With over 10 years’ experience at Engage ESM, most recently as a Solutions Architect, I keep up to date on industry best practice across all areas of ServiceNow and I’m specifically interested in how improved capabilities within the platform can help organizations in their strategic goals.
2020 will see the new ServiceNow Orlando release bring new functionality and refinements that will help customers make better decisions, solve more complex problems more quickly, and automate their work more efficiently.
The overall theme here is intelligence and, in this blog, I will cover key features in the release - specifically what the improvements to AI, machine learning, and natural language look like, what they mean for the platform, and ultimately how they improve the user experience.
Machine learning and natural language abilities in ServiceNow aren’t new to Orlando, in fact my colleague, James Morrisey, covered this topic when these innovations were first released in the New York release last year. Yet, it is important to recognize that Orlando isn’t just repackaging the same with a new badge, rather it is taking a significant step towards a more natural way of working. This is being achieved by consolidating, improving, and expanding the horizons of AI and continuing the journey to AI-as-a-Service.
Natural language understanding
Natural language understanding (NLU) is a major player in the Intelligence improvements, and with significant numbers of consumers regularly using smartphone speech-recognition technology or interacting via Siri, Google Assistant and Alexa (and Bixby if you swing that way), it’s only natural that this is a direction for ServiceNow to take too.
The previously mentioned blog summarized how NLU works and is implemented, but here’s a quick reminder:
The above all connect into an NLU model which defines how a user can communicate to a ServiceNow application.
Previously, each NLU model was specific to an application, and entities within a model were specific to an intent. Whereas the Orlando version gives users the option to leverage the NLU models and clone them to new applications and move entities to cross all intents within a model.
Besides, the users can now compare and test draft models against published ones, this means when creating or updating a model they can see how much of an improvement or deterioration changes to a model have caused.
Speaking of improvements to NLU models, the introduction of the PA NLU dashboards allows admins to track in real-time communications between users and ServiceNow, offering valuable insights not only to what is being asked but on how well the modeling is handling the user requests.
This all leads to a more natural and consistent experience when communicating with ServiceNow, which really helps when talking about one of the most powerful user experience improvements in Orlando, the Analytics Q&A.
I should caveat this by saying that Analytics Q&A isn’t generally available just yet, but this could soon change how reporting is achieved through your organization.
Generally, reporting and analytics is an involved process that requires a deep understanding of data available and what is required - it is often a time-consuming task.
Imagine preparing for a management meeting. Even if the required data is available in ServiceNow you will still need to output multiple reports to cover numerous topics, and typically to further drill-down on specific data points will require more manual intervention, in turn slowing down decision making and the agility of an organization.
So, what is the solution here? Imagine you don’t have to waste valuable time generating many reports for a meeting but rather you bring your mobile device, then when the conversation swings to supplier performance you can easily bring up a relevant report simply by asking ServiceNow, “How many tickets are with our suppliers right now?” ServiceNow will respond with either a pre-defined report or dynamically create one for you, and leveraging the NLU and machine learning capabilities of Orlando you can even ask more exploratory questions such as, “What are the average change times for Supplier X services?”
The below example shows a manager asking very simple questions and in real-time getting relevant results in the formats that they need:
Orlando has brought to the market a good range of improvements and new features, the platform’s intelligence is very exciting and includes more than just analytics Q&A and NLU improvements, but also predictive intelligence which helps in triage and predicting trends. Also, these enhancements apply to the mobile side as well to mobile branding and mobile analytics which can change the way users view and use ServiceNow as a mobile experience.
This is a significant release that really consolidates and improves the platform baseline, in my opinion, Orlando is moving us to a more natural and intuitive way of working, utilizing the way we interact with technology at home to how we can interact with technology in the workplace, taking the monotony and tediousness out and replacing it with something more approachable.
In the second part of this blog I will explain the Orlando release enhancements for addressing the mobile workflows.
If you would like to find out more information on any of these features, please contact us here.