AI Can Make Your ERP System Powerful (Like Amazon’s)

February 5, 2020


Some manufacturers, taking a cue from Amazon’sOpens a new window e-commerce business, have begun to integrate artificial intelligence technology into their Enterprise Resource Planning data platforms to deal with an age-old problem: swollen inventories.

The difficulty facing the so-called asset-intensive sector is that separate, or siloed, databases can be created in ERP management systems that in turn can lead to redundancies that overstock your products.

Until now, the only solution available to most manufacturers was to conduct a routine, manual cleansing of databases that sometimes took long hours or even days to complete.

The stand-downs prevented their ERP platforms from responding to dynamic business developments and skewed revenues.

Self-teaching tech

One company’s manufacturing system is rarely similar to another’s, requiring individual solutions that are costly to design and implement.

But you may not be aware of how far artificial intelligence tech has traveledOpens a new window within ERP platforms. It’s now capable of wading through multiple systems engaged in an asset-intensive manufacturing process and producing suggestions for your in-house teams, on a real-time basis, while also learning from the decisions your teams make.

The technology teaches itselfOpens a new window based on your management priorities, and hones its suggestions to the solutions that have been implemented. That way it can match itself to the unique footprint of your manufacturing process.

Among its benefits, artificial intelligence can quickly create a rich overview of the process you may already monitor with your ERP system, analyzing data siloes that previously were neglected or overlooked.

Artificial intelligence can deliver a digitized network footprint of all goods, services and logistics that flow through a supply chain.

Many ERP systems must grapple with inconsistent naming conventions or catalogues created during data sharing between disparate ERP systems.

Taking guesswork out of planning

But it goes further. AI also can pick up on trends in your market and provide predictive inventory analysis for indirect maintenance, repair and operationsOpens a new window (MRO) and direct goods or finished products. This means your teams don’t have to rely on subjective calls as to likely demands.

>Your plants can access the most immediate requirements within your inventory on a per-plant basis, which means data managers and plant personnel get a better picture of your inventories.

The technology also takes a lot of the data crunching off the table.

With supply chains so tight, it’s bound to become a critical, must-have element for ERP systems.

A customized artificial intelligence solution can be designed, developed and deployed quicker than you might expect —  within 12 to 24 months. An off-the-shelf solution could be operational within 90 days but might not be as effective.

The end result is optimization of your production lines and happier customers. Your company could deliver the sort of experience that big distributors like Amazon already offer.

Key takeaways:

  • AI tools are now available to help your company get over some of the inefficiencies that can creep into all ERP systems – even the best.
  • Predictive analytics and the ability to crunch data in real time means that AI can make your manufacturing process far more responsive.
  • Companies such as Amazon have raised the bar as far as customer expectations are concerned. Tolerance for lack of inventory is going down all the time, while AI can offer a solution.
  • Many management teams realize that innovation is the best way to meet their financial and customer-service goals but they have not considered AI solutions.

Santiago Perez
Santiago Perez

Researcher & Entrepreneur, VitalBriefing

Santiago is an entrepreneur, researcher and designer of sustainable urban strategies. With in-depth knowledge of urban planning, sustainability and resilience, he's an expert in circular economy and environmental tech.
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