If you have been thinking if there’s anything beyond rate reduction negotiations with suppliers that the oil and gas supply management organizations can offer to their enterprises, then you should know that your ask is very real. Positioned on a rig of enterprise data including demand, prices, contracts, emails and production output, along with huge online data, these supply chain management organizations can contribute to-
Here, machine learning is a great mobilizer. You will find it very amusing to note how machine learning algorithms source data from this enterprise data rig and make predictions without very elaborate and exhaustive programming. Yes, but while technology and data are so easily accessible, we do not see many organizations able to tap enough of this rig of data.
Where is the Challenge?
The challenge is in grooming mindsets that can leverage advanced analytics. Too many supply management organizations directly starting off with the development part without a clear knowledge of the drivers. Then when the outcome is not very commendable and adds not enough value, the supply management organization loses its credibility.
Now there are many advanced analytics vendors that offer self-serving portals that do not require huge understanding or experience of machine learning, data science, or even basic statistics to help its users with predictive and prescriptive models. But organizations that have been able to successfully implement advanced analytics approach strategically instead of diving headlong into the vantage it offers.
Key Drivers for Effectiveness of Advanced Analytics
The effectiveness of advanced analytics in supply chain management is driven by-
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