In this short article, we’ll take a look behind the scenes at the significant benefits of the Data Cloud, including the way it enables AI approaches. We’re looking at three major benefits, and we’ll conclude with some not-so-wild speculation about the way these benefits add up to more than the sum of their parts.
Reason One: Data Sharing
On a tour of the American West during the height of his popularity, humor-columnist Dave Barry offered up this indelible memory of his travel through America’s 43rd state:
“It seems that most of Idaho…is outdoors.”
Still true! Also true for your supply chain — and especially your supply chain data. It’s estimated that 90% (or more) of the supply chain data relevant to your enterprise resides outside of your four company’s walls.
And unlike Sales, HR, or even Finance, where a majority of data is typically being inputted by people within your organization — a majority of supply chain data is coming from partners and systems completely outside of your enterprise. Shipment events and inventory levels and or order statuses — almost all of them, somebody else’s figures.
It takes many hands to make a supply chain run — and while many hands make light work, they’ve also been known to make for iffy data.
That’s because getting this data has traditionally meant a continuous campaign of system integrations and maintenance — and like highway work, the flashing lights and “New Traffic Pattern” signs never rest. With continuous implementation projects, upgrades, and synchronizations, you almost get used to the armies of service providers.
But of course you’d rather not: because it’s brittle, and expensive — both in terms of sheer expense, and in terms of opportunity cost.
However, with a Data Cloud, like Snowflake’s, “construction season” can finally end. Snowflake has introduced Data Sharing, which provides “the ability to distribute the same sets of data resources with multiple users or applications while maintaining data fidelity across all entities consuming the data.” In layman’s terms, any data that’s available in Snowflake’s Data Cloud can be accessed securely without the need for integrations.
The best part? Your data never leaves your Data Cloud. It’s viewed, not moved, so the data stays secure. With this kind of capability, an upgrade here or there finally becomes what it should be: somebody else’s headache!
Reason Two: Process Sharing
By definition, supply chain is multi-party. (Even Radar o’Reilly had a network, right?)
But in the real world a supply chain network is much more than a constellation of pals you can phone when the chips are down. In reality, ever supply chain is a multi-part machine, running at its best when the timing and tuning are just right. This means coordinating activities with carriers, suppliers, manufacturers, and distributors…constantly and continuously.
Of course, this is precisely why supply chain work is so tough: it’s highly manual, decentralized, distributed, and ad hoc. Getting everyone on the same page is literally a full time job.
To date, the best solution to this challenge has been the use of portals. But most portals offer only marginal improvement over the trusty “email with an attached spreadsheet.” Portals can also be costly to set up and maintain — and usability, typically, is janky at best.
Fortunately, much like Data Sharing, data clouds have also enabled Process Sharing. Turns out, it’s not only feasible to share data securely within the data cloud, it’s also possible to share processes. Now, your supply chain team can truly collaborate: working directly with partners on the same data within the same workflows. And we’re not just talking about chat here: we’re talking about a shared platform, the same interfaces for tasks, assignments, and reminders, all secured within the data cloud. That’s because just like data sharing, process-data is viewed, not moved, so you always control it.
The same data, the same workflows…what’s next? Someone to do the work for you?
Reason Three: Automation and AI
Shared, secure data, and shared, secure processes: indeed these offer the essential foundation for advanced technologies like AI and automation. Automation requires good data: to trigger actions at the right time, follow the appropriate conditions, and to execute and check for appropriate outcomes.
According to a recent survey by IBM, 72% of CSCOs expect their processes and workflows to be automated over the next three to five years. And 80% of supply chain leaders would like to use AI to improve their operations.
We think the Data Cloud is the necessary stepping stone for these ambitions to come to life. If you know or work for one of those 80%, and you want to learn more about the benefits of data sharing and process sharing — check out this blog.
Conclusion: More Than The Sum of The Parts
Perhaps the biggest advantage of bringing these “more than” additive capabilities together is the added plus of freedom to innovate. As we noted above, for most supply chains, maintenance is a full time job. What will be most interesting to see is what happens when that’s no longer the case.
What happens when optimization and innovation become our daily bread?
That will be something to see…
Coming up next: 3 Signs your Supply Chain is Ready for Innovation.
