For PLOS, there are three areas we're looking at. The first is automation. And I think technology is growing. We've got a couple of pilots underway in areas of machine learning that might help with something like PLOS Match that currently works based on algorithms. We've seen that begin to deteriorate over time. Our matching rate four or five years ago for papers coming in was around 85%. It's now dropped to somewhere around 55%. And we've taken a look at that. Some of that is around needing to tweak the algorithms, but one of the challenges we have with PLOS ONE is how many papers we are now receiving that are multidisciplinary in nature. And so the idea of being able to match that to a single editor is much, much harder.
So we need to be able to look more broadly at the metadata we're getting, even being able to scan and understand the article abstract to really gain a clear understanding of what the paper is about, and therefore, who the appropriate reviewers are. I think there are ways in which smart automation can help with all of those things.
In other things, we have a series of fairly clear technical but ethical scans for papers that come in right away, before we do anything. That's particularly important on PLOS ONE. Given the volume of submissions, we don't want to be sending things out for review that are a waste of our time or a reviewer's time. And I do see things there that can be automated. Some things are still going to need an eye on them afterwards, but I think we could take away a significant amount of work there.
The second area is industry standards. We were having a conversation about this over dinner last night, around why industry standards take such a long time to develop. Or even when they are developed with things like ORCID, why is it taking us so long to have them widely implemented? Ultimately, I think it comes down to money, and the fact that you look at an organization like ORCID, and it's operating on a shoestring.
If ORCID is something that's so important to all of us, that doesn't feel like a good thing to be happening. So how do we collectively solve that problem? Some of it is around politics, if we're honest about it. I mean, this is a smallish industry. And we've got a few big players, but then we've got tons of smaller players. And I think we all like to think about the ways in which we differentiate ourselves from each other, far more than we think about our common interests, and the way in which we need to collaborate for the greater good of all. I think that hampers us with a lot of these initiatives.
The third area is standardizing the way we work with libraries and consortia. I'm not sure that that's possible or even desirable, necessarily, to do fully across publishers. But I think as we're going into this, I learned a lot from implementing Big Deals going back 10, 15 years when I was at Sage. Coming away from that, what we're trying to do it at PLOS is to have our definition of, “Here are the three things we can offer, and then maybe small tweaks that we can offer to those.” But the idea that we're going to do a distinctive deal for every single library or consortia that we speak with just isn't something that we want to get into, because it's just not scalable. And it's even less scalable, I think, in an open access world, where the revenues are not the same, and the margins are not the same, as they were for a subscription business, in many cases.