The Cost of Still Using Spreadsheets

In today’s complex risk landscape, spreadsheets can no longer carry their weight. They create administrative burdens and introduce the possibility of human error. 

Person typing on a computer with a spreadsheet open

Legacy strategies for risk management, such as spreadsheets, have retained a stronghold among risk managers in lieu of newer, technology-based solutions like RMIS software. According to a 2018 poll, 60% of risk managers still use spreadsheets, while a mere 10% rely on a fully integrated data management system. This is a testament to the demanding workload risk managers face.

In today’s highly complex risk landscape, spreadsheets can no longer carry their weight in the way they might once have. Instead, risk professionals are left slogging through the administrative burden of maintaining numerous spreadsheets and jeopardizing accuracy in the process.

Instead, industry professionals should look forward to newer solutions that can improve efficiencies with less manual process and provide data analytics and insights.

The Role of Spreadsheets 

Spreadsheets were originally designed to centralize data and serve as a quick look-up tool. While this once aligned with risk management practices, risk management as a business function has since expanded its role under the scrutiny of both internal and external parties. This is compounded by the fact that the risk landscape has changed significantly in the last decade alone.

Today, spreadsheets are holding businesses and their risk management teams back.

Cost of Using Spreadsheets in 2023

Relying on spreadsheets can be risky for the following reasons:

  • Reliance on manual processes: Manual processes are time-consuming and prone to human error.
  • Workflows divided between departments: Departmental barriers and data silos impede progress and collaboration and can result in more file errors and redundancies.
  • Limited analytics: New outputs and changes often require custom programming and can be undermined by even one human error in a formula or calculation. AI-based RMIS software helps anticipate risk through predictive modeling, instead of reacting after the fact.
  • Limited room to grow: Legacy systems were not built to support the risk management and claims administration process. As a result, these systems will always have limitations that prevent users from getting ahead of the curve.

See also: It's Time to Rethink the Spreadsheet

The Benefits of Using a Risk Management Platform

Using technology-based tools, companies can improve the efficiency of their insurance and risk management programs.

One major automotive brand, which I'll refer to as “Company A,” has seen these benefits first-hand. Within the past year, Company A began digitizing its insurance process. Prior to doing so, the company’s insurance and risk department relied heavily on spreadsheets with different sources of information, as well as the nuanced knowledge of individual employees to share where to find specific data, its traceability, what processes exist and the history of current information. Realizing the inefficiencies and room for error this created, Company A determined that it needed to capture all the relevant information from different files and platforms and get it together in one system – an RMIS software.

As a result of its new software’s organization and streamlining capabilities, the company’s insurance and risk department was able to better manage and apply its existing information. Previously, Company A’s  claims management was conducted mostly in-house and with portions conducted by third-party vendors, leading to a decentralized system. This process was the same for policy management and was often conducted across multiple spreadsheets. Now, the spreadsheets have been consolidated into the new risk management software, allowing Company A to automate specific evaluation processes.

With an RMIS system and application programming interface (API) technology, this company can collect information more effectively and quickly present that information to insurers and other stakeholders in new ways. With a trustworthy, efficient and fast system, the Company A team can spend more time on risk handling instead of administrative tasks. 

Another example of successful spreadsheet to AI-based insurance and risk management technology implementation is NIP Group. With an extensive amount of data across more than 25 niche industries, the company's complex claims requirements necessitated a solution that addressed unique needs and provided a level of efficiency that spreadsheets were not allowing.

By bringing in AI-based software to help manage data and claims management, the company was able to create a streamlined implementation process with secure data loading and an extract/load/transfer (ELT) tool for automation. This included the ability to customize the data hierarchy based on business needs instead of in a more linear fashion, as is traditional with spreadsheets.

Now, rather than varying spreadsheets, NIP Group can manage different lines of coverage across various industries and entities across one, singular system. Prior to using an AI-based insurance and risk management system, NIP Group was only able to develop and use a small portion of the information it needed. Now the company can see the bigger picture and save significant amounts of time. 

In addition to helping the company streamline internal reporting and file management, it now has more capacity for managing reporting for carriers and tower insurance company groups and can easily maintain compliance with state banking and insurance annual reports.

Benefits of Using Risk and Claims Software

With newer, AI-powered RMIS tools on the market today, relying solely on spreadsheets for data input, tracking and analysis is a legacy management method that comes with its risks – human error and poor use of risk managers’ expertise.

By taking advantage of the right software, companies can better secure their data, automate processes and remove the likelihood of errors – resulting in cost and time savings.

Mark Tainton

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Mark Tainton

Mark Tainton is head of strategic analytics at Ventiv Technology.

He oversees the development of Ventiv’s advanced analytics product suite, including: Ventiv Predict, Ventiv Geospatial and Ventiv Data Sciences. Tainton has a rich history of leading, building and mentoring data analytics and data science teams. His experiences include serving as global head of business intelligence and management information with Aon Risk Services, vice president of global business intelligence with Arthur J. Gallagher and head of data analytics with Calamos Investments.

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