People & Leadership

Advanced analytics: Unlock the future of business insight 

Learn how advanced analytics gives you deeper insight and the ability to make data-driven decisions.

People in an office

Advanced analytics gives you deeper insight and the ability to make data-driven decisions. You want to be able to predict future trends and make the best of your operations.  

We’ll explore advanced analytics’ definition, importance, types, and benefits, illustrating how crucial it can be for modern business success. 

Here’s what we’ll cover

Discover Sage Intacct

Our cloud financial management platform delivers deep accounting capabilities across multiple industries designed with a single aim—to accelerate your success.

Learn more about Sage Intacct

What is advanced analytics?

Advanced analytics refers to techniques used to analyze data beyond traditional business intelligence (BI) methods.  

It encompasses various sophisticated techniques, including predictive analytics, machine learning, data mining, and big data analytics, to uncover patterns, predict outcomes, and generate actionable insights.  

Unlike basic analytics, which focuses on historical data, advanced analytics aims to forecast future events and behaviors. 

Types of advanced analytics 

There are several types of advanced analytics, each with its own set of techniques and applications: 

Predictive analytics

It uses historical data to predict future outcomes.

Techniques include statistical modeling, machine learning algorithms, and regression analysis. 

Prescriptive analytics

Suggests actions based on predictive analytics. It uses optimization and simulation algorithms to recommend the best course of action. 

Descriptive analytics

It focuses on summarizing historical data to understand what has happened.

It includes techniques like data aggregation and data mining. 

Diagnostic analytics

Explores data to understand the root causes of past performance.

It involves techniques like drill-down analysis and data discovery. 

Big data analytics

Analyzes extensive, complex data sets that traditional data processing software cannot handle.

It involves distributed computing and advanced data storage solutions.

The financial benefits of advanced analytics

Improved financial decision-making  

Advanced analytics provides a comprehensive view of financial data, leading to better strategic decisions.  

Data-driven insights can significantly boost decision-making and accountability, allowing you to allocate resources more effectively and get the best financial performance. 

Increased revenue and profitability 

Your business can increase profitability by identifying new opportunities and optimizing existing processes.

Advanced analytics helps uncover revenue drivers, streamline pricing strategies, and maximize financial returns. 

Enhanced risk management 

Predictive analytics enables CFOs to anticipate and mitigate financial risks before they become significant.

You can implement proactive measures to safeguard the company’s financial health by identifying potential threats and opportunities. 

Operational efficiency and cost savings 

Identifying inefficiencies and optimizing financial processes can lead to significant cost savings and improved productivity.

Advanced analytics can help you streamline operations, reduce waste, and achieve cost-effective financial management. 

Better financial transparency and reporting 

Advanced analytics provides detailed insights into financial performance, improving transparency and accountability.  

Use these insights to produce accurate and timely financial reports, ensuring compliance and improving stakeholder confidence. 

Advanced analytics in the real world —Resson

Resson, a bioinformatics and predictive analytics company, uses Sage Intacct to boost financial visibility and transparency.  

This integration supports Resson’s executive team in making timely decisions based on accurate data and predictive analytics, helping them invest wisely in key verticals and new crops. 

Predictive capabilities

Resson uses near-real-time predictive analysis for crop management. It aids agricultural companies in optimizing yield and managing costs effectively, which translates into better financial planning and forecasting. 

Operational efficiency

Advanced analytics can identify inefficiencies in financial processes, optimize operations, and reduce costs.  

Resson’s adoption of the Sage Intacct financial management solution streamlined its financial processes, saving workdays and shortening its financial close by more than 50%. 

Customer insight

By analyzing financial data related to customer transactions, you can better understand business needs and preferences, helping you develop personalized and effective financial strategies.  

Resson’s ability to tag transactions with specific business contexts allows it to generate detailed insights into customer profitability and project costs, further enhancing financial decision-making and operational efficiency.

AI: Automation and generative AI

Artificial intelligence (AI) is changing the nature of advanced analytics through automation and generative AI (gen AI).  

Automation in AI refers to using algorithms and machine learning models to perform repetitive tasks without human intervention.

This increases efficiency, reduces errors, and allows employees to focus on more strategic activities. 

Gen AI, on the other hand, refers to algorithms that can create new data, designs, or content based on the data they have been trained on.  

For example, gen AI can simulate market scenarios, create realistic customer profiles, or generate new product ideas.  

Gen AI can significantly enhance predictive capabilities in AI analytics by providing more comprehensive scenarios and potential outcomes. 

What AI means for the future of advanced analytics

The integration of AI and advanced analytics has profound implications.  

According to our report, The Secrets of Successful CFOs, 79% of CFOs believe AI will improve revenue growth, and 77% think it will enhance job satisfaction.  

Despite AI’s high adoption rate in general, only 51% have fully used AI-powered finance tools, indicating a significant opportunity for growth in this area​​. 

Look at these opportunities with AI and automation going forward. 

