Cloud computing has taken the business world by storm, offering faster deployment of applications and access to information from almost anywhere. The cloud model also lets organizations provision computing resources on an as-needed basis, and reduces the cost and complexity of system investments. These benefits are compelling, but how can cloud computing benefit a company's finance team?
To answer this question, it's helpful to examine the current state of the financial management technology market and how legacy systems handle tasks in comparison to a modern, cloud-based financial management system.
Current State of Affairs
Finance executives face enormous pressure to deliver compelling insights for business planning, yet their financial systems often hold them back. In Accenture's 2014 High Performance Finance Study, senior finance executives rank complex legacy systems and environments as their greatest challenge--outranking issues such as the need to optimize the capital structure of the enterprise, or managing the complex needs of stakeholders.
This unfortunate reality comes at a time when "the C-suite demands more timely reporting and more accurate forecasting from their finance teams," according to the report.
This top-challenge ranking isn't surprising, considering many financial systems in use today have been in place since the 1990s. Yet if you dive deep into the core of financial system technology architectures, you'll find there's not a lot of difference between those old systems and much of what's available on the market today. That's because at no point did traditional financial system vendors reengineer the technological architectures of their systems to meet modern business needs. At their core, they're the same legacy systems designed to be deployed on customers' premises to handle financial accounting--and not much more.
Now let's dig a little deeper into what this means for specific finance activities.
Reporting and Analytics
A particular weakness of legacy financial systems is report generation. This typically involves extracting and transferring data from finance and other operational systems to business intelligence applications, which can require hours of batch processing to create a single report.
Further complicating this effort, the data finance teams need often lives in multiple, geographically dispersed systems. The time and work that goes into report generation ultimately results in documents laden with stale...