Machine learning (ML) has the potential to revolutionize Enterprise Performance Management (EPM) by providing organizations with real-time insights and predictive capabilities across planning and forecasting processes. With the ability to process vast amounts of data, ML algorithms can help organizations identify patterns, trends and relationships that would otherwise go unnoticed. And as the technology continues to evolve and improve, even greater benefits are likely to emerge in the future as Finance leverages the power of ML to achieve financial goals.
Join us as we examine Sensible ML for EPM – Future of Finance at Your Fingertips.
For CFOs, whether artificial intelligence (AI) and ML will play a role across enterprise planning processes is no longer a question. Today, the question instead focuses on how to operationalize ML in ways that return optimal results and scale. The answer is where things get tricky.
Why? Business agility is critical in the rapidly changing world of planning. To think fast and move first, organizations must overcome challenges spanning the need to rapidly grow the business, accurately predict future demand, anticipate unforeseen market circumstances and more. Yet the increasing volumes of data across the organization make it difficult for decision-makers to zero in on the necessary data and extrapolate the proper insights to positively impact planning cycles and outcomes. Further exacerbating the problem, many advanced analytics processes and tools only leverage high-level historical data, forcing decision-makers to re-forecast from scratch whenever unforeseeable market shifts hit.
But with AI and ML, business analysts can analyze and correlate the most relevant internal/external variables. And the variables then contribute to forecasting accuracy and performance across the Sales, Supply Chain, HR and Marketing processes that comprise financial plans and results.
Over the coming weeks, we’ll share a four-part blog series discussing the path toward ML-powered intelligent planning. Here’s a sneak peek at the key topics in our Sensible ML for EPM series:
Regardless of where you are in your Finance journey, our Sensible ML for EPM series is designed to share insights from the experience of OneStream’s team of industry experts. We recognize, of course, that every organization is unique – so please assess what’s most important to you based on the specific needs of your organization.
The aspiration of ML-powered plans is nothing new. But to remain competitive amid the increasing pace of change and technology disruption, Finance leaders must think differently to finally conquer the complexities inherent in traditional enterprise planning. ML has the potential to greatly improve EPM by providing organizations with real-time insights and predictive analytics. However, organizations must overcome challenges (e.g., ensuring good data quality and selecting the right ML algorithm) to achieve success. As ML continues to evolve, increasingly more organizations are likely to leverage its power to drive better financial and operational outcomes.
Several challenges lie ahead for organizations of all sizes, but one of the most important decisions will be implementing the right ML solution – one that can effectively align all aspects of planning and elevate the organization toward its strategic goals. Sensible ML answers that call. It brings power and sophistication to organizations to drive transparency and increase the velocity of forecasting processes with unprecedented transparency and alignment to business performance.
To learn more about the value of Sensible ML, download our whitepaper titled “Sensible Machine Learning for CPM – Future Finance at Your Fingertips” by clicking here. And don’t forget to tune in for additional posts from our machine learning blog series!