Companies use enterprise resource planning (ERP) systems to collect and share enterprise data across business functions, helping them run more efficiently and profitably. These systems provide stakeholders in finance, human resources, project management, supply chain logistics and virtually every business department with access to the essential data they need to inform their daily decision-making.
But raw data alone doesn’t provide the level of business insights needed to stay ahead in today’s competitive market. ERP analytics — the advanced data analysis capabilities embedded in modern ERP systems — allows companies to consolidate, analyze and draw insights from their data to turn it into valuable strategic insights. This article details specific ERP analytics capabilities and advantages, ERP analytics’s role in risk management, important key performance indicators (KPIs) it measures and more.
What Is ERP Analytics?
ERP analytics refers to the process of analyzing data generated by a company’s ERP system to gain insights that inform data-driven decisions. ERP systems integrate business processes and functions, including accounting, inventory management, human resources, supply chain management and more. These systems, by their nature, collect and store vast amounts of data on a business’s sales, production, inventory and financial transactions. ERP analytics involves using tools, such as statistical analysis and business intelligence, to extract actionable insights from this information.
By analyzing ERP data, a business can identify patterns, trends and anomalies, and use this information to optimize its operations, improve efficiency, reduce costs and increase profitability. For example, ERP analytics can help a company identify which products are selling well, which suppliers are providing the best value and which business processes are causing delays or inefficiencies. ERP analytics also helps the business more accurately forecast future trends.
Key Takeaways
- ERP analytics replaces limited, error-prone manual analysis with automation that adds context and insight to crucial business information within an enterprise resource planning (ERP) platform.
- ERP analytics tools include data mining, statistical analysis and reporting.
- With ERP analytics, decision-makers across the business can track and measure key performance indicators (KPIs) and adjust their strategies to optimize performance.
ERP Analytics Explained
ERP analytics helps companies understand the volumes of data captured within their enterprise resource planning (ERP) solutions from across their organizations. This detailed information enhances business reporting and tracks KPIs, giving companies deep insight into what they are doing right, where they can improve and the root causes of their most complex problems. Insight from ERP analytics also helps businesses spot patterns in their ERP data, which they can use to overcome inefficiencies and continuously improve operations over time.
From revenue figures to demand forecasting to inventory turnover, ERP analytics combines, analyzes and presents data to stakeholders in the form of dashboards, charts and other visualizations. Consider a decision-maker in charge of supply chain management. With ERP analytics, this manager can see across every supplier, node and workflow in the company’s supply chain, with detailed information on how each piece of the puzzle is performing in real time. For example, if the supply chain manager notices that an overseas supplier repeatedly delivers its products late during adverse weather events, they might instead choose to source the materials from a local manufacturer to avoid costly delays.
This makes ERP analytics a form of actionable reporting. Rather than simply presenting a business with static summaries of raw data, actionable reporting provides practical insight and steps that stakeholders can take to address concrete business challenges and capitalize on new opportunities.
ERP Analytics Components
Specific tool sets in ERP analytics include data and text mining, data visualization and descriptive analytics, all of which add rich context to a company’s data. These tools are often enriched by advanced technologies, such as artificial intelligence (AI) and machine learning (ML), which allow for the rapid analysis of large and complex data sets. The following ERP analytics tools help businesses draw value from the growing volumes of data their ERP systems create and collect across multiple business functions.
Data Mining
Data mining is the process of uncovering links, patterns and anomalies in large data sets. It involves extracting and analyzing data from an ERP system’s centralized database to uncover hidden information that can be used for decision-making and prediction. For example, data mining in ERP analytics can be used to identify which products or services are most popular among customers, which suppliers are the most reliable or which production processes are the most efficient. Data mining can involve simple statistical analysis or employ advanced technologies, such as AI and ML. The goal is to unearth insights that drive improved performance, increased sales, cost savings, risk avoidance and other forms of business value.
Performance Metrics
Performance metrics allow companies to compare current performance data with historical data to track their progress — or lack thereof. These insights tell them whether they need to stay the course in their operating strategy or adjust their approach to meet performance objectives and business goals. ERP analytics solutions often display performance metrics on business intelligence dashboards to paint a complete picture of a company’s performance and simplify decision-making. Some examples of performance metrics in ERP analytics are inventory turnover, on-time delivery and sales growth.
