The modern company’s bulky Rolodex of software providers and partners can bog down staffers with license-renewal and security compliance tasks. Can ServiceNow Inc.’s new automation tools hand them off to machines, saving humans time and money?
Dave Vellante (@dvellante) (pictured, right) and Jeff Frick (@JeffFrick) (pictured, left), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, took apart the announcements at the ServiceNow Knowledge17 event in Orlando, Florida.
First up is the Jakarta release for ServiceNow governance, risk, and compliance, which aims to take the headaches out of third-party vendor security. “You have all these vendors that you’re trying to interact with, and you’re trying to figure out, OK, what do I integrate with in terms of my third-party vendors and who’s safe and do they comply to my corporate edicts?” Vellante said.
ServiceNow claims a module in Jakarta can automate that vetting process.
The bigger announcement was Software Asset Management, which garnered many claps and cheers from Knowledge17 attendees. The management tool can tell users precisely what licenses they have so they can better leverage them, according to ServiceNow.
This is a big pain point for customers of Oracle, who use licensing and software audits as major negotiating tools, Vellante explained. “Customers don’t really know what they have, what the utilization is, and they buy more licenses even though they could re-purpose licenses,” he said.
ServiceNow claims that these new tools can boost performance by as much as 30 percent.
Can machines do it all?
Ironically, some of this comes from automating tasks that the least skilled workers in an organization could handle, but which become tedious at scale, according to Frick.
ServiceNow sometimes claims it can eliminate email, but this is not yet a reality in most companies, and ServiceNow’s apps in lieu of email run on cloud, which can suffer from”spinning logo” latency, Vellante stated.
As for whether ServiceNow’s new tools can automate processes that typically require more intelligence, they may not be perfect, but they might abstract away complexity in the early stages, Frick argued.
“Let the machine take the first swag at that and let it learn, and based on what happens going forward, let it adjust its algorithms,” he said.