Behind the Oracle Cloud SCM news - how do cloud applications help customers address logistics visibility?

Jon Reed Profile picture for user jreed February 16, 2024
Summary:
Oracle just released a host of new Cloud SCM logistics features, including new modeling and automation functions. But how do cloud applications change logistics? How are we addressing the visibility issues that have plagued customers in search of real-time tracking? Here's what Oracle's Srini Rajagopal had to say.

Businessman solve untangle the rope to find a solution. Business concept illustration © riedjal - Shutterstock
(© riedjal - Shutterstock)

Another quarter, another slew of functionality from Oracle to make sense of. In this case, I'm referring to the latest logistics features added to Oracle Cloud SCM.

I had a reporter ask me - what is newsworthy about this latest release? What's most newsworthy isn't the release itself - it's how logistics cloud customers can absorb new functionality at this kind of pace. And: how these new features directly tie to customer requests and requirements.

Historically, logistics just wasn't a cloud business. Updates came slowly and painfully, transparency was elusive ("where is my shipment?") and data silos were everywhere. So how did we get here? That's a question worth digging into with Oracle's Srini Rajagopal - Vice President, Logistics Product Strategy. But first, a rundown of some of the new features. As per Oracle:

  • Expanded Business Intelligence Capabilities: Enables customers to combine transportation and trade data with other operational data in Oracle Fusion Data Intelligence.
  • Enhanced Logistics Network Modeling: Helps logistics managers to model different scenarios and compare different scheduling options for drivers.
  • New Trade Incentive Program: Enables customers to simultaneously automate support for multiple country-specific trade programs.
  • Updated Oracle Transportation Management Mobile App: Mobile apps support for third-party transportation service providers and fleet-managed drivers
  • Improved Workbenches: Help logistics managers quickly and easily create highly configurable workbenches.

Logistics challenges need new solutions

But during my chat with Rajagopal, the Oracle SCM capabilities that really jumped out were of the predictive/AI variety. As Rajagopal told me:

We can already predict for you the ETA on a shipment, and we do that in a far more sophisticated way than you typically would see. We actually give you the predicted ETA right when the shipment has been planned, even before it starts moving. You can do this for any geography. The advantage of having it when the shipment has just been planned is you haven't really done anything on that shipment yet. Now if you know the shipment is at risk, you can actually take action now and fix things.

It's worth noting: this is not generative AI beta feature talk, but predictive AI that is well-tested in production scenarios. But that doesn't mean modern logistics is a cakewalk. Quite the opposite - Rajagopal says these logistics capabilities are all derived from the challenges customers now face. Take Logistics Networks Modeling (LNM) as an example:

Logistics Network Modeling is a capability that actually we put in the product, in response to our customers coming to us and saying, 'Hey, you know, we really need a way to use all our data that's in the product, to then figure out how to model - how to design our transportation networks for resilience.'

So how do I know if a port is going to shut down? How do I easily figure out what's my next best port to ship through? And how do I know that I have enough capacity to get through that port? How do I know that I have the right carrier relationships, and the carrier network to actually go through the port, and reach my customer through that port? And then how do you do that? That's what LNM does for you.

But these advanced modeling and predictive capabilities can't be magically sprinkled on any kind of legacy infrastructure. It's no accident these features stem from a standardized data structure, via modern cloud applications.

So let's break down how these components add up to a better approach. I asked Rajagopal to pull apart each area, starting with this: why are customers driving this change? No surprise there - Rajagopal says the pandemic was a huge wake up call. Customers faced the reality: their supply chain infrastructure was legacy - not nearly resilient enough for the world we live in now.

Ever since the pandemic, we had customers coming to us saying, 'We know our stuff has shipped from this vendor in China, but I have no idea where it is. And when it does get here, I find out after it arrives, several weeks later, when someone opens the door and unpacks it.' customers really woke up to that need for visibility to what's going on in their supply chain.

How cloud applications changed logistics

An integrated logistics platform is a clear need. By why cloud? Why do cloud applications excel for delivering such a platform? Rajagopal says one big key is that cloud applications make it possible for the smaller players in a logistics network to easily connect and extend network visibility. Without cloud applications, that isn't happening: 

When we looked at the clutter we used to sell on-prem many years ago, and then we switched to selling cloud, we found what really helped was: it opened the market for smaller customers who may not necessarily have thought it profitable to lay down an enterprise grade logistics system and keep it running. Now they find it much more easy to do that, because all you're doing is you're consuming it off the web, right?

You don't need to have hardware; you don't need to manage your own data center; no need for DB admins and all of these other skill sets that were required to have an enterprise grade application running. You don't need to know how to patch it; you don't need to know how to upgrade it - all you're doing is using the application. So it really opened up the space and the ability for smaller customers to take advantage of solutions like these.

The shipment of new functionality via SaaS is a clear benefit - though in my experience, companies do have to adjust to a new set of challenges around how to put that functionality into play (but: they strongly prefer those challenges over the on-prem variety). But that's not the only benefit of a standardized cloud architecture. Rajagopal:

So all your extensions and customizations, which you can still do, are done through APIs, and are done via what's called our PaaS Cloud Platform, and works with our SaaS Cloud. So from an end customer perspective, you have all of that power, but from a SaaS application vendor perspective, my application and my data schema stays standard, which makes it easy for me to deliver all those upgrades and enhancements to you on a rapid cycle. So it's sort of a win-win for both the customer and for us.

But now, there is a more potent benefit to this particular approach. It's obvious that a common data platform is superior for analytics and predictive modeling. But it's also a big advantage for applying new AI features also.

My take - how do we move from logistics silos to next best actions?

There has been something of a debate around whether you can realistically do AI on-premise. What I think we're learning is that while on-prem AI certainly can be done in a one-off type of way, it's harder to distribute that functionality across customers, given the variations in the data structure and code base.

Building AI into standard data structures gets a better result, especially when you want to scale it across your customer base. This allows vendors like Oracle to focus less on the plumbing chores, and more on the types of customer needs Rajagopal's team is working on, such as building AI into supply chain decision support, via next best actions, etc.

And yes, gen AI is on deck for Oracle logistics customers as well. In my view, the most compelling aspect of gen AI in the logistics space is the potential to create easier interfaces for on-the-go logistics professionals, who are rarely able to peruse screens on a desktop. It's easy to see how an interactive mobile front-end would fit into their day-to-day.

You can't get rid of logistics silos overnight. I've found that even the logistics operations giants like Amazon still have blind spots in package visibility, at least when it comes to the unfortunate folks in Amazon customer support charged with tracking down outlier shipping problems.

But managing logistics customers on SaaS brings new ways of tracking all of this. Of the items Rajagopal and I talked about, the most compelling to me was the ability to surface aggregate metrics, in an anonymized fashion:

It's extremely secure - Oracle ourselves will not be able to access a customer's business data, but we can see the performance metrics of how the system is behaving for them... We have automated metric collection and alerting. If we think something is going wrong, we can tell the customer: 'You did something in the last week that caused this process to slow down, and you need to take a look at it. Because if the performance continues to degrade, then it could cause issues for you down the road.'

Making supply chain course corrections nearer to real-time has obvious financial value. The ability to do that via metrics applied to your industry is another piece of the puzzle. When you are able to monitor these types of bottlenecks across customers, there are typically some surprises. Often we are measuring the wrong things - or overlooking a more important indicator. That's a topic I plan to pursue further.

Supply chain and logistics problems aren't going away. This type of practical modernization talk is something I think we can all agree is overdue, so let's get to it.

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