Lack of version control
Companies that rely on manual processes may find they have multiple versions of the same document in use, which increases the risk of errors. Using a spreadsheet for quoting, for example, can be dangerous if a user pulls down a spreadsheet from the network with old or incorrect rates.

A user should know that he is automatically using the latest rates and correct rating algorithm, and that all data is up to date and current. There should not be a question of whether a spreadsheet is the "official" version.

Automated technology allows multiple users to access all data from one consistent version in real time to make decisions.

Lack of audit trails
Spreadsheets enable businesses to visualize and organize data in a way that people who have no technical background can easily use. However, spreadsheets should never be used as a system of record. Even one small error can produce the wrong result and affect an entire account. A user may disagree with formulated values on a spreadsheet, set up their own controls and link the results from the first document to the second with no oversight or testing for accuracy.

Changes to calculations involving premiums need to be verified for accuracy and should require user authentication, something manual processes cannot do.

Companies need applications that leave an automated audit trail of changes made, who made them and why as well as the receipt of proactive alerts about changes to algorithms and important data. On top of that, these audit trails should be easily reportable.

Lack of consistent data management
A spreadsheet has uncontrolled data formatting and organization. As a result, it is very hard to ensure that the same data standard is enforced throughout the company.

Taking an inventory of all critical spreadsheets across corporate data sources, including file shares, employee desktops and document repositories ensures the data elements are being consistently formatted.

Inconsistent data formats can cause issues during data warehousing or big data analytics. Using an automated software system enables controls to be enforced on the data elements and allows easier use of business intelligence and reporting tools across the enterprise. Information can be organized in one warehouse and recorded in a central system and accessed in real-time.

Lack of scalability 
Insurance agencies that experience rapid growth produce more data, and as a result, must hire additional employees to manually process this data, which diminishes profit and net income.

In some cases, companies cannot handle the increase in data and have to turn away business. Complex processes such as specialty lines ratings are difficult to perform correctly when handled manually. To thrive, agencies and carriers need automated processes and technology that enable them to grow without having to add additional staff. 

Insurance agencies and companies can no longer effectively compete using manual processes. Succeeding in today's uncertain business environment requires organizations to embrace new technologies that enhance growth, improve efficiency and reduce risk to the institution and its stakeholders.