Skip to main content

historical

From SLA Reporting to Proactive IT Operations

Data-driven IT operations dashboard showing analytics and proactive service management metrics built by agentic engineer Emil Ingemar Karlsson

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

Outcome

The result was a move from a static SLA view toward an exploratory operations dashboard. It made recurring patterns and improvement opportunities easier to discuss with the responsible teams. I do not have verified long-term impact figures for this historical project, so I present the delivered analytical capability rather than claiming savings or incident reductions.

When: 2018

Want to compare notes?

I am always interested in thoughtful conversations about the decisions, trade-offs, and systems behind this work.

Get in touch

Continue through the journey

Earlier and later work.

Data-Informed B2B Platform Strategy Across 35 Markets

historical
Combined product analytics, survey evidence, and direct customer research to guide investment decisions for an enterprise B2B platform used across 35 markets.

Food-Waste Marketplace MVP with Django

historical
An early full-stack marketplace connecting consumers with surplus food from local restaurants and grocery stores, built as a focused Django and Bootstrap MVP.

Related content