Part 14 in the “Intelligent FP&A” series
Two of my favorite TV shows from the 1960s that dealt with the future were The Jetsons and Star Trek. One has a much better track record of predicting how technology has evolved. While we’re not quite driving the flying cars of the Jetsons – yet – let’s look back on the fantastic technological tools the crew of the USS Enterprise had at their disposal: the communicator (smartphone); tablets (Kindles and iPads); communication earpieces (Bluetooth); and virtual assistants (Alexa and Siri). With computers that can recognize natural language commands, I find myself believing we are still closer to the beginning, rather than the middle, of where technology can take intelligent FP&A in the future.
Picking up from where I left off in the last article in this series, the transition to cloud computing is another area that has taken hold across many industries. I remember when the cloud was first explained to me, in early 2010; now the cloud is indispensable.
Cloud deployment leads to an explosion of connected devices
By leveraging cloud technology, organizations can streamline operations, reduce costs, and provide greater flexibility. The deployment of cloud technology is widespread, and growing fast, in organizations globally. As recent research details, cloud computing will spark an explosion of connected devices and more real-time user interfaces. The architecture of IT will flip upside down, as data and content move to centralized cloud data centers. The cloud is the standard for the modern enterprise; approximately 70% of all organizations have at least one application in the cloud today. Cloud-based systems give iFP&A teams the ability to select best-in-class application solutions, offer real-time accessibility, and support business partnering and advising capabilities.
To ease the transition, many organizations are moving from private to public clouds, often taking a hybrid approach that straddles private and public cloud platforms. According to research from IDC, public cloud will account for 32% of IT infrastructure in 2020, while private cloud will take a 20% slice of the budget pie, equaling more than half (52%) of all infrastructure spending for the first time ever.
And more flexibility to adapt to adopt new technologies
The benefits of this transition include more flexibility to adopt new technologies to meet changing business needs, ease collaboration and data-sharing, and produce greater computing capacity for data storage and analysis, especially as more and more devices are connected. One challenge will be the transition from on-premises computing platforms to offsite locations that are more distant from the environment that organizations control and depend on to operate.
Digging in a little deeper, we start getting into some of the more “science-fiction” aspects of where iFPA will be heading in the future. Artificial intelligence (AI) is a technology that would be classified as “developing”; leading organizations are making early investments and developing practical applications. One purpose of AI is to capture, manage, and analyze massive amounts of data and produce insights. Algorithms search for patterns and filter out the noise, as a human would, only faster and more accurately.
Machine learning (ML) is a subset of AI. ML is a technique that helps systems learn from existing data to forecast future behaviors and explain trends and outcomes. In other words, ML tools can learn to use data to explain complex phenomena. This will help our business partners improve their decision-making skills and ability to react to changes in their business, including being able to detect trends and patterns before they would be apparent by other methods.
To learn more about how to optimize your intelligent FP&A process, learn about “Collaborative Enterprise Planning.”