Real-Time Data Analytics: How ERP Systems are Empowering Business Leaders?

Real-time data analytics relates to collecting, processing, analyzing, and interpreting data, just as it is generated. Modern businesses are becoming increasingly dependent on real-time data analytics since market conditions have become so volatile and dynamic, making historical data redundant. 

This technology is linked to Enterprise Resource Management Systems (ERPs). An ERP system functions as a one system that integrates the core functions of a business such as finance, sales, supply-chain, HR and more. 

The synergy between real-time data analytics and ERP systems empowers decision-makers to act swiftly, seize opportunities, and drive business performance. Real-time data analytics combined with an ERP system is the key to unlocking a competitive edge in today’s dynamic business world. ERP systems have different characteristics, including recording data in real-time as well as integrating it with multiple departments.

How ERP Systems Collect and Process Data?

ERP systems collect data mainly from user inputs from multiple applications and modules. Once this data is stored, it is then processed against different parameters to analyze and evaluate if any action has to be taken. 

In order to process the data further, ERP systems work on the principles of Data Validation and Data Verification. Data Validation refers to checks on accuracy, completeness, and adherence to predefined rules and constraints while Data Verification refers to cross-referencing data with master data as well as performing duplicity and accuracy checks.

Real-Time Analytics Capabilities of ERP Systems

Let’s say you went to the shop to buy 9 packs of chocolates. Assuming the shop had 10 packs of chocolate, and you bought 9, the ERP system will not only record low-inventory, but will automatically communicate it to the supplier that the stock of chocolates is now low. As such, the supplier will be intimidated to process the next shipment of chocolates. The same information will also be updated on other systems such as sales. 

Earlier, this was a big hassle, because businesses were not able to keep track of business operations on a high level like an ERP could. This often led to problems like shortages and surplus, leading to ineffectiveness throughout the business and ultimately losing big chunks of money.

Benefits of Real-Time Data Analytics in ERP Systems

ERP and Real-Time Data Analytics can do wonders together in  a number of ways, including: 

  • Timely Decision Making: The fundamental reason for real-time data analytics is to ensure the decisions are taken on time, and there is no halt to any department within a business. The timely decision making factor leads to numerous financial benefits as well with improved efficiency. 
  • Data-Driven, Continuous Improvement: Consistently collecting and analyzing data allows businesses to improve their systems. Organizations can identify areas for improvement, track the effectiveness of process changes, and measure the impact of improvement initiatives.

Empowering Business Leaders with Real-Time Data Analytics

Modern businesses are already using and benefiting from real-time data analytics, allowing them to make timely decisions. Business leaders are able to evaluate large volumes of data with simplistics versions offered by real-time data analytics programs.  

Examples of Real-Time Data Analytics in Action

In recent times, the era of e-commerce has taken the world by storm, and that has made real-time data analytics and deployment even more important. Take the example of If you purchase or even search for a certain product, you aren’t only shown related items, but you are also shown advertisements regarding the same product again on your social media as well. 

The websites track real-time data including time spent, cart abandonment rates, click-through rates (CTR), and browsing patterns to offer you products according to your requirements. This data is analyzed to personalize product recommendations, optimize pricing strategies as well as offer promotions in real-time. 

These statistics are highly volatile and may have changed compared to just a few months old data. Therefore, data analysis of the most recent data would not only be the most suitable approach, but it will be the most logical one too. 

Impact of Real-Time Data Analytics on Business Performance

Real-time data analytics help in improving business performance. However, this is highly dependent on the aspect of analysis. If a company has tons of data but perceives it in a wrong manner, the real-time data could become counter productive. 

In the larger context, however, there has been evidence of improvement in business performance through real-time data analytics. One report by McKinsey suggests that real-time analytics have helped in improving productivity levels between 5% and 30%. 

From a customer’s perspective, real-time data analytics can do wonders. According to a study published in Harvard Business Review, companies leveraging real-time analytics in their sales and marketing efforts experienced an average of 16% increase in revenue while 58% respondents also agreed that it helped in customer retention. 

Implementation of Real-Time Data Analytics in ERP Systems

It is quite evident that real-time data analytics can do wonders for a business. However, its implementation remains the elephant in the room.

