The analytics landscape at Captive Resources was marked by many manual and time-consuming reporting processes, leaving no time for data analysis. MS Excel was the primary and preferred tool for reporting and analysis, and even when incorporating more advanced features such as macros and linked sheets, CRI reached the limit of the capabilities of the tool. Reports were largely in tabular form, with little focus on data visualization.
A large part of the time associated with these manual processes was due to CRI’s data residing in several siloed source systems. Any report which required data from multiple systems required complex Excel formulas and v-lookups and additional layers of auditing to mitigate the risks of manually combining this data for every request or refresh.
As they grew, CRI knew the time required for the existing manual reporting processes would begin to impact the business, such as making quick decisions related to finances and pricing. Without a more systematic way of understanding and predicting company growth, staffing considerations would also become more complex. In general, manual processes with ever-increasing amounts of data put data quality at risk.
Furthermore, there was little standardization between captives, so analysis across captives was already difficult and would only become worse as CRI expanded. This lack of standardization not only impacted the performance of CRI, but also their business partners. Pinnacle, the actuarial firm engaged by CRI, estimated that 30% of their time was spent on transforming, massaging, and validating the inconsistent data they receive from CRI.
CRI needed the ability to automate their reporting and see data across captives so they could perform unified analysis of premiums, claims/loss history, pricing factors, member counts, and more.
CRI engaged Analytics8 to build a solution that would automate reporting, leverage data to support the planned growth, and refocus the effort of resources toward analysis of data. We started by conducting a strategic assessment of the company’s current state of technology and business processes. We interviewed business users to identify their daily processes and understand how they were currently utilizing their data. During these discussions, Analytics8 identified the key metrics that CRI leadership wanted to measure and helped users prioritize their report requests and use cases.
We also conducted meetings with data source experts and SMEs and profiled multiple source systems. This allowed us to begin plans for a data warehouse and gain an understanding of the feasibility of implementing each data source.
Combining the knowledge gained on the business and data sides, we created a use case prioritization matrix which weighed business value against feasibility to identify the optimal implementation schedule which would deliver value in short iterations.
The assessment resulted in an overarching long-term roadmap and more detailed short-term implementation plan with artifacts that can be used immediately to begin implementing the recommended solution. We provided a detailed plan for a robust data warehouse and centralized reporting platform and provided suggestions on data storage, BI and ETL tools, and staffing needs to support their ideal solution.
The roadmap and other deliverables from the strategic assessment allow CRI to proceed confidently with a solid plan to address growth concerns and implement an even more powerful and robust business intelligence solution. CRI is utilizing the roadmap to plan for future phases, and the documentation within can serve as blueprints to speed up the development process.
CRI now has a better understanding of data needs for business users across departments and the tools, data organization, and methods to effectively address those needs. They also have a better understanding of the future state they are working towards and have begun process improvements to support those goals. Efforts have started to consolidate and standardize data sources to be utilized in future phases. Departments are also focused on standardizing and prioritizing their KPIs which will benefit the report design and development phases.
After the DWH is built, CRI will be able to integrate their disparate data for unified analysis of premiums, claims/loss history, pricing factors, member counts, and more.
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