Can artificial intelligence solve the ERP complexity conundrum?

Note: This article was co-authored by Ben Leane.

ERP systems have had to re-invent themselves many times over to stay in the game of advancing technology solutions. Today, the challenge facing ERPs is different. The Fourth Industrial Revolution presents two problems that need to be solved simultaneously: delivering more, better capabilities, and insights while demanding that teams do more with less. The conundrum is that the solution of one problem works against resolving the other. Could AI provide an "intelligent" answer to this state of affairs?

The need for more

In a changing business environment, competitiveness depends on insight and agility. Here lays the issue, that ERP should be used for decision-making and not as a transactional engine.

These changing demands called for an increase in ERP functionality to include insights, metrics, and KPIs a modern solution needs to cater for. However, by enriching ERPs with these bells and whistles, we increased their data content, and hence made reaching the end goal overwhelming. There should be a way not only to crunch data, but also to provide intelligent insights into trends and relationships that simplify this process for the busy executives. Especially when most configurations allow for one or two tiers of routing logic to be configured.

Artificial intelligence (AI) can play a role in these scenarios by providing insights and ultimately improving the user experience. The best examples of this application are the upsell (buy better) and cross-sell (buy extra) in the retail industry. There are two applications for AI in the service and maintenance industry: predictive maintenance and condition monitoring. This is a funny example though, as condition monitoring can be categorized under insight, whereas predictive maintenance is more of a decision-making engine.