Market Insights Technology Software Enterprise Software

Enterprise Performance Management Software - India

India

In 2024, the projected revenue in the Enterprise Performance Management Software market in India is expected to reach €62.82m.
Looking ahead, the market is anticipated to experience a steady annual growth rate (CAGR 2024-2029) of 12.24%, resulting in a market volume of €111.90m by 2029.
It is worth noting that the average Spend per Employee in the Indian Enterprise Performance Management Software market is projected to be €0.12 in 2024.
When compared globally, United States is expected to generate the highest revenue, reaching €2,658.00m in 2024.
India's growing demand for Enterprise Performance Management software is driven by the need for efficient financial planning and analysis in its rapidly expanding business landscape.

Key regions: China, Germany, United States, United Kingdom, Canada

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Analyst Opinion

The Enterprise Performance Management Software market has been growing at a steady pace in India.

Customer preferences: Indian companies are increasingly adopting Enterprise Performance Management (EPM) software to improve their financial planning and analysis. The software helps in budgeting, forecasting, and reporting financial results. The demand for EPM software is high among large enterprises, as they require complex financial planning and analysis. Small and medium-sized enterprises are also adopting EPM software to streamline their financial processes.

Trends in the market: The EPM software market in India is witnessing a shift towards cloud-based solutions. The cloud-based EPM software offers flexibility, scalability, and cost-effectiveness. The software can be accessed from anywhere, and the data is stored securely in the cloud. The demand for cloud-based EPM software is increasing among small and medium-sized enterprises, as it eliminates the need for expensive hardware and IT infrastructure. Another trend in the market is the integration of artificial intelligence (AI) and machine learning (ML) in EPM software. AI and ML can help in automating financial processes, predicting financial outcomes, and identifying patterns in financial data. The integration of AI and ML in EPM software can help in improving the accuracy and speed of financial planning and analysis.

Local special circumstances: India has a large number of small and medium-sized enterprises (SMEs) that are looking for cost-effective solutions to streamline their financial processes. The demand for EPM software is high among SMEs, as it helps in improving their financial planning and analysis. The Indian government has launched several initiatives to promote digitalization and automation in the country. The government's Digital India program aims to transform India into a digitally empowered society and knowledge economy. The program has led to an increase in the adoption of EPM software among Indian companies.

Underlying macroeconomic factors: India is one of the fastest-growing economies in the world. The country's GDP is expected to grow at a rate of 7.5% in the next few years. The growth of the Indian economy has led to an increase in the number of companies and the size of their operations. This has led to a higher demand for EPM software among Indian companies. The Indian IT industry is one of the largest in the world. The industry is expected to grow at a rate of 7.7% in the next few years. The growth of the IT industry has led to an increase in the development and adoption of EPM software in India.

Methodology

Data coverage:

The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the allocation to the country where the money was spent at manufacturer price level (excluding VAT).

Modeling approach / Market size:

The segment size is determined through a top-down approach. We use financial statements such as annual reports, quarterly earnings, and expert opinions to analyze the markets. To estimate the segment size for each country individually, we use relevant key market indicators and data from country-specific industry associations such as GDP, level of digitization, GDP sector composition, and observed level of software piracy.

Forecasts:

We use a variety of forecasting techniques, for instance, advanced statistical methods, depending on the behavior of the relevant segment. The main drivers are the GDP and the level of digitization.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic is considered at a country-specific level.