The Three Stages of Developing IT Service Management
Working with service management processes and technologies in different organisations, we have seen that the weight of supporting legacy systems and processes inhibits investment in the innovation organisations most need to succeed. And sadly, oftentimes, siloed services and operations teams can’t keep up with the technology demands of today’s digital-first world.
In this article, we explore the most typical problems organisations struggle with in each development stage and how AI can help automate and optimise services and operations to deliver better digital business services.
Pekka Lehti
Pekka has over 20 years of experience in IT consulting and creating value for customers. He is a strong believer in continuous improvement, which drives him to learn and look for new ways to develop business operations in customer organisations.
Stage 1: How to expand services cost-effectively?
The most typical problems organisations struggle with at this stage:
Technology services are siloed and scale poorly.
IT services do not cater to business needs effectively.
To tackle this, you may have already implemented a service platform to improve the services your technology services and operations teams deliver. Common solutions are ServiceNow, Jira, Salesforce, and Freshdesk.
While the platform is in use, you struggle with automation and generating business value from the chosen technology. The solution? Creating and developing the most central processes that keep the business running. Often, a fruitful starting point is automating core service and operations processes, such as incidents, changes, and common requests.
Stage 2: How to deliver better experiences with AI?
The most typical problems organisations struggle with at this stage:
Developing employee and customer experiences.
Improving service consistency and productivity.
Here are some examples of use cases for AI-powered automation that increase the speed and quality of service operations:
AI-powered customer service
Problem: Your customer support organisation receives thousands of poorly detailed customer enquiries or issues daily.
Solution: AI analyses category and urgency of inbound messages, forwarding them to the right handling unit and suggesting resolutions based on similar issues solved earlier.
Result: Better customer service in terms of faster resolution and increased internal employee happiness with less message ping-pong.
IT service-level agreement (SLA) monitoring with the help of AI
Problem: Your IT departments might miss their SLAs due to a lack of resources or work spikes.
Solution: AI monitors customer issues or service-level trends that potentially breach SLA, alerting or proactively resourcing help based on breach severity.
Result: Improved reliability and trust in IT services, mitigating organisational risk.
Customer sentiment analysis with AI
Problem: Your organisation struggles to gauge customer satisfaction effectively or in a holistic manner.
Solution: AI analyses recent customer surveys, emails, chats, forum posts and incident reports to predict customer sentiment (e.g., positive, neutral, or negative), prioritising attention/support for prolonged resolution processes and/or dissatisfied users.
Result: Customers feel heard and receive timely responses, improving satisfaction and loyalty.
Stage 3: How to accelerate productivity and innovation?
The most typical problems organisations struggle with at this stage:
Improving productivity across the organisation.
Managing change without disruption.
During your AI-powered automation journey, remember to ensure continuous improvement and robust governance of your service operations. Use business optimisation tools and industry best practices to optimise vendors, digital portfolios, cloud infrastructure, your IT workforce, and your processes.
Here are a few ideas on how to develop operations even further at this stage:
Drive process management best practices across the organisation to reduce risk and increase efficiency.
Optimise your workforce and workflows to boost productivity and increase customer satisfaction.
Support development teams with self-service access to needed resources to improve the visibility of applications and assets.
Provide service owners with one place to manage their IT service portfolio, so they can make informed, strategic investment decisions.
Reaching Peak Performance with AI-Powered Service Management
Developing IT service management is not a linear journey. Organisations may encounter challenges and setbacks along the way. However, by embracing a continuous improvement mindset and leveraging the power of AI, organisations can break down silos, enhance customer experiences, and ultimately achieve peak performance in their service delivery.