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Financial Management Consulting Company

Case Study

Simplifying Revenue Management system with Modern Data Intelligence

With nearly 1 million monthly case billing records generated across its multiple data sources, our customer is the Tier1 management consulting company in the United States – delivering unmatched quality and guaranteed on-time Consulting Services. 

Our customer was looking to scale its operations even further by integrating the scattered data to generate meaningful insights and enhance its solutions that can cater to its customers’ individual preferences. By developing effective and logical solutions, they were looking to transform billions of data points into insightful metrics. With Microsoft Azure and custom revenue management systems, the organization is well-positioned for even more exciting and revolutionary developments in the future.

Uniting the scattered data silos data and decentralized systems in one single source of truth

An American private investment firm based in Boston. It specializes in private equity, venture capital, credit, public equity, impact investing, life sciences, and real estate. They invest across a range of industry sectors and geographic regions. 

Achieving meaningful, relevant DATA requires significant amounts of digital heft. Each property has its own pre-defined system, which is then treated into heaps of transactional records, downloaded as separate excels. Accordingly, each record consists of numerous attributes that then need to be integrated to compose a single meaningful insight.

It was therefore imperative to streamline their data assets in a standardized form and right manner which would be most convenient for their internal teams. This was clearly a daunting task, so our customer wanted to partner with someone that could help them develop a centralized data platform and a billing management system.

Key business challenges include

Scattered data structure with little to no standardized system of recording the data points.

  • Absence of full records for older cases or vendors operating on legacy systems
  • Difficulty in gaining complete visibility due to decentralized data sources.
  • Lack of automation imposing unnecessary manual intervention for redundant tasks which further affected the reliability of the datasets
    available for data products.
  • Lack of relevant attributes and datapoints for generating meaningful insights and developing focused reporting capabilities
  • Engaging their teams with unnecessary transactional workflows that stood in the way of operational excellence.

Management system for simplified customer invoicing

Customer was majorly working on multiple disparate data sources to gather their entire data. At this point, their data was more like information not understanding the significance and its use. Their entire data ecosystem was divided into three different datasets — Core Revenue Management System, internal system and Data coming from other platforms being used (Revenue Management Application, Salesforce, SAP).
The Customer team collaborated closely with Kasmo to build and deploy a utilities management system for accelerated decision making and extract timely insights.

By identifying different data quality challenges, we could leverage Azure Data Services, and implement Azure Data Factory pipelines. Data Lake was used to store and analyse the data, thus enabling Conservice to improve the quality of its data sources.

Customer wanted to focus on automating reporting and analytical capabilities. So, they are now considering new ways to use data storehouses. With data warehouse, and discovery capabilities of Azure, they can generate user specific experiences that bring together business and customer data to simplify the ways in which their customers can process revenue and billing.

Since Customer also wanted to forecast monthly revenues, Azure Machine Learning Service provided a way to predict numbers and values immediately. With it, they now have forecasted data for over five years.
Now, Customer can move “full speed ahead” with its data modernization goals by leveraging technologies such as Azure Data Services (ADF, ADLS, Databricks, Azure SQL, Synapse Analytics, Purview)

Looking ahead, they wanted focus more on increasing their business avenues, and spend less time in managing their incoming data.

To elaborate it further, here’s an interesting example on how they plan to generate more business insights. By adding a self-serving reports capability through which they can select various financial or operations attributes as per their need and create a completely customized report all on their own. Thus, allowing them to centralize, add features, and increase the speed to the changing requirements quickly.

It's all about timing, optics and forecasting

An all-encompassing view and understanding of their existing data assets are crucial for automation and lesser human intervention. Failing to use data to drive understanding can leave companies unknowingly in the dark about opportunities for improving performance.

This new level of visibility has given Customer a platform to shift toward more data-driven, strategic decision support. As a result, they are now able to achieve:
Financial Reporting cycle enabling CFO, finance department understand revenue from each line of business, profitability, margins, and opportunities to reduce cost.

  • Improved Data Accuracy and better predictive analytics capabilities to forecast monthly revenue.
  • Improved reliability and consistency resulting in increased efficiency associated with property management, utility management, billing, payment, help desk, and other business operations.
  • Maximized Operational Reporting Features & Risk Mitigation
  • Standardized Reporting for all the operational teams with Superlative Power BI Solutions through self-service reporting platforms

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