Gartner Magic Quadrant: Exciting EPM Software Trends Every Business Should Know in 2024

Gartner Magic Quadrant: Exciting EPM Software Trends Every Business Should Know in 2024

By Kristina Zhelyazkova

Gartner Magic Quadrant: Exciting EPM Software Trends Every Business Should Know in 2024

By Marta Teneva

July 4, 2024

Are you struggling with inefficient financial planning and outdated processes? This blog explores the evolution of Enterprise Performance Management (EPM) software, highlighting the transition from manual methods to advanced AI and ML-integrated solutions. You will gain insights into the latest market trends and technological advancements driving EPM growth and learn how to select the right EPM tools for your business needs in 2024.

Enterprise Performance Management (EPM) has undergone a remarkable evolution, transitioning from rudimentary manual processes to leveraging cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) technologies.

This transformation has not only streamlined financial planning, budgeting, forecasting, and reporting processes but also equipped organizations with strategic insights for informed decision-making.

As we explore EPM software, we uncover the technological advancements and shifting business dynamics that have shaped their development.

From the initial reliance on paper-based systems and spreadsheets to the integration of sophisticated software solutions, the progression towards cloud computing, and the recent adoption of artificial intelligence (AI) and machine learning (ML), each phase reflects a leap towards more efficient, insightful, and agile financial management.

Moreover, this article explores the current EPM market’s size, emphasizing its significant growth trajectory and the factors driving this expansion.

As EPM software continues to evolve, it promises to offer even greater capabilities, integrating advanced analytics and fostering tighter collaboration across enterprises.

This article aims to provide a comprehensive overview of how EPM software has evolved, what different EPM tools presently offer, and the exciting trends on the horizon for 2024, guiding organizations in choosing the right EPM solution to meet their evolving needs.

The Evolution of EPM Software

The evolution of EPM software has been marked by significant technological advancements and shifting business needs, leading to more sophisticated, integrated, and user-friendly solutions. This evolution can be traced through several key phases, each introducing new capabilities and focusing on addressing the growing complexity of organizational financial planning and analysis needs.

Timeline infographic depicting the evolution of Enterprise Performance Management (EPM) software. The timeline includes stages such as manual processes and standalone EPM tools, emergence of EPM software solutions, advancements in technology and integration, cloud computing and accessibility, and incorporation of artificial intelligence (AI) and machine learning (ML).

Initially, EPM processes were highly manual, relying on paper-based systems and basic electronic spreadsheets. Organizations used standalone tools, primarily spreadsheets, for budgeting, planning, and reporting. This approach was time-consuming, error-prone, and lacked real-time insights.

Data resided in siloed systems, making it difficult to achieve a unified view of financial performance across different departments and business units.

In response to the limitations of manual processes, dedicated EPM software solutions began to emerge. These solutions aimed to streamline financial planning and reporting processes, offering more accuracy and efficiency than spreadsheets.

Early EPM software was primarily deployed on-premises. These systems offered better data consolidation and facilitated some degree of automation in financial reporting and analysis.

EPM software evolved to support integrated financial planning, linking strategic planning, budgeting, forecasting, and financial reporting into a cohesive system. This integration enabled better alignment between financial goals and operational plans.

The integration of BI tools with EPM tools enhanced reporting capabilities, providing more insightful analytics and data visualization options to support decision-making.

The shift to cloud-based EPM software represented a significant evolution, offering scalability, reduced IT overhead, and enhanced collaboration. Cloud platforms enabled real-time data access, anywhere and anytime, fostering more agile and flexible financial planning processes.

The introduction of mobile access to EPM tools further increased flexibility, allowing finance teams to access critical financial data and perform tasks from any location.

The latest evolution in EPM software includes the integration of AI and ML technologies. These advancements bring predictive analytics, scenario planning, automated anomaly detection, and natural language processing to financial planning, significantly enhancing forecasting accuracy and operational efficiency.

EPM tools now support more dynamic, continuous planning processes, moving away from the traditional static annual budgeting model. This shift allows organizations to adapt more quickly to market changes and business needs.

EPM software’s role has evolved from focusing mainly on financial reporting to providing strategic insights supporting decision-making at all levels of the organization.

Modern enterprise performance management software emphasizes collaboration, with features that streamline workflow, enhance communication among stakeholders, and integrate financial planning processes across the enterprise.