Reporting
Actionable reporting provides insights that suggest steps a company can take based on its organizational data. In other words, actionable reports don’t simply convey a raw data summary; rather, they provide pragmatic and practical information that inspires decision-makers to take initiative, solve business problems and jump on new opportunities. Unlike manual reports that present data and results in the form of simple spreadsheets, reports created using ERP analytics present results in the form of charts, graphs and visualizations. These formats bring context to a business’s performance data, making it more digestible for stakeholders in every department, regardless of their level of data expertise.
Descriptive Analytics
Descriptive analytics is one of the most basic and common types of analytics. It often uses basic mathematical operations to summarize and highlight patterns in current and historical data, allowing decision-makers to compare past and present performance so they can make informed choices about future strategies. For example, finance teams might compare quarterly sales figures or yearly market share data to gauge how the business is performing and where it needs to focus to meet its strategic objectives.
Statistical Analysis
Statistical analysis allows businesses to dive more deeply into their ERP data to understand the reasons behind their current performance drivers and roadblocks. Statistical analysis takes the data generated by descriptive analytics one step further by using statistical techniques, such as regression analysis and hypothesis testing, to uncover patterns and relationships that enable data-driven decisions based on large data sets.
Data Querying
Data querying refers to the process of retrieving specific data from a company’s ERP system using query languages or tools. It involves writing and executing queries against the centralized database of an ERP system to retrieve the required data based on specified criteria. Data queries are generally made in the natural computing language of the ERP system. For instance, Oracle SQL database administrators use Oracle SQL coding language to query information in their database environment. The output of a data querying request can be as simple as a specific data point or as complex as a deep data-mining exercise to uncover hidden trends in a company’s ERP data.
Data Visualization
Data visualization is the process of representing data generated by a business’s ERP system in a graphical or visual format, such as graphs, charts, plots, maps and dashboards. The purpose of data visualization is to make complex data sets more understandable and easier to interpret by presenting them in a clear and concise manner. For instance, a car manufacturer might use a histogram showing supply chain performance over the years alongside seasonal fluctuations in shipping delays to better predict its production capacity ahead of peak demand periods.
Data Preparation
Data preparation is one of the most important steps in ERP analytics. It involves combining raw data from multiple sources, cleansing that data to avoid duplication and inconsistencies and labeling the cleansed data points so they are ready for further processing and analysis. Data preparation also ensures that analyses are conducted using a complete and robust data set, which, in turn, delivers the most accurate and valuable business insights.
Visual Analysis
Visual analysis allows users to explore and interact with data visualizations in real time, providing an intuitive and responsive way to explore and analyze the data. Users can drill down into specific data points, change variables and parameters and dynamically update visualizations to see the impact of changes on the data. This type of analysis is often likened to visual storytelling because it brings a narrative framework to complex data sets. In the case of ERP analytics, this narrative framework helps data experts in finance, human resources, procurement and other departments communicate the findings of their analyses to decision-makers so they can make informed choices quickly and with confidence.
Advantages of ERP Analytics for Businesses
ERP analytics allows teams across a business to better understand their operations and make informed, data-driven decisions. With real-time insight into their performance, from financial results to the success of marketing campaigns to the efficiency of supply chain operations, businesses can determine what works, what doesn’t and where they must improve to drive revenue, growth and customer success. The advantages of ERP analytics include:
- Improved demand forecasting: Demand forecasting helps businesses anticipate, prepare for and meet customer demand for their products and services ahead of time. ERP analytics provides companies with both historical data for comparison and real-time insight into their processes to identify where and when they need to adjust to meet demand. For example, an accounting firm must anticipate demand for its year-end tax services ahead of the tax-filing deadline in April and make sure it has the necessary resources, bandwidth and headcount.
- Deeper understanding of customer behavior: Customer data is a staple of ERP systems. Marketing, sales, customer service and other teams collect and draw insight from this data to better understand their audience and meet their needs. For instance, marketers might personalize email offers based on a customer’s recent purchases. Contact center workers might bring up a caller’s previous interactions with their business to make sure they use the most up-to-date information available when serving them. ERP analytics makes access to accurate customer data across the business a breeze, leading to improved service and stronger customer relationships. The better a business can gauge customer preferences and buying patterns, the better it can forecast future patterns and behavior.
- Real-time market insights: Economic uncertainty, geopolitical shifts, fluctuating currencies, supply chain delays — the only constant in today’s economy is change. ERP analytics helps businesses predict and adapt to these shifts proactively, keeping them one step ahead of change and putting them in the best position to gain a competitive advantage. It predicts market fluctuations, identifies opportunities and helps management make appropriate decisions. With immediate access to real-time market data, businesses can predict with confidence and optimize their operations to gain a competitive advantage.
