I’ve been contemplating technology enabled tectonic shifts in industry. Of course, AI is topical. There’s something more fundamental happening, particularly in asset-heavy industries.
Whether a manufacturing facility, an energy asset or large-scale construction projects, there has traditionally been a distinction between the science applied using machines and the commerce that has powered the businesses that surround this technology.
Process control systems run the machines in the first instance and are walled away from complex IT systems running businesses worldwide. However, it is the combination of insights from these domains that powers business intelligence.
For example, knowing the supply and demand from your ERP system enables optimal manufacturing scheduling. Operational asset insights help businesses optimize not only their maintenance, but also their procurement and supply chain.
Data siloes between these domains meant that users reverted to the most prolific information system out there – Microsoft Excel, creating intricate workbooks typically based on weekly or even daily data exports.
But the modern business is a real-time business and squeezing value from your operations means leveraging real-time trustworthy insight that drives desired human action.
Enter cloud tech which is firmly finding its place in industrial companies too. Sensors have never been cheaper, and it has never been easier to take data from these sensors and input it into the cloud. The compelling insights one can create by marrying operational and business data is differentiating. Applying modern AI capability and the skies the limit.
The workflow of:
(a) getting data into the cloud at the right frequency;
(b) joining it together;
(c) creating AI-driven insight;
(d) delivering it for optimal user experience; is a pre-requisite.
Cloud providers boast great platform technology, process control vendors boast predictive operational insights, and ERP vendors make your business tick through complex logic.
There are very few companies that are trying to bring together these traditionally distinct domains and do the hard graft of going through all the steps from data to insight to experience.
I believe our IFS.ai strategy wins with customers here – we don’t sell an AI platform or a separate AI app. We are doing the hard work of wrangling all the necessary data (a lot of which we already have) to deliver specific AI use cases for each of our target industries and surface that insight into the experience our customers already utilize – IFS Cloud.
We already help customers with manufacturing scheduling optimization, asset maintenance planning and field service optimization – all these use cases marry core operations data and structured ERP, Asset, Field Services data. And we have another 100+ Industrial AI use cases we are actively prioritizing on our roadmap.
There is bound to be convergence between science and commerce. Companies that can effectively leverage software to dismantle data siloes will unlock value from transitioning into real-time businesses.
SOURCE: KUMAR V. (2024,JUN 11). HOW AI FITS INTO ENTERPRISE TECHNOLOGY. IFS BLOG. https://blog.ifs.com/2024/06/how-ai-fits-into-enterprise-technology/
