Future enterprise decision making needs decision intelligence, not ERP - Image by Oleg Gamulinskii from Pixabay Talk to a business leader about digital transformation, data, analytics, or systems, and Enterprise Resource Planning (ERP) will inevitably rear its head. Composable ERP has long been the foundation for the efficient recording and execution of core business processes in large-scale organisations.

But in 2023, the age of the so-called perma-crisis and where we produce some 50x more data than we did in 2010, the ERP as the linchpin of corporate software is looking increasingly out-of-date.

ERP delivered a huge step change in how organisations manage their resources and core processes. Paper-based documents (invoices, credit notes, purchase orders) became electronic records. They allowed businesses to create, process, and track resources more efficiently, consistently, and at a greater scale than ever before. This breakthrough meant businesses could better automate their operations. It led to an order of magnitude improvement in the efficiency of managing an enterprise-scale organisation.

In short, the advent of ERP was massive for its time, helping codify business processes into software. This helped establish a reliable, usable system record of business transactions that could be used for downstream processing and analysis. Yet to keep up, it needs to harness decision intelligence, a technology dubbed the next evolution in enterprise resource planning.

Decision intelligence is a game changer; it applies AI to decision-making processes across every aspect of an organisation to boost performance. It allows the complex chain of cause and effect across the organisation to be analysed, understood, and visualised for decision-makers. Achieving this requires capabilities well beyond those of what we know as ERP.

Why ERP isn’t enough for the future

While ERP has been a staple of company’s tech stacks since its inception in the ‘60s and ‘70s, two ongoing phenomena are proving beyond its capabilities to handle:

  1. the massive explosion in data spurned by the internet and connected devices
  2. the increasingly disorderly world in which organisations operate today

The rapid growth of data has left ERP playing catch-up and highlighted a flaw with modern business processes. If data-driven decision-making is the best approach, why has our decision-making capacity not improved at the same rate?

The reason for decision-making languishing behind the exponential growth of data is that focusing on data first is misguided. Businesses should instead begin by looking at the decision first. They must figure out which hypotheses to test and what data will be useful for that.

Existing systems, such as ERPs, struggle to make sense of disparate and disconnected data. ERPs can often be insular and focus on data they create and capture themselves. This usually means there is a disconnect across departments, and decision-making is determined by silos. Instead, businesses need to understand and connect what’s happening across the entire organisation to gain a holistic understanding.

The world in which businesses operate is increasingly disorderly. Stability is hard to find from geopolitical conflict to environmental jeopardy to rapidly shifting customer trends, not to mention major global economic and health emergencies. This means that the same decision, made in two different parts of the world or at two different points in time, doesn’t look the same. You often don’t have the same information about your customers in say, Indonesia as you do in, say Switzerland.

All that means is the ERP playbook of standardisation and control doesn’t fit the bill. Organisations need agile operating processes to keep afloat against such a volatile backdrop. Existing software systems fail to address these challenges and, as such, are negatively impacting decision-making and agility in an increasingly complex world.

Decision Intelligence is the natural evolution of ERP

Against this backdrop of challenges, businesses must find new ways to support, augment, and automate decision-making. Decision intelligence – which uses AI to help businesses see what is happening and will happen across their organisation, to understand why it is happening, and to decide what they can do about it – is the answer. The technology incorporates various decision-making techniques by bringing together traditional and advanced disciplines to help model, monitor, and execute decision-making processes.

Decision intelligence is not the new ERP, but instead a powerful tool working on top of the ERP to bring organisations’ decisioning capabilities up to scratch for the modern day. It acts as an intelligence layer on top of existing architecture to draw out greater insights and ultimately make better decisions.

This technology moves us beyond the era of the ERP by bolstering human decision-making with probabilistic forecasts, counterfactual analysis, and optimised scenario plans. It allows business leaders to move beyond data towards a deeper understanding by answering the how and the why.

It’s time for businesses to embrace enhanced decision making

The next evolution beyond ERP is here. It’s time for business leaders to adopt decision intelligence if they want to solve the problems of the next digital age. The exponential growth of data and the increasingly uncertain operating environment is not going to slow down. ERP, as we know it, is not built to handle these challenges. Now, business leaders can ensure their decision-making technology is up to speed by blending traditional ERP with the advancements of decision intelligence, helping to bolster organisational decision-making for years to come.


FacultyFaculty is one of Europe’s leading applied artificial intelligence companies. We build, deploy and operate AI solutions to increase our customers’ performance and help them realise their full potential. We believe that AI should be safe, ethical and beneficial across society. Those principles have shaped our work with more than 350 organisations across the public and private sectors as we help them use AI to understand more deeply, make better decisions and act faster.

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