- Data that drives growth: Growth occurs when a business can identify and capitalize on new opportunities. That requires a complete picture of its operations, its customers and the overall market, as well as a precise understanding of where there’s room for improvement. ERP analytics not only combines all of a company’s ERP data in one place, but it also allows teams to use that data to model change — be it a new product launch, expansion into new territories or a shift from overseas to local suppliers — and understand how it will affect the business. Leveraging predictive analytics keeps guesses and speculation out of the game and uses data to make difficult decisions.
The Role of ERP Analytics in Business
Businesses that have invested in an ERP system expect more than just a large data repository; they expect business value in the form of insights and growth. They expect to unlock new sales opportunities, drive operational efficiency and cut unnecessary costs from their daily operations. In short, they want to be proactive in the way they use their ERP data, which is exactly what ERP analytics delivers.
ERP analytics helps businesses achieve the desired return on investment after implementing their new ERP system. More specifically, ERP analytics enables businesses to uncover the root cause of their performance issues, weed out inefficiencies in their business processes and optimize the cost of operations. ERP analytics also improves data quality and governance. Strict data management and preparation methods ensure that data sets are clean and up-to-date, and that stakeholders are making decisions based on an accurate view of their business and its customers. Additionally, ERP analytics can help businesses ensure compliance with regulatory requirements and internal policies by providing real-time monitoring and alerts that help identify issues proactively, reducing the risk of fines and legal liabilities.
The Impact of ERP Analytics on the Market
To understand the impact of ERP analytics on business performance and the wider ERP market, it is helpful to draw parallels with Major League Baseball. Access to real-time data on players and their performance under a variety of conditions has completely changed the game in recent years, giving coaches, managers and owners a data-driven, objective understanding of what they have, what they’re missing and what it will take to win. The standard of play today says it all, with players pitching better and batting and scoring more runs than ever.
ERP analytics has done the same for the ERP market. With the ability to see granular data on individual business processes, as well as big-picture visualizations of a business’s operations, decision-makers have turned ERP data into an invaluable asset for their companies. By leveraging the insights provided by ERP analytics, businesses can optimize their processes, reduce costs and improve customer satisfaction. In fact, Gartner predicts that ERP data will be the basis for 30% of AI-generated predictive analyses and forecasts in 2023.
Risk Management Options in ERP Analytics
ERP analytics empowers businesses to effectively manage risk. Leading solutions include governance, risk and compliance (GRC) capabilities that make it easy for businesses to set the data controls they need to meet their risk objectives. Built-in data preparation and quality processes are designed to meet complex regulatory requirements, such as security operations center (SOC) security and International Organization for Standardization (ISO) compliance standards.
The automation features of ERP analytics tools also help to reduce risk. The technology is purpose-built to monitor, track and record changes in a business’s data, be it customer insights collected by sales, employee data from payroll or financial updates from accounting. Not only does this ensure a clear paper trail, but it also removes the risk of human error from the equation. Additionally, ERP analytics plays a role in reducing fraud. By continuously monitoring key financial controls through saved searches, alerts and regular reporting, the role-based dashboards generated by ERP analytics can draw a business’s attention to activity that might be fraudulent and worthy of further investigation.
Measuring Business Success With ERP Analytics
Most businesses measure their success using a list of KPIs. The reports, dashboards and visualizations provided by ERP analytics allow companies to assess these KPIs accurately based on a real-time view of their data and operations. Here are a handful of KPIs that businesses can measure using ERP analytics.
- Customer experience (CX): CX metrics are a business’s most important measure of success. Every decision, investment and process a company implements aims to benefit customers — be it a direct investment in a new customer service platform or operational improvements to increase efficiency, such as the migration of legacy IT infrastructure to an agile environment. CX metrics, including customer feedback, product delivery times and fulfillment accuracy, help companies understand what they’re doing right and where they need to improve to drive sales and enhance customer success.
- Revenue growth and sales: Revenue and growth metrics tell a business how much money it has earned from the sale of its goods or services over a given period of time. Common revenue and growth metrics include average profit per item sold, average order value and operating margin. By using ERP analytics to track these metrics over defined periods, such as quarter over quarter or year over year, businesses can uncover trends that drive the highest revenue and adjust their strategies to capitalize on them. They can also use this data to identify their weakest revenue streams and look for ways to cut costs to minimize their losses.
- Inventory turnover: Manufacturers use inventory turnover as a measure of how quickly they can move products. For instance, a semiconductor company that supplies the automotive industry might have an inventory turnover of 50,000 units per week. The more products a company can move, the more it can sell and the higher its revenue and level of customer satisfaction. Data generated by ERP analytics can provide insights into inventory management.