The future of EPM software is expected to see further integration of advanced analytics, more sophisticated AI-driven insights, and even tighter integration with operational systems. The goal is to provide a holistic, real-time view of enterprise performance, supporting strategic decision-making and driving business growth.

The evolution of EPM platforms reflects the broader digital transformation journey of organizations, focusing on enhancing efficiency, insights, and agility in financial planning and performance management.

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EPM Market Size: Current State and Predictions

The current enterprise performance management (EPM) market size is estimated at USD 7.53 billion in 2024 and is expected to reach USD 11.86 billion by 2029, growing at a Compound Annual Growth Rate (CAGR) of 9.5% during the forecast period (2024-2029).

Bar chart showing the growth of the Enterprise Performance Management (EPM) market from 2024 to 2029. The market size is expected to increase from USD 7.53 billion in 2024 to USD 11.86 billion in 2029, with a compound annual growth rate (CAGR) of 9.50%. The source of the data is Mordor Intelligence.

The enterprise performance management (EPM) market is experiencing significant growth due to a combination of technological advancements, changing business needs, and the increasing importance of strategic financial planning. Here are some key factors contributing to the growth of the EPM market:

Organizations worldwide are seeking more efficient ways to manage financial planning, budgeting, forecasting, and reporting. The need for streamlined and automated financial processes to replace manual, time-consuming tasks is a major driver for EPM adoption.

The acceleration of digital transformation across industries has heightened the demand for real-time data access and insights into financial performance. EPM solutions provide organizations with the ability to analyze financial data in real time, supporting faster and more informed decision-making.

The integration of artificial intelligence (AI) and advanced analytics into EPM platforms has significantly enhanced their capabilities. These technologies enable predictive forecasting, scenario planning, and anomaly detection, offering deeper insights into financial data and future trends. This has made EPM solutions more attractive to businesses looking to leverage data for competitive advantage.

As businesses expand globally and operations become more complex, there is a growing need for comprehensive financial planning and analysis that can accommodate multiple currencies, regulatory environments, and business models. EPM solutions are designed to manage this complexity, making them essential for large, multinational organizations.

Organizations are increasingly recognizing the importance of aligning financial planning with strategic goals and operational performance. EPM software facilitates this alignment by integrating financial data with operational data, enabling holistic planning and performance management.

The shift towards cloud-based EPM solutions has made these platforms more accessible to a wider range of businesses, including small and medium-sized enterprises (SMEs). Cloud deployment offers scalability, reduced IT infrastructure costs, and ease of access, contributing to the market’s growth.

EPM solutions help organizations navigate the complex landscape of regulatory compliance and risk management by providing tools for financial reporting, compliance tracking, and risk assessment. This capability is particularly important in industries with stringent regulatory requirements.

Many organizations are undergoing digital transformation to improve efficiency, agility, and customer service. EPM is a key component of these initiatives, providing the financial insight and control needed to support transformation strategies.

Infographic detailing factors contributing to the size of the Enterprise Performance Management (EPM) market. Factors include increased demand for efficient financial processes, advancements in AI and analytics, strategic planning and performance management, increased focus on regulatory compliance and risk management, need for real-time data and insights, growing complexity of business environments, cloud adoption, and digital transformation initiatives.

In summary, the growth of the EPM market is driven by the need for more sophisticated, efficient, and integrated financial planning and analysis capabilities. As businesses continue to navigate a rapidly changing economic environment, the demand for EPM solutions is expected to increase, further fueling market growth.

Keep Exploring: How to Maximize Profits with Enterprise Performance Management (EPM) in 5 Steps

AI Integration in EPM Software: Types and Applications

Enterprise performance management (EPM) software is increasingly incorporating various types of artificial intelligence (AI) to enhance financial planning, analysis, and decision-making processes. These AI capabilities transform traditional EPM tools into more predictive, automated, and insightful systems that can handle complex data analysis at scale. Here are some of the primary types of AI used in EPM software and their applications:

ML, a subset of AI, is widely used in EPM software for predictive analytics, forecasting, and trend analysis. ML algorithms learn from historical data to predict future financial outcomes, such as revenue forecasts, expense trends, and cash flow projections. By analyzing patterns and relationships in data, ML can provide more accurate forecasts, helping organizations plan more effectively.

How it’s used:

• Predictive Forecasting: ML models analyze past performance data to predict future outcomes, enabling more accurate budgeting and forecasting.