Best Practices for Implementing Real-time Data analytics in ERP systems

  • Step 1: Scope and Objectives – Scope is defined as the boundary of a project while objectives relate to what a company aims to achieve out of it. Usually, with real-time data analytics, every company has a different approach. Some may want it for inventory management, while others such as airlines, would want it for service management. That’s why the scope and objectives need to be defined clearly. 
  • Step 2: Choosing an Appropriate Real-Time Data Analytics Tool – With the arrival of numerous ERP systems as well as real-time data analytics tools, choosing the right combination is important. Scalability, ease of use, and integration capabilities are the most important factors to consider. Some of the best tools include Microsoft Power BI, SAP Analytics Cloud, Oracle E-Business Suite, and IBM Cognos Analytics.
  • Step 3: Deployment – Deployment is the most crucial phase of merging the two. Most problems arise in this stage including bugs, as well as glitches, which are then fixed by a technical team.

Challenges of Implementing Real-time Data Analytics in ERP systems

One known problem in merging the two is deployment, as this is the stage where most glitches, errors, bugs, and other problems are likely to occur. However, beyond that, problems like Data Governance are also a big challenge. Since many companies like Oracle now offer an online ERP system, like the E-Business Suite, they have access to valuable data of a company. Although it is claimed to be encrypted, the ideology of one having sensitive business data is still a potential concern. 

Another big challenge is the excessively high cost of development and integration. Neither are ERP systems cheap nor are real-time data analytics tools. Prices can vary from $15,000 to $100,000 and even more in certain cases. This brings us to the concept of Return on Investment. Many businesses suggested that it took them years to get the return on this investment, and when they did, the technology was outdated. 

Overcoming Implementation Challenges

Not all solutions work equally well for every type of business. Some might be able to solve deployment issues by using hybrid ERP systems instead of cloud-only ERP systems. Cloud ERP systems work virtually and there is no need for physical storage devices, while Hybrid ERP systems work use both cloud and private systems. A company can choose to retain highly confidential data in their own servers, and process the rest in the cloud. 

On-premise ERP deployment allows a company to retain all of the data on its own physical servers. However, this option requires a lot of capital investment and is usually suitable for large enterprises.

To avoid potential glitches, full-scale testing of the newly deployed ERP system is advised. Besides, the company should retain their conventional system for at least 6 months after the ERP. This allows for a transition period and serves as a backup in case any issues arise during the initial stages of ERP deployment.

As far as internal security of the systems is concerned, ERP should be deployed with multi-factor authentication (MFA) for user access to enhance security. Modern ERP systems have several security modules like Intrusion Detection and Prevention Systems (IDPS) or Security Information and Event Management (SIEM). Such modules ensure that the security of the data is not compromised at any point. Moreover, to avoid any future problems, latest security patches and updates should be incorporated into the system.

It’s logical to opt for a phased implementation approach to manage costs and mitigate risk. Step-by-step implementation will reduce chances of any glitches, and ensure that costs are spread over a certain period. 

Future of Real-Time Data Analytics in ERP Systems

Future of Real-Time Data Analytics in ERP Systems

Fortunately, despite all the challenges, the future of data analytics and ERP systems looks bright. 

Emerging trends in Real-time Data Analytics

With the impact of AI, real-time data analytics is expected to BOOM even more. Programs like ChatGPT, Google Bard, and others will be able to process data, analyze it, and give a human-like decision based on the provided information. Earlier, the machines could only offer an analysis, but now, they will be able to advise business owners on their next step.

Future Developments in ERP Systems for Real-time Data Analytics

The future of ERP systems is bright with the impact of AI coming in strongly. Decision making will shift from minutes to seconds, thanks to evolving deep learning and AI systems. It is also forecasted that real-time dashboards, visual analytics, and augmented reality (AR) or virtual reality (VR) interfaces will be used on a greater scale to present real-time data in more intuitive and actionable ways. 

There is also a speculation about ERP systems getting more proactive and acting like a “Mobile Application” which sends you out real-time alerts and notifications based on predefined thresholds or anomalies in the data. For even better analysis, ERP systems will be integrating external data sources such as social media, real-time stock market data, weather data, and customer sentiment analysis.

Potential Impact on Businesses

Businesses will see a positive impact of real-time data analytics and ERP systems. Decision making will be improved significantly, and overall productivity will rise too. However, it is still quite expensive for any business to manage and handle both at the same time. Besides, global leaders have already highlighted concerns regarding AI and its aggressive development, which could ultimately impact businesses too. For example, AI systems might store sensitive information or data from a business ERP system and use it for analogy in another business’ case. 


ERP Systems and Real-Time Data Analytics have already started transforming the e-commerce industry. Business leaders have seen significant improvement in their business processes, operations, as well as profits with the right deployment, integration, and management of ERP systems. Data analytics trends show a promising future too, while the recent adoption of AI, machine learning and deep learning means we’ll start seeing these technologies integrated into ERP systems for enhanced productivity and efficiency.