ServiceNow announces machine learning capabilities to tackle some of the biggest problems in IT today.
With ServiceNow Intelligent Automation Engine, companies can prevent outages before they happen, automatically categorize and route incidents, benchmark performance against IT peers and predict future performance. Capabilities will also bring machine learning to ServiceNow cloud services for Customer Service, Security and Human Resources (HR).
The ServiceNow Intelligent Automation Engine applies machine learning to four of the biggest use cases that IT has today. ServiceNow has taken the combination of massive amounts of contextual operational data, huge R&D investments, and a team of leading data scientists, to address four big challenges for today’s IT organizations ‑ preventing outages, automatically categorizing and routing work, predicting future performance and benchmarking performance against their peers.
“Intelligent automation heralds a new era in workplace productivity,” said Dave Wright, chief strategy officer, ServiceNow. “With this game changing innovation, we have embedded intelligence across our Platform. Trained with each customer’s own data, ServiceNow is enabling customers to achieve a quantum leap in the speed and economics of their business.”
Here are the innovations launched today:
- Anomaly Detection to Prevent Outages —ServiceNow has bolstered its ability to help customers predict and prevent service outages with anomaly detection. The algorithms identify patterns and outlying occurrences that are likely to lead to an outage. Combined with new dynamic threshold measures, the system learns what is the normal range of behavior and flags outliers that can indicate future errors or malfunctions. Initially delivered in Operational Intelligence for IT, the anomaly detection capabilities can correlate past events that led to outages and initiate workflows to pre‑empt future problems when the same preceding events are observed again.
- Intelligence to Categorize and Route Work – ServiceNow will make available machine‑learning algorithms to each customer’s unique data set based on the DxContinuum acquisition. By learning from past patterns, the Intelligent Automation Engine can predict future outcomes, including determining risks, assigning owners, and categorizing work. Initially, this predictive intelligence capability will be used in the IT Service Management offering to categorize and route IT requests with a high level of accuracy. Learned models set the category of the IT request and assign the task to the right team, as well as calculate associated risk of action or inaction. This capability brings new levels of speed and efficiency to IT delivery, and provides a foundation for the future, where connected devices create orders of magnitude increases in service requests.
- Benchmarks to Evaluate Performance Against Peers – Available today, ServiceNow Benchmarks enables customers to compare their service efficiency to peers ‑ such as similarly sized organizations or companies in the same industry. In the past, comparing performance to peers was difficult, if not impossible. Now, companies can not only know how they are performing against their own goals, but how their performance compares to like organizations.
- Performance Predictions to Drive Improvements—The Intelligent Automation Engine powers new algorithms in its real‑time Performance Analytics application to help customers better determine when they will achieve performance goals. Customers set a performance objective and based on the data profile, Performance Analytics uses the optimal algorithm to predict when they will reach the objective.
The Intelligent Automation Engine is part of the Now Platform, which powers cloud services to speed and automate work for IT, Security, HR, Customer Service and custom applications for any department. As the platform evolves, all departments and applications will benefit from intelligent automation. By automating both routine and complex processes and predicting outcomes, every organization can dramatically reduce costs, speed time‑to‑resolution and deliver consumer‑like experiences for employees, partners and customers.
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