From SLA Reporting to Proactive IT Operations

In one line: ServiceNow history became SQL datasets and Power BI views so operations could discuss patterns — not only SLA compliance slides.

Context

In 2018, I worked with IT operations data that was primarily used for retrospective SLA reporting. I wanted to make the same ServiceNow history useful for improvement work: finding recurring incidents, shifts in resolution time, and areas where teams could intervene earlier.

My Contribution

I shaped the analytical approach, prepared SQL-based datasets, and built the Power BI dashboard shown above. The work connected incident history, service levels, and operational patterns in one interface for managers and delivery teams.

Scope

1. Data Collection and Analysis:
   • Gather relevant data from various sources, including incident logs, performance metrics, and historical records.
   • Analyze this data to identify patterns, trends, and anomalies related to SLAs, service quality, and operational efficiency.
2. Trend Identification:
   • Focus on key performance indicators (KPIs) such as response time, resolution time, and uptime.
3. Proactive Suggestions:
   • Generate proactive recommendations based on identified trends.
   • For example, if a recurring issue is detected during specific hours, suggest adjustments to resource allocation or preventive maintenance during those times.
4. Dashboard and Reporting:
   • Create an interactive dashboard that visualizes SLA performance, trends, and improvement opportunities.
   • Provide real-time insights to stakeholders, including IT managers, support teams, and decision-makers.
5. Operational Review:
   • Share evidence and improvement hypotheses with the people responsible for service delivery.
6. Continuous Improvement:
   • Implement a feedback loop to monitor the impact of suggested improvements.

Technology Stack

• BI Tool: Power BI
• Database: SQL
• ITSM Tool: ServiceNow

Effect

The result was a move from a static SLA view toward an exploratory operations dashboard. I do not have verified long-term impact figures for this historical project — only the delivered analytical capability.

Where AI fits now

The same ServiceNow and ITSM patterns feed proactive data agents and anomaly alerting today; the prerequisite is still traceable SQL datasets and clear ownership — the data platform step later formalised that discipline.