In complex information flows where a lot of varied data is transmitted through many companies and divisions, incidents will occur. When Visma Spcs had an incident where invoices sent from Visma to Visma's customers were duplicated and the service meant to receive the transactions did not handle the duplicates properly. They decided that the receiver service was to be upgraded to prevent this incident from happening again, as well as fixing some other issues the service had had. Incidents like this one must be investigated and a solution must be implemented to decrease the likelihood that similar incidents will happen again. In this report, the reader will see examples on how this can be handled and the benefits of tackling technical debt, along with how much more complicated the solutions might get if the service is not allowed to be taken offline.

När problem med materielsystem upptäcks efter att de har levererats till Försvarsmakten så är detden vidmakthållande organisationen som tar hand om det. Den arbetar för att det aktuella problemetåtgärdas och även förebygger liknande problem. Många instanser runt om i Försvarsmakten är inblandadei arbetet; ibland kan samordning och kommunikation vara ett problem för verksamheten. Uppsatsen undersöker hur ett datorbaserat samarbetssystem kan bidra till att förbättra den vidmakthållandeprocessen inom Försvarsmakten. Undersökningen visar att ett datorbaserat samarbetssystem kan underlätta arbetet för en idag redanfungerande vidmakthållandeorganisation. / When problems with materiel are found after being delivered to the Swedish Armed Forces it is the maintaining organization that handles it. It sees to that the current problem is fixed and that similar problems are prevented. Many competent bodies in the Swedish Armed Forces are in-volved in the work, and therefore co-ordination and communication can be a problem for the activities. This thesis will investigate how a computer based co-operation system can simplify the maintain-ing process in the Swedish Armed Forces. The study shows that a computer based co-operation system can contribute to the process in a today functional maintaining organization.

Background: Maintaining system reliability and customer satisfaction in a DevOps environment requires effective incident management. In the modern day, due to increasing system complexity, several incidents occur daily. Incident prioritization and resolution are essential to manage these incidents and lessen their impact on business continuity. Prioritization of incidents, estimation of recovery time objective (RTO), and resolution times are traditionally subjective processes that rely more on the DevOps team’s competence. However, as the volume of incidents rises, it becomes increasingly challenging to handle them effectively.  Objectives: This thesis aims to develop an approach that prioritizes incidents and estimates the corresponding resolution times and RTO values leveraging machine learning. The objective is to provide an effective solution to streamline DevOps activities. To verify the performance of our solution, an evaluation is later carried out by the users in a large organization (Ericsson).  Methods: The methodology used for this thesis is design science methodology. It starts with the problem identification phase, where a rapid literature review is done to lay the groundwork for the development of the solution. Cross-Industry Standard Process for Data Mining (CRISP-DM) is carried out later in the development phase. In the evaluation phase, a static validation is carried out in a DevOps environment to collect user feedback on the tool’s usability and feasibility.  Results:  According to the results, the tool helps the DevOps team prioritize incidents and determine the resolution time and RTO. Based on the team’s feedback, 84% of participants agree that the tool is helpful, and 76% agree that the tool is easy to use and understand. The tool’s performance evaluation of the three metrics chosen for estimating the priority was accuracy 93%, Recall 78%, F1 score 87% on average for all four priority levels, and the BERT accuracy for estimating the resolution time range was 88%. Hence, we can expect the tool to help speed up the incident response’s efficiency and decrease the resolution time.  Conclusions: The tool’s validation and implementation indicate that it has the potential to increase the reliability of the system and the effectiveness of incident management in a DevOps setting. Prioritizing incidents and predicting resolution time ranges based on impact and urgency can enable the DevOps team to make well-informed decisions. Some of the future progression for the tool can be to investigate how to integrate it with other third-party DevOps tools and explore areas to provide guidelines to handle sensitive incident data. Another work could be to analyze the tool in a live project and obtain feedback.

Forskning visar att traditionella rotorsaksanalyser har begränsningar när det gäller att utreda händelser i komplexa system. För de komplexa system som utgör dagens moderna arbetsliv krävs att analyser sker på en övergripande systemnivå, organisationsnivå, där till exempel tekniska, organisatoriska och sociala faktorer som påverkar arbetssystemet beaktas. I takt med att rapporteringen av händelser och tillbud ökar blir mängden rapporter att hantera allt större, det krävs tekniska system och hjälpmedel för att bearbeta data. Är Informationssystem om Arbetsmiljö (IA) ett ärendehanteringssystem för att hantera enstaka ärenden eller går det att upptäcka trender och använda systemet förebyggande på en övergripande organisationsnivå i det systematiska arbetsmiljöarbetet? Syftet med studien var att visa om användningen av ett incidentrapporteringssystem ger ett företag möjlighet att analysera arbetsmiljöbrister ur ett systemperspektiv och på så sätt öka kunskapen om risker inom företaget. En kvalitativ fallstudie utfördes, på ett verkstadsföretag, med en abduktiv ansats med växling mellan empiri och teoretisk reflektion. Studien bygger på såväl data från IA-systemet som underlag från intervjuer av händelseansvariga på det studerade företaget samt en litteraturstudie. Analysen visar att IA-systemet stödjer analys ur ett Människa-Teknik-Organisation-perspektiv (MTO-perspektiv) men saknar en strikt taxonomi kopplad till förståelsen av bakomliggande orsaker till händelser. Det saknas stöd för att på ett tillförlitligt sätt analysera händelser på en övergripande system- eller organisationsnivå. Inkonsekvent kategorisering av incidentrapporter försvårar effektivt utnyttjande av incidentrapporteringssystem och utvärdering av analyser påverkas negativt. Ett alternativ skulle kunna vara att utöka IA-systemet med en textanalysdel som kan hantera fritext i databasen och söka efter nyckelord. Genom att kombinera fritextanalys med taxonomi kan trender påvisas ur en stor mängd data. / Research reveals traditional root cause analysis to have limitations when used to analyse incidents in complex systems. For complex systems like modern work life environment analysis is required to be carried out on overall system level, organisational level, where technical, organizational and social factors impacting the system of work are considered. As reporting of incidents and near misses are increasing, the corresponding number of reports to be handled are larger, which requires the assistance of technical systems in order to handle all data. Is Occupational Health and Safety Information System (IA-system) an incident reporting system just for single incidents or will it facilitate detection of trends to use the system for preventive actions on a higher organizational level to support systematic work environment management? The purpose of the study was to show whether the use of an incident reportingsystem gives a company the opportunity to analyse work environment deficiencies from a system perspective and thus increase knowledge about risks within the company. A qualitative case study was carried out, at a manufacturing company, with an abductive approach supported by switching between empirical and theoretical reflection. The study is based on data from the IA-system and interviews from people responsible for handling issues at the studied company as well as a literature study. The analysis shows that the IA-system supports analysis from a Human-Technology-Organization (HTO) perspective, but lacks a strict taxonomy linked to the understanding of underlying causes of incidents. There is no support to reliably analyses of incident at an overall system or organization level. Inconsistent categorization of incident reports makes effective use of incident reporting systems difficult and evaluation of analyses is adversely affected. A solution could be to expand the IA-system with a text analysis part that can handle free text in the database and search for keywords. By combining free text analysis with taxonomy, trends can be demonstrated from a large amount of data.