Enterprise Analytics
Analytics is used by companies to drive continual performance improvements in focus areas of interest to the company. Analytics can be used to drive a company's whole business or just specific operations, depending on the maturity of the analytics programs within the company along with the maturity of the data and processes or products which generate the data.
Analytics requires measurrments to be made, called Key Performance Indicators or KPIs, at regular intervals so that data can be collected over time and analytics "dashboards" can be designed and built to analyze the collected data and yield visual insights that can be tailored for different stakeholders such as C-suite executives, senior management or operational roles like product managers in engineering or service-line owners in IT.
These visual dashboards are used to drive the analytics value-chain as shown below:
Note that this value-chain is a continual process and not a one-shot; analytics data is fed into the left hand side of the process on a continually updated basis, sometimes monthly, weekly, daily, every hour or as best can be achieved in "real-time".
Analytics in the enterprise context can be used to aggregate data on a global basis so companies can gain insights and make decisions based on real-world data coming from their global operations or global product deployments. So, enterprise-level analytics is generally the most extensive form of analytics available to companies as opposed to edge-analytics or device-analytics.
Enterprise analytics generally stops short of 100% automation, which is more the domain of machine learning and other artificial intelligence technologies. Analytics is a decision-action assist technology that uses real operational data gathered over long periods to provide trendiing insights, in "real-time", into areas that need attention - in IT for example, Incident SLAs may be being breached so analytics can be used to provide visibility into SLA performance over time and decisions can be made to take remedial actions that drive towards the required performance levels.
IT Analytics
ServiceNow®
The ServiceNow® portfolio of products and services are widely used by enterprises to help drive digital transformation to streamline and enhance workflows in IT, HR & Customer Services. This cloud-based portfolio of software components is built on a common core, the Now Platform®, with a single data model so users can extend core functionality using common platform APIs to implement their own custom applications to run on the platform.
Licensable modules provided off-the-shelf include components used in IT:
- ITSM for streamlining service management,
- ITAM which integrates the physical, technological, contractual, and financial aspects of IT hardware and software assets,
- ITBM for aligning IT workflows with business goals,
- ITOM which helps IT gain visibility across infrastructure and apps, maintain service health, and optimize cloud delivery and spend.
as well as components used to streamline workflows across HR, Customer & Field Services, Security Operations and Finance.
ServiceNow® Performance Analytics
The platform includes Analytics, Intelligence &Reporting modules which together increase user productivity and help optimize process workflows . Performance Analytics (PA) is the in-platform analytics tool used to build analytics dashboards which drive the analytics value-chain above. Because PA is in-platform and the platform has a single data model, PA can be used to drive perfromance across all the different components (ITSM, ITBM, ITOM, HRSM etc).
Analytics dashboards have to be designed, built and maintained; why? Everybody's data is different and what they want to do with that data varies considerably. Hence analytics dashboards tend to be highly customized, which requires expertise with the platform data model, with the different components with analytics best practises and with PA itself.
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