What are the most exciting things your organization is working on?

The most exciting thing we're doing is leveraging both our financial investments and our technology stack. We're reexamining our architecture and making sure that our tools are all integrable. By having a rich set of tools, knowing how the APIs work, what's available and what each of these discreet things can do, we’re able to bring solutions much faster, whether it’s using something as big as Workday or something as small as our texting platform. I can put the small pieces together and come up with a solution without buying something big.

Instead of thinking of software as a circle where there's a need and then we buy a solution, I keep telling people that we're buying gears. We still need to buy a circle that fits your needs. We have to buy a texting platform, for example, but we need to make sure it's got robust APIs and good web services.

We're finding clever uses for all of these things with individual solutions that were never purchased for those particular purposes. We've got the pieces and my team is getting very smart at understanding how the APIs work and how to use them to build solutions like bots. We have a password reset bot, which is critical. 75% of all the calls that come to our help desk are password resets, so we built a bot that can query Workday to find out key information about you, send you a text message using our texting platform, have you enter the code and then go behind the scenes into AD and reset your password for you; that’s all automated. We couldn't have done that if the pieces didn't go together. I didn't have to spend money on any major technology, because we already had all the pieces.

We’re working with a big insurance company that has a large IT budget. The CIO needs to find efficiencies in their budget, so we are building a small model for them where we'll be injecting their contracts data, user logs data, market data around contracts, data from procurements, etc. We’ll start by identifying where the leakages are in their overall spend. For example: Are they not negotiating properly with the big companies like IBM, Microsoft or AWS? Then we can help them find easy ways of saving money. It's a basic example of a machine learning (ML) model but we are looking at a lot of other stuff, like employee engagement and automation.

For one of our other clients, we are working on automating their entire talent acquisition process, which will reduce the burden on recruiters. And we are also working on something with a few of our customers as POC to give every person in the company a digital assistant. If you need to set up a meeting in a conference room, for example, you can use the digital assistant. You tell the bot, "I need to set up a meeting with these three people." It finds the conference room, the time, etc. That's just one example of the digital assistant’s capabilities.

We are doing speech analytics as well, so the CEO can ask the digital assistant, "How many logos did we acquire this quarter?" The CEO shouldn't have to ask the COO, who then has to ask some analytics person; this is a direct query that can be entered into something like Slack. The speech-based analytics is an automation, but then you also have a bot that you can talk to, which can dump that information. And we are also building security into it, so nobody can randomly request things. It looks at your provisioning levels and authorization levels first and then it completes the request.