• Anomaly Detection: ML algorithms identify outliers in financial data, which can indicate errors, fraud, or unusual trends needing further investigation.

NLP allows EPM tools to understand and interpret human language, making it easier for users to interact with the software using natural language queries and receive insights in easily understandable formats.

How it’s used:

• Chatbots and Virtual Assistants: NLP powers chatbots and virtual assistants that can understand user queries, provide financial reports, and offer insights in natural language.

• Data Entry and Extraction: NLP is used to automatically extract relevant information from unstructured data sources, such as invoices or contracts, reducing manual data entry.

DL, a more complex subset of ML, is used for processing large volumes of data and identifying patterns that might not be visible to traditional analysis methods. It’s particularly useful for high-dimensional data and can enhance the accuracy of financial models.

How it’s used:

• Complex Forecasting: Deep learning models tackle complex, multi-dimensional forecasting problems, such as demand forecasting, by analyzing vast datasets including external factors like market trends and economic indicators.

Generative AI, which includes technologies like Generative Adversarial Networks (GANs), can create data that mimics real-world financial scenarios. This capability is useful for scenario planning and stress testing.

How it’s used:

• Scenario Planning: Generative AI creates realistic financial scenarios, helping organizations explore various strategic options and their potential impacts.

• Data Augmentation: Enhancing datasets with artificially generated data to improve the accuracy of financial models, especially when historical data is limited.

Cognitive computing combines ML, NLP, and other AI technologies to mimic human thought processes in a computerized model. It’s used in EPM tools to provide insights and recommendations based on a comprehensive analysis of financial data.

How it’s used:

• Decision Support: Offering insights and recommendations for financial decisions by analyzing a wide range of internal and external data sources.

• Risk Management: Identifying and assessing financial risks by understanding patterns and correlations within complex datasets.

The integration of these AI technologies into EPM software enables more automated, accurate, and insightful financial planning and analysis. For example, AI can automate routine data analysis tasks, freeing finance professionals to focus on strategic decision-making. AI-driven forecasts can adapt to changing market conditions faster than traditional methods, providing organizations with a competitive edge. Moreover, AI-enhanced reporting and insights help communicate complex financial information across the organization, building a decision-making culture based on data.

As EPM tools evolve with AI, organizations can expect these technologies to become more sophisticated, offering deeper insights, improving operational efficiency, and enabling more proactive and strategic financial management.

Some of the predictive models already available in PlanIQ (part of the Anaplan platform): 

PlanIQ Forecasting Algorithm Suite by Anaplan. The suite includes various predictive models such as Anaplan AutoML, ETS, ARIMA, Anaplan MVLR, Multiplicative Decomposition, Croston's, Amazon AutoML, Amazon CNN-QR, Amazon Deep AR+, Google AI, Prophet, and Naive. Each model is designed to optimize different aspects of forecasting and is powered by various technologies from Anaplan, Amazon, and Google.

Gartner Magic Quadrant 2024: Exciting EPM Software Trends

To categorize the vendors based on the types of improvements they plan to release for 2024, we can group them into four main categories: AI and Machine Learning Enhancements, Data Integration and Management, Generative AI and Natural Language Processing (NLP), and Forecasting and Scenario Planning. This categorization reflects the focus areas of innovation and enhancement in the financial planning software market, according to Gartner’s Magic Quadrant for Financial Planning Software.

Magic Quadrant chart for financial planning software as of October 2023 by Gartner, Inc. The chart is divided into four quadrants: Challengers, Leaders, Niche Players, and Visionaries. Leaders include Anaplan, Oracle, OneStream, Board, SAP, and Workday. Challengers include Vena and IBM. Visionaries include Planful. Niche Players include Kepion, Syntellis, Prophix, Acterys, and insightsoftware. The chart positions companies based on completeness of vision and ability to execute.

Figure 1: Magic Quadrant for Financial Planning Software

Acterys: Plans to release automated AI data models for enhanced forecasting capabilities.

Insightsoftware: Aims to integrate Azure Machine Learning to enhance planning speed and accuracy.

Planful: Expects to deploy new AI and ML features, including AI-driven financial narrative generation.

Prophix: Plans to enhance its back end to support complex resource management and planning models with AI.

Workday: Plans to release its Predictive Forecaster, leveraging external data for ML time series forecasts.

Anaplan: Expects to enhance its data integration and management capabilities.