  1. Enhanced accuracy and efficiency. Automation can handle large volumes of data quickly and accurately, allowing for more detailed and reliable analytics. 
  1. Innovative solutions. Gen AI can create new possibilities by simplifying the simulation of different scenarios and outcomes, providing businesses with innovative solutions to complex problems. 
  1. Scalable insights. AI-powered analytics can quickly scale to handle increasing data loads, making it easier for businesses to adapt to growth and changing market conditions. 
  1. Real-time analysis. AI supports real-time data processing and analysis, allowing businesses to make immediate decisions based on the latest information. 
  1. Personalized experience.: AI can analyze customer behaviors and preferences to deliver highly personalized experiences, enhancing customer satisfaction and loyalty. 

Real-time analytics come into play by offering CFOs and other executives such as CEOs, COOs, and department heads the ability to make quicker, more informed decisions. 

Rohlik Group CFO Vineta Baja says: “Internal stakeholders request information in real time, and they should have it in real time. The right tools should be the bread and butter of finance functions now, and if they’re not, they should be at the top of your agenda.” 

Vineta says traditional methods, such as outsourcing or changing business processes, are less effective now because of changes in the global economy. 

Vineta believes CFOs must think of new ways to solve problems. She says: “Often, there is no need to wait until the month end to understand business performance. Real-time data, BI, and data scientists can help move the future of finance from a month-end cycle to an ‘on demand’ cycle.” 

Discover Sage Intacct

Our cloud financial management platform delivers deep accounting capabilities across multiple industries designed with a single aim—to accelerate your success.

Learn more about Sage Intacct

Use cases for advanced analytics

Advanced analytics can be applied in various industries to drive growth, improve efficiency, and enhance customer satisfaction. Here are some industry-specific use cases: 

SaaS (Software as a Service) 

SaaS companies can use advanced analytics to predict customer churn, optimize product features based on usage data, and personalize marketing efforts.  

Predictive analytics could identify at-risk customers, which can help you create targeted retention strategies and significantly reduce churn rates. 

Non-profits

Non-profits can use advanced analytics to track donor behaviors, improve fundraising strategies, and measure program effectiveness.  

By analyzing donation patterns, non-profits can identify the most effective channels and times for fundraising campaigns, increasing overall donations. 

Professional services

Professional service firms can use advanced analytics to optimize project management, forecast demand, and improve client satisfaction.  

By analyzing past project data, professional service firms can better allocate resources and predict project timelines, leading to more successful outcomes. 

Healthcare

Healthcare providers can use advanced analytics for predictive diagnostics, patient risk stratification, and optimizing treatment plans.  

Predictive analytics can help identify patients at high risk of readmission, allowing for targeted interventions that improve patient outcomes and reduce costs. 

Financial services

Financial institutions can use advanced analytics for fraud detection, risk management, and customer segmentation.  

Banks can detect and prevent fraudulent activities by analyzing real-time transaction data more effectively. 

Hospitality

The hospitality industry can use advanced analytics to optimize pricing strategies, enhance guest experiences, and improve operational efficiency.

Hotels can personalize marketing efforts and increase occupancy rates by analyzing booking data and guest preferences. 

Construction and real estate

Construction and real estate companies can use advanced analytics for project planning, risk assessment, and market analysis.

Predictive models can help identify potential delays and cost overruns, helping you take proactive measures to keep projects on track. 

Retail

Retailers can use advanced analytics to optimize inventory management, personalize customer experiences, and forecast demand.

By analyzing sales data, retailers can ensure they have the right products in stock and offer personalized promotions to increase sales. 

Distribution and manufacturing

Manufacturers and distributors can use advanced analytics to improve supply chain efficiency, predict equipment failures, and create optimal production schedules.

Predictive maintenance models can help reduce downtime and extend the lifespan of machinery. 

FAQs

What is the difference between advanced analytics and traditional analytics?

Traditional analytics focuses on descriptive and diagnostic analytics, analyzing historical data to understand what happened and why.

Advanced analytics includes predictive and prescriptive analytics, forecasting future events, and recommending actions based on those predictions.

How can advanced analytics benefit small and mid-sized businesses?

Small businesses can use advanced analytics to gain insights into customer behavior, optimize operations, and identify new market opportunities.

This can lead to increased efficiency, better decision-making, and higher revenue.

What tools are commonly used in advanced analytics?

Standard tools include machine learning platforms, statistical analysis software, big data processing frameworks, and data visualization tools.

Is advanced analytics only for tech-savvy companies?

No, advanced analytics can benefit companies of all sizes and industries. Implementing it may require expertise, but many user-friendly tools and services make it accessible to non-technical users.

What are the challenges of implementing advanced analytics?

Challenges include data quality and integration issues, the need for skilled personnel, and the initial cost of implementing advanced analytics solutions.

However, the long-term benefits often outweigh these challenges. 

Final thoughts

Advanced analytics can transform your operations, providing deeper insights and supporting you with more informed decision-making.  

By understanding and implementing advanced analytics, your business can gain a competitive edge, improve operations, and better serve customers.

As technology evolves, the importance of advanced analytics in business will only continue to grow. 

Resson’s success story with Sage Intacct illustrates the practical benefits of advanced analytics in improving business visibility, decision-making, and operational efficiency.  

With the right insights, your business can optimize its processes and drive growth, so you remain competitive in a world of data.