I recently had a conversation with Dave Wright, Chief Strategy Officer of ServiceNow, about their acquisition of DxContinuum, a Silicon Valley based machine learning company. Derek has already covered the main elements of the story but this update adds some nuance to the deal based upon our conversation.
ServiceNow is a cloud software firm that does a great job of automating the service functions of firms. While the company got its start in the IT area, they’ve also had success in helping internal service groups in HR, accounting and other areas prioritize service requests, quickly connect people to the right subject matter expert (or content) and speed up the workflow of specific and often interconnected groups (e.g., new employee onboarding).
A hallmark of their past success is to help internal groups document the services they deliver, capture (and improve) metrics re: services delivered and meet the service level agreement details that their consumers expect to see.
The DxContinuum deal brings a level of machine learning to ServiceNow’s offerings. Specifically, what ServiceNow hopes this technology will accomplish is to make the categorization and routing of service requests more efficient and automatic.
According to Wright, many companies have service desk personnel who spend lots of (non-value added) time reviewing service tickets and trying to decide who (or where) in the firm this request should be forwarded to. Not only is it labor intensive, it can also be wrong. There may not be a feedback mechanism in this manual process to help these workers do an ever more accurate routing.
Machine learning would allow ServiceNow software to look at piles of prior service tickets and examine the content of the request and who it got referred to. The machine learning would determine what kinds of words, phrases, escalation language, etc. are associated with specific routings.
Based on this historical track record, the software can start pre-selecting specific routings of a number of requests without any initial user intervention. Once in production, the software can continue to learn by detecting new/unfamiliar requests and study how and where at service desk sent these for fulfillment. I do not know if a feedback/correction mechanism is or will be built-in. Great machine learning tools have this and I’d expect ServiceNow would add this to their product line.
There are also other uses for this technology within the ServiceNow suite. Dave discussed how the tool could be used to predict when outages of equipment could occur based on prior experiences. With that knowledge, ServiceNow can dispatch repair persons to not only deal with the causal issue triggering the service request but also send along parts for the repair person to install and thus another service call in the near term.
This tool could also predict what parts a technician might require based on the past experience of prior but similar service requests. This could cut down the number and expense of repeat trips to solve a single problem.
There’s a clear IoT (Internet of Things) angle for this, too. As the number of these devices grows. Consensus estimates run 50 billion connected devices in use by 2020. We can therefore expect the number of service requests to repair, replenish, reset, etc. these devices to balloon accordingly. The efficient analysis and routing of these requests will become a cost-sensitive and critical imperative for companies operating such devices.
ServiceNow intends to integrate both the DxContinuum technology and its entire workforce into the ServiceNow organization. As with any acquisition of a big data, artificial intelligence/machine learning and/or analytics firm, retention of the talent may be the difference between the deal becoming accretive or not.
While my brief conversation with Dave focused on the topics above, we didn’t get a chance to discuss the long-term fate of other DxContinuum solutions (see graphic above). It’s easy to see the artificial intelligence/machine learning capabilities in these solutions, and, that makes it easy to see why ServiceNow is doing this deal.
More on this deal and its integration into the full ServiceNow suite should appear throughout the year and at their next user conference (Knowledge 17). And as Derek pointed out, we look forward to hearing from customers – the ultimate arbiters of value add.
Image credit - via ServiceNow
Disclosure - ServiceNow is a premier partner at time of writing