- Project margins: In project-based industries, such as construction and consulting, project margins tell companies how much money they have made after subtracting their expenses to complete a project. For a construction company, those expenses include labor, materials, overhead and internal delays, while for a management consultancy they might include office space rentals and employee travel expenses. ERP analytics can be used to combine project data, including costs, budgets, expenses and revenue, to develop a complete picture of how project margins are tracking.
- Productivity: Inefficiency is the enemy of profit. Be it equipment failures in a warehouse facility, supply chain delays for an international distributor or reduced employee output in a manufacturing plant, companies need a way to track and minimize productivity roadblocks wherever they can. ERP analytics make it possible for businesses to uncover where and when these inefficiencies occur so they can be addressed. For example, a logistics company might notice that shipments are increasingly being delivered late due to staff shortages, prompting it to rethink its shipping capacity or hire additional drivers to meet demand.
- IT spend: Businesses want to extract the most benefit from their IT investments at minimal cost. Mature companies are particularly sensitive to technology spend as many have built up a tangle of legacy IT systems over the years that are costly to run, integrate and keep up to date. ERP analytics puts the cost of hardware, software and cloud subscriptions at decision-makers’ fingertips so they can look for ways to optimize their spend and reduce costs without sacrificing performance.
Implement ERP Analytics With NetSuite
ERP analytics analyze data generated by a business’s ERP system to provide insights that help leaders make informed, data-driven decisions and improve performance across the business. NetSuite SuiteAnalytics provides companies with real-time visibility into their operational data, as well as business intelligence dashboards embedded directly into their ERP systems.
Rather than requiring companies to build performance reports and business intelligence dashboards from scratch, NetSuite SuiteAnalytics comes equipped with pre-built reports and dashboards based on industry best practice, helping businesses make better decisions faster. Self-service features within the solution ensure that analysts and decision-makers from every department can access the data they need without waiting for IT. Additionally, NetSuite SuiteAnalytics’ central database reduces the time needed to combine and prepare data for analysis, making reporting more accurate and efficient.
15 Universal Metrics All Orgs Need to Track
Access to real-time data is the key to measuring and driving business success. Equally important is a consistent view of data and performance across teams so that every stakeholder is equipped to make informed, data-driven decisions that help the business stay competitive in today’s rapidly evolving marketplace. This is where ERP analytics adds tremendous value, allowing businesses to consolidate, analyze and draw insights from their data to turn it into valuable strategic insights.
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ERP Analytics FAQs
What is ERP in business analytics?
Businesses use enterprise resource planning (ERP) systems to gather, analyze and share insights among multiple departments. ERP systems connect the dots between business processes to find efficiencies. Real-time data analysis with ERP analytics allows them to connect more data points from more sources in more complex ways, opening the door to deeper business insights and better decision-making.
Is ERP a part of analytics?
Enterprise resource planning (ERP) systems provide companies with a great deal of historical data to inform their reporting and data analyses, but they do not bring context to this data. For that, companies need business intelligence, which uses analytics to compile data into dashboards and visualizations that reveal valuable business insight.
How do analytic capabilities enhance ERP systems?
If enterprise resource planning (ERP) systems are a historical record of a business’s enterprise data across departments, ERP analytics is the historian that knows all of that data by heart and can apply their knowledge to bring context to that information. In turn, this context helps stakeholders make sound and well-informed decisions about how to optimize their operations.
What types of reporting can ERP systems produce?
ERP systems can generate a range of reports across business functions. Common examples are quarterly financial results, supply chain performance reports and recurring back-office reports on invoicing, procurement and payroll.
What is the role of analytics in an ERP system?
Enterprise resource planning (ERP) analytics involves the consolidating, mining and query of business data to extract actionable insights. These analyses help users identify trends and patterns to inform their decision-making, optimize their teams’ operations, drive profitability and cut costs.
What is ERP data analysis?
The role of enterprise resource planning (ERP) data analysis is to gain actionable business insight to drive data-driven decision-making. The output of ERP data analyses are reports, dashboards and data visualizations that track key performance indicators (KPIs). In turn, this information tells businesses how they are performing and how they can improve across key areas.
What is ERP in simple terms?
Companies use enterprise resource planning (ERP) systems to collect and share enterprise data across business functions. ERP systems provide teams in finance, human resources, project management, supply chain logistics and virtually every business department with access to essential data that informs their daily decision-making.
