Complex or Simple ERP?

Source: Äri-IT Kevad 2025 (Business IT Spring 2025)

Author: Villu Puusepp, Business Area Developer, BCS Itera

You can answer the question in the title right away: ERP is simple when all inputs come solely from a company’s own data, but it instantly becomes complex when external data sources come into play.

I’ve been a developer at BCS Itera for a relatively short time, and ERP as standalone software was new to me. My first impression reminded me of a modern car engine: you can still replace some parts, but there are others that are impossible or simply pointless to fix. ERP is likely headed in the same direction—it may soon become a system whose inner workings no one truly understands. I’m talking about AI.

Nevertheless, as a developer, you still need to ensure the engine has its oil changed and is using the right fuel. In this article, I’ll explore what additional inputs could be added to an ERP system to ensure its smooth operation.

What is ERP and Where is it Heading?

ERP is business software, but in reality, it signifies an entire system that connects all aspects of a company’s resource planning. This can encompass a wide range of tools and solutions. We’ve discussed the impressive—perhaps even too rapid—evolution of ERP in our previous magazine issues. If Microsoft is to be believed, the old ERP toolkit might soon be gathering dust.

Late last year, I saw a video clip of Satya Nadella (Microsoft CEO) predicting that in the near future, ERP software would be replaced by a single AI interface. This would mean a direct connection between the database and the user—the ERP toolkit as we know it would cease to exist. It would also render thousands of apps and SaaS services redundant. Quite a harsh prediction.

For this reason, I won’t be introducing different tools, but instead focusing on the role of data. Whether ERP is AI-based or not, its performance will always depend on the quality of its inputs.

ERP in the Real World

I recall a fascinating example from an economics lecture at the Estonian University of Life Sciences, likely an introduction to macroeconomics. The lecturer presented an interesting case from Sweden. Whether it was a real incident or hypothetical isn’t important. Unexpectedly, data analysis revealed a strong correlation: the number of injuries sharply increased at the same time as the volume of shoes imported from Italy grew. It turned out that, while beautiful, these shoes were slippery in winter conditions, leading to more falls and injuries.

ERP and Unforeseen Circumstances

Let’s consider that Swedish example in the context of ERP. Suppose a company’s ERP system is working flawlessly: processes are smooth, resources are well-planned, and data is managed correctly. However, the company lacks a broader overview of market and societal changes. If the government suddenly imposes new import restrictions related to Italian shoes or tightens safety regulations, the entire operation would need to be re-planned, or in the worst case, the store might even have to close. This highlights a critical limitation of ERP systems: if they rely only on internal data and lack access to information from external sources, unexpected market shifts will inevitably go unnoticed.

The Main Shortcoming of ERP Today

ERP cannot effectively ensure resource planning if it relies solely on local data. Therefore, it’s crucial for the system to be linked to as many external data sources as possible—whether these are market trends, legislative changes, consumer behavior analyses, real estate prices, or real-time sensor data. Often, important patterns emerge in completely unexpected places.

How Can ERP Get More Inputs?

The short answer: it’s complex and becoming increasingly difficult. One possibility is mutual data sharing—the more information you share, the more you receive in return. In practice, this could mean creating general and anonymous data layers that can be used without violating personal data protection or trade secret principles.

Such data exchange is already happening today. For example, Google shares traffic information based on our mobile phone movements but doesn’t disclose data on specific devices or users. Similarly, data exchange could also work between the state and companies. Currently, data primarily flows from companies to the state, but a more efficient system would allow the state to obtain necessary information directly from a company’s database—of course, according to configured security rules. This would make the process simpler, faster, and less stressful.

Could a Global ERP Have Prevented the Great Depression?

Could global economic data have prevented the Great Depression of the 1930s? This is speculative, but it’s clear that a lack of information or its misinterpretation played a significant role.

At that time, the American economy was tied to the gold standard, meaning the money supply was limited. Simultaneously, the Industrial Revolution accelerated economic growth, creating a situation where asset values should have constantly decreased, but they didn’t. When the imbalance finally shifted too much, the stock market crashed, followed by the Great Depression.

It’s possible that if the economy had constant and up-to-date information on actual trends, the crisis could have been mitigated or even prevented. This shows that ERP-like solutions, which provide a comprehensive overview and real-time data processing, could greatly contribute to economic stability.

Does ERP Work Globally Today?

The global economy follows the same principles as a small business’s balance sheet—the only difference is scale. If a small business’s financial data is accurate down to the cent, why shouldn’t the same apply to the economies of countries and the world, especially in today’s information age?

The main problem isn’t a lack of technology, but rather data quality and accessibility. Leaving aside conspiracy theories that data is deliberately distorted, the reason remains insufficient or inaccurate information that financial models rely on.

New Challenges for ERP Solutions

The purpose of this article is to raise the question: How can data be made more accessible and interpretable? If we find a solution, it could improve existing financial models or lead to a new, real-time model.

On the positive side, ERP systems are becoming increasingly user-friendly, and AI will develop them even further. Therefore, the primary challenge lies in data availability and interpretation. For example, Microsoft Business Central already has a large number of users today, meaning that the global output of an ERP system could already quite accurately reflect reality. Technically, it’s also not difficult to create an API interface that allows for data sharing.

However, this comes with several important questions:

• How can collected data be anonymized and original data privacy ensured?
• How can the interests of wider society be included in this funding model?
• How can we avoid a situation where a large amount of data is concentrated under the monopoly of one company or state?

These questions require well-thought-out and balanced solutions. I believe BCS Itera has the potential to lead a project with such global impact.