers are under significant pressure to deliver information in the form of reports and analysis in a timely manner. They need trusted data that they understand and can explain to their end clients. The inability to quickly evaluate quality and completeness or explain basic definitions and methodologies results in a lack of trust and is caused by the black-box nature of many of the legacy systems I have encountered throughout my career. Furthermore, many of these business-critical emails are never responded to due to the sheer volume of inquiries. Relying on email notifications and distribution lists to communicate status, escalate issues, and manage exceptions is not a scalable solution.
I read recently that the number of emails sent and received each day exceeded 333 billion last year. Less than 40% were opened! Meanwhile, the average business person receives 121 emails a day. When you do the math, less than 70 of those emails are opened and read.
Clearly, email isn’t a safe or sustainable solution. With the growing number of data sources companies rely on to manage their processes and make decisions for their businesses, transparency into the accuracy and availability of that information is crucial.
3 ways to get transparency and control of data
We experienced this email chaos first-hand processing hundreds of automated jobs per day for our Rivvit clients. We would exchange dozens of emails per day from clients with questions such as: Where was this data point sourced from? Did you receive this file? When did you receive it? Did it process successfully? Were there any issues? The questions go on and the ability to quickly provide real-time status updates for basic questions was not possible, but sorely needed.
To solve the challenge and give our clients more transparency and control over their data, we built three key features into Rivvit.
1. Configurable ingestion framework
Rivvit-EDM is powered by a configurable, low-code ingestion framework that is set up directly through the user interface. Clients benefit by accessing a complete data dictionary with all data sources, fields, rules, mappings, and hierarchies directly in Rivvit. Configurations are always up-to-date because they are embedded in the software and drive Rivvit’s ingestion workflow. No longer do clients need to ask basic data lineage questions because they have the information at their fingertips.
2. Data quality management
Rivvit-DQM detects data issues based on business rules configured for each client’s unique data. Rivvit users have transparency into the health of their data in a single dashboard. Exceptions are summarized for each rule, owner, and level of criticality so data stewards can view and research issues down to the field level across each of their data domains.
There is a built-in exception management workflow that allows data owners to change priority or status, assign issues, and add commentary – all with a complete audit trail. This self-service capability allows Rivvit users to do their research and communicate with colleagues directly in the software and provide transparency to downstream consumers regarding the status and quality of data they rely upon.
3. Scheduling and event tracking
With Rivvit’s Workflow Manager, we’re able to set up custom schedules for any task and automatically track the underlying steps needed to successfully complete it. We initially developed Workflow Manager to show the status of our core data ingestion and extraction capability and quickly expanded it to track the status of nearly 1000 automated jobs that we process daily including everything from reconciliations to custom procedures and database backups. Now, our clients have complete transparency into the status of all scheduled jobs so they can focus on addressing issues instead of chasing down status. This is a chief data officer’s dream!
Data transparency drives increased productivity and confidence
Today’s data management environments need built-in data governance and stewardship best practices and configurable processes to empower users with knowledge about their data and confidence in its usability.
Transparency is key for our clients and Grandview’s Managed Data Service. Our goal is to give Rivvit users a single point of reference to understand their business rules, supporting policies, and status of their data. With easy access to this information, they are more productive and have greater confidence in their reporting and decision-making.
