Exhibit 99.2 

E2Open Product Demo

Transcript

October 14, 2020

Pawan Joshi (EVP, Products & Strategy):

The example I’m going to use here is a brand owner that manufactures laptops and desktops. The business sells its products through two major channels: the distribution channel and the retail channel. It utilizes contract manufacturers to make its product and allows you to quickly navigate down and see the different types of channels (the retail channels, the retailers), what they sold last week, how it compares, how much inventory they’re carrying and how many shipments they’re receiving. The same thing applies across the distribution channels—across their tier 1 distributors and tier 2 distributors.

While this view allows brand owners to operate their channels, what becomes really interesting is the next level of adjacency or the output of this information, which allows owners to figure out what is happening in each channel. In this example, I’m able to detect using demand-sensing. Here there is a 37% increase in the forecast, which is the upside that I have.

The next upstream process adjacent to this runs through the supply plan. The supply plan assesses whether I can meet this 37% upside or not. In this scenario, the answer to that looks like you cannot, and I can only see an 85% attainment of that forecast. As a brand owner, I’m very curious to see why I cannot meet this forecast. In this particular example, I see my planned shipments are not lining up with my forecast. I see that I only have a week and a half of runway before I start running out of inventory.

Because we have the ability to connect into the supply side, we can look through to manufacturing. Here, we can look through to contract manufacturing and see what components are running short. Very quickly, right here on the dashboard, we are able to identify a 50,000 unit memory shortage that results in this $13 million revenue impact, which is what is causing the shortfall.

Because this is an operating platform from the dashboard, at a click of a button, I’m able to navigate down into my supply planning application, understand the requirements and supply plans, and see the projected inventory for that memory chip. I also understand where the depletion happens, and as a planner, I am able to trigger a couple of resolution scenarios. Because this operating platform also allows me to monitor my manufacturing facilities and my suppliers, at a click of a button, I can look at what the supplier is going to see, and I can get a verification of the 50,000 unit replenishment that I’ve asked for.

If the supplier confirms the suggested plan, I can actually go back and get that. The plan is going to rerun, in the back, so the same process happens. Here, I see 50%. 50,000 units come back in as a confirmation, and then I rerun my plan on the supply side. I refresh my dashboard and see my exception going away. My finished goods metric climbs right back up, my planned shipments line up, and I can see a 99% attainment.

This process that I showed you happens every single day. Every minute, every second, and across multiple tiers of the supply chain for any large brand owner, this process is occurring. We have the ability to actually tie this all together to have this run in a systematic fashion because of the applications that we have and the access to information that we have across the board.

Now, we typically don’t stop here. Since I’ve come up with a plan, I also need to monitor the execution of that plan. Using my logistics ecosystem, I can create dashboards that allow me to look at where my ships are, what product is sailing, where it is sailing, and what the state of affairs are. Because of this, I can—with a mouseover on that particular ship—see what bill of lading it’s carrying, what the container ID is, where it is headed, and then more importantly, also predict arrival times. This is interesting just in terms of locating what it is, but what makes our application extremely unique is that not only are we able to figure out whether the shipments are running on time or not, we are also able to figure out the impact of that shipment running early, late, or on time. We can do that because we are not only connecting the logistics and managing that, but are also looking at what happens at the destination. A great example of this is that second shipment when I clicked on impact analysis. I am not going and looking at just that shipment. Rather, I’m actually looking at the final destination of that shipment. Then I have about 6 days’ worth of material there before I start running out of it. I now have a 6-day lead time to go resolve that exception as I go through this process.

I’ll show you what this allows me to do. If I pop back up, our operating platform also comes back with suggested resolution methods to solve this problem. One of them deals with a reroute of that same shipment, a couple of other options include moving material from alternative locations in Chicago or Seattle and then the fourth one is interesting because it’s suggesting an alternative movement of material from Brazil.

But we’ve also gone in and done a trade management to license check. What we’ve been able to do is combine this with what happens at the destination to see the impact. Also, when we are doing suggested resolutions, we are able to evaluate things like global trade, water crossing and logistics to be able to drive a more complete, more consistent, and more unified decision-making process.

At the end of the day, when I’m resolving my exceptions, when I’m planning my supply chain, when I’m looking at what’s happening in the channel and what’s happening to the supply, I can plan better, and more importantly, I can execute better and I can execute and plan holistically.