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ITSM ticketing requests often have deceptively simple solutions. Yet, ticketing volumes continue to rise and overwhelm the limited front-line ITSM workforce that serves a crucial role in IT service delivery.
While the problem is well-recognized by ITSM service agents and help desk staff, management and executives responsible for key ITSM decisions do not necessarily share the same perception of the ground realities.
Popular theory in the domain of organizational management and operations posits the lack of communication between front-line employees, management and business executives as responsible for this gap. The disconnect is not limited to discussions between employees at various hierarchical levels of the organizations, but also intelligence from the data available to them.
While a broad scope of intelligence is available to engineers immediately in charge of analyzing data, only the select metrics KPIs are communicated to leadership and business executives and the front-line support staff, and almost none is communicated to front-line staff responsible for engaging with end-users.
According to a study by Sidney Yoshida, “Only 4 percent of an organization’s front line problems are known by top management, 9 percent are known by middle management, 74 percent by supervisors and 100 percent by employees ”. The study further showed that this gap suppressed an organization’s profits by up to 40%.
This concept is referred to as the Iceberg of Ignorance, and is even more relevant in the digital era, and especially as it pertains to digital and technology-driven services.
The IT Service Desk allows end-users to log complaints and service requests, and a support agent (or chatbot) helps route the request ticket to the resolution team. In practice, ticket resolution and its associated process is not always intended to resolve the underlying root cause, provide a long-term solution, identify business challenges and opportunities masked by the communication between the IT Service Desk front-line employees and end-users.
Let’s recap the current state of traditional ITSM. When a support ticket is created, support agents try to collect information from end-users to guide the request to the right resolution team. From this interaction, only the most relevant knowledge is provided to the resolution team for fast and timely resolution. Once the ticket is resolved, some insights may be manually collected to help improve the resolution process. This approach fails to scale, even when the manual process is replaced by automation without adequate intelligence and optimization into the ticket routing and ITSM planning process.
Here are a few key elements responsible for the Iceberg of Ignorance in the ITSM organization:
ITSM organizations may not collect detailed information on the journey of a ticket request, especially considering the large ticketing volume. Visibility into the resolution process and understanding of the major bottlenecks is not provided by popular KPIs, but requires additional measures to monitor how each ticket request hops between IT teams and queues before finally meeting the correct resolution personnel.
The hierarchical structure of the ITSM organization governs the communication across the different hierarchical levels. Executives make decisions based on KPIs and metrics, but the decision parameters are not always the most insightful choice in identifying real business challenges and opportunities. An accurate understanding of the real technical challenges facing end-users is readily available among front line employees, but requires additional communication channels beyond KPIs and metrics logs received by executives.
When ITSM teams operate in isolation, the knowledge and insights they gain in resolving specific IT issues is contained in silos. Inadequate knowledge management and a lack of centralized information repository for disparate teams. This means that even the solutions to the same issues must be discovered and applied from scratch, due to inadequate knowledge transfer between teams.
Timely decision making requires IT leaders and engineers to access the right intelligence at the right time. In the case of the IT Service Desk, real-time view of user feedback on IT performance and potential issues means that corrective actions can be taken proactively. The delay in receiving data, performing a thorough analysis and manually extracting useful intelligence renders any insights as less impactful, than the intelligence received in real-time.
The disconnect between teams across departments and hierarchical levels of the organization means that insights on ITSM process optimization are not communicated between them. Employees continue to follow routine procedures, without knowledge that they are contributing to the waste process or that there may be better ways to operate. Additionally, there may as well be gaps in the implementation of an ITSM best-practice guideline coming from decision makers. Due to the communication gaps, the so-called Iceberg of Ignorance grows in both directions.
The idea behind the theory mainly centers around the communication gap. How can ITSM organizations eliminate the divide between front line support agents and key decision makers?
Before resolving the issue, business organizations must understand that the modern ITSM process is mostly data-driven. The problem is not limited to solving the communication gap between personnel across the organizational hierarchy. Instead, they need to extract insights from raw information including but not limited to the interactions between front line employees and end users that request tickets.
ITSM technologies that offer hyperautomation intelligence capabilities can offer a key role in resolving the challenge end-to-end.
For instance, the traditional IT Service desk does not account for ticket queue management. A ticket waits an average of 80% before someone will deal with it as it’s stuck in a queue. Unlocking the iceberg of ignorance will shine the light about the waiting time in the queue, the bottlenecks and where exactly we can dramatically improve the MTTR by removing those bottlenecks.
Additionally, queue handling is not about resolving tickets faster on a first-come-first-serve basis. Additional intelligence is required to understand how tickets from within the queue should be prioritized based on metrics such as business value, user satisfaction, scope and intensity of the associated incident, and of course, the volume of the queue itself.
A connected ITSM platform can help monitor the ticket resolution process throughout its journey. Monitoring how every ticket hops between resolution teams and queues can provide valuable information on the ITSM (waste) processes. Natural Language Processing (NLP) capabilities can analyze interactions with end-users at scale, make sense of a vast pool of historical ticketing archives and create an up-to-date and well-informed knowledge base.
This reduces the burden on front line employees and engineers to manually document issue resolution.
Furthermore, gathering insights at scale allows engineers to connect the dots between user requests and proactively find technology issues before they impact end-users. From a business perspective, this means lower downtime and improving service dependability, all of which yield tangible returns on investments.