SAP: Plans to introduce planning as a service, potentially serving as the data persistence layer for SAP Analytics Cloud.

Anaplan: Introduction of AI conversational chat, including NLQ capabilities.

Discover More: Making the Switch: Why Retailers Choose Anaplan for Demand, Finance and Merchandise Planning

Board: Plans to build on its ModelOps support with features based on GenAI, including LLM technology foundations.

Jedox: Plans to release analysis and scenario planning driven by GenAI and natural language.

OneStream: Plans to release GenAI capabilities, providing intelligence through financially aware LLM interaction.

Oracle: Plans to release a secure cloud-based GenAI finance assistant for automated management reporting.

Vena: Expects to leverage GenAI using Azure OpenAI for natural language questions and what-if scenarios.

Wolters Kluwer: Plans to add NLP, AI chatbots, and enhanced anomaly detection for insights from data.

IBM: Intends to offer multivariate forecasting capabilities for complex decision-making.

Syntellis: Intends to release market-based demand planning for accurate forecasting and planning.

These categories underscore the strategic focus of each vendor, highlighting their commitment to leveraging AI, ML, and data integration technologies to drive innovation in financial planning and analysis tools. The advancements reflect a market trend towards more intelligent, efficient, and user-friendly financial planning solutions.

What to Consider when choosing an EPM Software Solution

Choosing the right Enterprise Performance Management (EPM) solution is crucial for the effective management of an organization’s financial planning, budgeting, forecasting, and reporting processes. Here are key factors to consider when selecting an EPM system:

Infographic listing key factors to consider when selecting an Enterprise Performance Management (EPM) system. Factors include integration capabilities, scalability, customization and flexibility, usability and user experience, advanced analytics and reporting, cloud vs. on-premises, security and compliance, performance and reliability, AI and ML, vendor reputation and support, total cost of ownership, collaboration features, and futureproofing.

• Data Integration: Ensure the EPM solution can seamlessly integrate with your existing ERP, CRM, HRIS, and other critical business systems to consolidate data across the organization.

• System Compatibility: Check for compatibility with your IT infrastructure to avoid integration issues.

The chosen EPM solution should be able to scale with your business, accommodating growth in data volume, number of users, and complexity of operations without significant performance degradation.

Assess the degree of customization the EPM solution offers to meet your specific business needs and the flexibility to adapt to changing business processes and requirements.

A user-friendly interface and ease of use are crucial for ensuring high adoption rates among stakeholders. Evaluate the learning curve for new users and the availability of training and support materials.

The solution should offer robust analytics and reporting capabilities, including dashboards, visualizations, and predictive analytics, to provide deep insights into financial performance and forecasts.

Decide whether a cloud-based or on-premises solution best fits your organization’s needs, considering factors like cost, security requirements, and the need for remote access.

Verify the EPM solution’s security features and compliance with relevant regulations (e.g., GDPR, SOX) to protect sensitive financial data and ensure regulatory compliance.

Evaluate the system’s performance, particularly in processing large volumes of data, and its reliability in terms of uptime and support response times.

Consider the extent to which the EPM solution incorporates AI and ML for advanced forecasting, scenario planning, and anomaly detection to enhance decision-making.

Research the vendor’s reputation, customer service record, and the quality of technical support offered. Consider the vendor’s stability and commitment to future development of the EPM solution.

Analyze the total cost of ownership, including license fees, implementation costs, ongoing maintenance, and potential costs for upgrades and additional modules.

The ability for team members to collaborate within the EPM platform is vital for efficient planning and performance management processes.

Consider the vendor’s roadmap for future development to ensure the solution will continue to meet your needs as new technologies and business practices emerge.

Choosing the right EPM solution involves a thorough evaluation of your organization’s current and future needs, available budget, and the specific features and capabilities that will support your financial and operational goals.

You may also like: EPM Software Pre-Built vs. Custom Solutions: What Is the Right Choice for Your Business?

EPM Software FAQs

Achieve Peak Performance with B EYE’s EPM Services

B EYE’s enterprise performance management services offer a comprehensive suite for financial planning, budgeting, forecasting, and beyond, utilizing Anaplan for insightful, data-driven decision-making. Our cutting-edge solutions empower businesses to conquer operational challenges and unlock maximum profitability. Connect with us to explore how our EPM services can transform your financial planning, risk management, and operational efficiency.

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