10min. Reading time, Written by: Ruxandra Ionescu

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We are in a modernised world in which technology and digitalisation can be found in various aspects of life. Business processes and procedures are moving faster. Thus it is important to have the right “tools” for the real-time interpretation of data. Numerous Business Intelligence (BI) tools are already being used in companies, but serious decision errors can still occur. The reason lies often in  a misinterpretation of the data due to their actuality. Business Intelligence products work with outdated, aggregated data and do not reflect the actual situation. They are also not very user-friendly in their application.

Therefore it is worth taking a closer look at data-based analysis tools and focusing on real-time systems. There are considerable differences between classic business intelligence Tools.

In the further course of this article we will explain what these differences  are and what you need to pay attention to through the following points:

1. Problems of classical Business Intelligence (BI) solutions
2. Advantages of real-time data systems
3. Application examples

  1. Problems of classic BI solutions 

• Complexity – traditional tools are not user-friendly

The goal of a business intelligence tool is to make information accessible and usable. For this to happen, not only the user interface but the entire handling of the system should be simplified so that the tool can provide clear support for the user. In reality, however, conventional BI tools are too complex, so that users quickly lose motivation to deal with the software.

• Rigid systems – processing aggregated, periodised data

A classic business intelligence system,  processes and periodise data  by so-called ETL routes (Extract, Transform, Load) . This takes place, for example, once a day or at night. The data is summarised in blocks and after the processing of the data by the ETL run, the user can view the finished report. If the user needs another report, he/she has to wait until the periodised ETL run is running again so that data can be processed into another report, which again is rigid and slow.

• Distortions of reality – past data is processed

Through the use of traditional business intelligence tools, the analysis of a company is done with data that does not reflect the actual state, but only a time record from the past. Thus, through the use of conventional BI tools, reports, quarterly and annual financial statements, etc. are created with outdated data records. Here, no timely reaction to current circumstances can take place, which in turn can lead to bottlenecks and wrong decisions.

Therefore, it is of utmost importance to be able to process real-time data in order to create appropriate measures in time. Real-time data systems or real-time business monitoring systems can support this.

2. Advantages of real-time data systems

• Scalability for visualisation of the actual state

The functioning of a real-time data system is characterised by the transmission of data to the target system. If five changes (events) occur per second, these five events per second are promptly transmitted to the system.

In comparison, a classic business intelligence tool collects data records from the last period in staggered form and processes them into a report. As a result, decision-making is based on data that is already out of date and does not provide a view of the current state.

• Better overview of impending problems through integrated alerting systems

Built-in alerting systems provide insightful information quickly and easily, giving a significant competitive advantage. For example, failures can be displayed promptly via the dashboard and additionally alerted by message (SMS, mail, etc.). It can also provide helpful support for any company-relevant planning such as personnel deployment, warehouse capacities, resource management, etc.

• Intuitive usage options through SSBI (Self Service Business Intelligence)

Data interpretation and analysis are often associated with complex processes. This may well be the case if the software solution is not too user-friendly. Real-time monitoring systems often have the considerable advantage of a simple and intuitive usage, in the form of self-service business intelligence or SSBI, so that not only experts can work with them, but also personnel from other departments. The advantage here lies in the decentralised collection and processing of data, which in turn leads to an optimal overview of the entire company. In addition, this relieves the IT staff so they can take care of tasks that have a higher prioritisation.

• Real Time Data for Holistic Monitoring of Processes

A Real Time Business Monitoring System relies on the processing of real-time data. Real Time Business Monitoring systems not only analyse, but also offer an all-round monitoring of company-relevant processes with the question: What is currently happening in my company? This means that problems can be reacted to as quickly as possible and not only after an error has occurred. Furthermore, potential for improvement in the company can be uncovered, which in turn leads to new opportunities, such as:

• Higher economic efficiency
• Cost savings
• Better customer loyalty
• Performance optimisation
• Opening of new lines of business

3. Application examples

There are many possible applications for real-time data systems. The potential has already been recognised and used by many industries. The following application examples should explain why Real Time Business Monitoring systems are becoming increasingly popular:

Application example 1: Quality measurements on the assembly line

In the industrial sector, quality standards are set to shape the final product. Therefore, measurements have to be taken again and again to check whether the specified quality criteria are being implemented. Here, real-time data systems can record the measurements to find out how the quality turns out, or where there could be potential difficulties and how often they occur.

In order to measure the profitability of the company, targets are set by management in the form of KPIs (key performance indicators). Example: The maximum failure rate of one piece in a hundred. Here, these targets are measured with sensors. If a piece fails, this is displayed on the dashboard in the form of a KPI. It can be seen how many pieces out of a hundred actually have a problem.

Application example 2: Stock measurements to prevent cancellation rates 

A package is ordered via a webshop. As a target, this package must arrive at the customer within two days. If the delivery time is delayed, the cancellation rate increases and customer satisfaction decreases. By using real-time data systems, logistics partners can be connected to the supplier’s tracking carrier. The system measures the time when the package was handed over or when the customer received the package. This makes it possible to create a guideline value.

Example of a guideline value: A parcel from the warehouse takes one day and 7 hours to reach the customer. The person in charge can evaluate the data and set optimisation measures. If the time were shortened, customer satisfaction would be even higher, so here the target value can be reduced to 24 hours. Also in the course of a process change, the user can monitor it by using a monitoring system. Here, for example: A change in the carrier or changes in the warehouse so that the goods can be taken out more quickly. In the course of the changes, the person concerned can observe the changes in real time and evaluate for himself whether something has actually changed or whether the value remains the same.

Application example 3: Automated company control through real-time business monitoring

Companies are currently often managed with a combination of BI systems and Excel reports. Data from the previous period is collected, processed into a report and combined with a conventional BI system. Relevant business decisions are then based on this data. These are compared with the results of the next period.

The approach of a real-time data system is to work with current data. In case of impending problems, the system automatically sends out a warning signal so that it can react promptly. Every change is thus automatically checked.

The goal of real-time data systems is to automate corporate management in the future so that reports no longer have to be read. In this way, the increasingly complex reporting system can be dismantled.

Conclusion: 

Business Intelligence solutions are already being used in many companies. However, there are still challenges in corporate management. Fundamental decisions of a company are often based on information from the past. This, in turn, is associated with an enormous expenditure of time and an increased error rate, as warning systems are rarely integrated. Among other things, the application of conventional business intelligence can be complex, so that companies cannot derive any advantage from it.

Real Time Business Monitoring systems offer considerable advantages in this respect, as they work with real-time data and are simple and intuitive to use. In addition, they offer a holistic view of the entire company through the decentralized use of data. Integrated alerting systems also ensure that processes run smoothly.