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Financial Advisory Software Firms Sees Business Doubling
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
- Quality Assurance
Services
- System Integration
- Software Design & Engineering Services
The Challenge
Orion’s platform gathers and analyzes data on client investments, allowing firms to view their overall performance, as well as identifying weak or strong points in their business strategy. This presents its own hurdle, though. There is a LOT of data to wade through: 51 terabytes of it, in fact. Finding a BI tool that could handle this volume without sacrificing granularity was not going to be easy. Before implementing a BI tool, Orion used a manually built, flexible, and customizable reporting platform for operational reporting. So far, so good - except, by the time they generated each business metrics report and sent it to the client several weeks after the month ended, it was already out of date. Plus, the data was static, so clients couldn’t delve in to check the details or context. They only had headline figures, giving them an idea of overall performance. If they wanted to analyze this in any way, they’d have to request a special data query. This could take a day to develop. Orion realized that the company needed to take the leap from business metrics to business intelligence. Their customers needed a platform with better visualizations and direct access to accurate, up-to-date data, in order to make informed business decisions. Orion had executed a proof of concept by integrating an Excel interface into their API to get a feel for what customers wanted. The first approach was to create a dimensional model of the data, push it to firms using an SQL Server and teach them how to connect data to their current data visualization tool. However, Orion customers found dashboard-building to be too complex. Often, they didn’t yet know or understand what they wanted to get out of their data. Clearly, they would need a solution that was ready to deploy out-of-the-box and accessible by all users - not just those with IT expertise.
About The Customer
Orion is a premier portfolio accounting SAAS provider for advisors. Its 950+ clients manage assets spanning 1.5 million accounts and totaling nearly $375 billion. Orion’s platform gathers and analyzes data on client investments, allowing firms to view their overall performance, as well as identifying weak or strong points in their business strategy. The company faced challenges with their existing static reporting solution, which provided outdated information and lacked interactivity. Orion needed a more dynamic and real-time business intelligence tool to meet their clients' needs for better visualizations and direct access to accurate data.
The Solution
After attempting to build their own solution and then testing five different BI solutions, Orion chose Sisense. Both Malinda and CEO Eric Clarke loved the look and feel of the product, and the sheer ease and responsiveness of it. What’s more, they were amazed to find that they were able to go from the concept stage to getting their final product ready to use within just two months. Their customers wanted preconfigured dashboards, with the interactivity to let them explore their data and drill down into details. Luckily, the white labeling function in Sisense worked perfectly for this: they could embed the BI tool into their product and offer it to their clients as part of their own platform. Now, Malinda says that advisors are better able to monitor business trends, zoom into the details, address questions regarding Assets Under Management (AUM) changes over time, new accounts opened by month/year/quarter, transaction types, top performers, cash flows, demographic trends, and more. Sisense’s Elasticube feature actually helped them to clean up, strip back, and simplify the amount of data they were using, more than halving the 500 GB of data that was clogging up their SQL Server.
Operational Impact
Quantitative Benefit
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