The analytical journey in IT Service Intelligence and Service Management starts from understanding the demand for services and ends in analyzing how the services were delivered. Combined with ServiceNow, Numerify delivers end-to-end insights into your IT services supply chain, and features dashboard analytics of your key data sources.

service-on-demand-icon Service Demand Analysis

SLA Performance  Management

resolution image Resolution & Fulfillment Effectiveness

backlog-icon Workload & Backlog Management

root-cause-icon Root Cause Analysis

customer-satisfaction-icon Customer Satisfaction

Service Demand Analysis

Employees, students, contractors and partners all want something from the IT organization. As an operational leader, you have to understand and forecast how this demand is shaping up and plan your resources accord- ingly. It is important to understand where, when and why the demand for service varies so that the response can be adjusted accordingly. Numerify’s ITSM solutions will help your organization reach these goals.

Key analysis

  • Which service catalog items are being used the most within each category and what is the average fulfillment time for these items?
  • What is the total cost of the service catalog items requested in the last quarter by department, normalized by the size of the departments?

SLA/Quality of Service Management

Having a clean, accurate and timely view of SLAs is important for several reasons – whether it is to show the efficacy of the organization or to identify training opportunities. When SLAs are breached, you want to analyze those incidents or service requests, slicing and dicing the data a myriad of ways to pinpoint the root cause.

Key analysis

  • How has my SLA trended over time by assignment groups and help desk locations? Which of these groups are consistently the best performers? This is key for making better business decisions.
  • Are there some patterns such as multiple routing or assignment, timely escalation not triggered, ineffective KEDB, lack of training of the support engineer, performance issue of the configuration item and so on.

Resolution & Fulfillment Effectiveness

Reducing backlog is achieved either through either increasing the number of fulfillers or increasing effectiveness of each fulfiller. In this age of doing more with less, it is imperative to investigate how resolution effectiveness can be increased via training, better processes or automation.

Key analysis

  • What is the FCR, FTR, MTTR and MTBF for all open incidents by category, location, assignment group and how have these KPIs changed over time? Are there any outliers that showed remarkable improvement?
  • What does the Incident lifecycle look like? How often does an Incident get re-assigned and what % of the total resolution is for the final step that actually solves the issue?

Workload & Backlog Management

Higher backlogs are a leading indicator of potentially missed SLAs. In order to accurately staff for in-time incident and problem resolution, you need to make sure that your IT fulfillers are not being overworked or that the total workload across incidents, problems and service requests is within reasonable limits and in line with historical observations. A surge in new employees or a new application rollout may need additional fulfillers to handle new service requests and incidents. We will help you utilize your ServiceNow data to manage your backlog and workload

Key analysis

  • What was the average initial response & resolution time for each assignment group as compared to their staffing levels and how has this changed in the last 6 months?
  • What is the current size of the incident backlog and which are the top 10 assignment groups by priority and average age in days of the backlog?
  • Which fulfillers stand out in the number of items in their backlog, the oldest problem in their backlog?

Root Cause Analysis

The best resolution rate is not as good as the best prevention solution. IT Analytics can help identify causal patterns and thus help prevent future incidents, problems and even service requests. Moreover, it can help predict what is about to come to pass by bringing to light the seasonality of service requests or the cause-effect relationships between certain events and higher volume of incidents.

Key analysis

  • What are the top Configuration items by Incidents that breached SLAs in the last week and last month?
  • Show me a list of the top categories or CI classes that account for 75% of my outstanding problems that have aged more than 30 days?
  • How many incidents were caused by changes introduced in cloud based applications that have been recently upgraded by the vendor?

Customer Satisfaction

The end goal of a high performance, modern IT service management team is to make the business side feel that they got the best support ever. Surveys can help measure the customer satisfaction, but there are other ways to measure what customers feel about the service they got, since taking yet another survey may not be on the top of user list.

Key analysis

  • What are the number of incident closed vs number of incidents having user feedback and analyze the data against different dimensions such as – User Group, Resolution Mode, and Location/Region? Is there a seasonality to incidents and problems in any given category that is unique and unusual as compared to all other categories
  • What departments have the highest % of the incidents that are re-opened, escalated or overdue?
  • For which departments is the % of time spent on waiting for user response highest as compared to the total resolution time?