A previous ITSM.tools article (from 2017) explained why and how the level zero solvable (LZS) technique can help with IT self-service success. It painted a picture of a common IT self-service mistake: organizations launch IT self-help capabilities with an inadequate knowledge base and knowledge management capabilities.
For example, a knowledge base might be spilling over with knowledge articles. However, if critical articles are missing or can’t be found or understood by end-users, there might as well not be one in the context of IT self-service success.
In my opinion, LZS is still an unknown knowledge management technique for many IT service desks, especially outside of North America (where I originally read about it in an HDI post). Plus, while the initial use was IT self-service, I believe the basis of the technique can also be used in assessing the suitability of knowledge articles and their use by IT support staff. In particular in the context of bounced tickets.
What follows is a reimagining of the 2017 article that’s eventually tailored for the bounced ticket opportunity.
Leve zero solvable explained
LZS measures the percentage of incidents that end-users could have resolved via self-service to understand whether a knowledge base is sufficient to support the launch of an IT service portal. There are two options for calculating the LZS metric in this scenario.
The first requires IT service desk staff to search the proposed self-service knowledge base while dealing with end-user issues, as though they’re trying to solve the incident via the service portal. If a knowledge article exists, the incident record can be flagged as “LZS.”
The LZS metric is the number of flagged incident records as a percentage of the total incident records handled that month. For example, an IT service desk would have a 50% LZS score if five of every ten issues dealt with could have been solved using self-service.
Alternatively, the LZS metric can be calculated on a sample basis, with project staff retrospectively matching incident records to available knowledge articles. Either way, the higher the LZS metric, the higher the probability that end-users will use IT self-service successfully and continue to use it.
Two key points when using LZS for IT self-service
First, just because there’s an available knowledge article doesn’t mean an incident record can be flagged as LZS. For example, a knowledge article might be unsuitable for end-user needs. Therefore, an honest decision needs to be made as to whether a knowledge article could be successfully used by someone without related technical knowledge.
Second, after the service portal launch, the LZS score will decrease because self-service adoption rises, and most LZS issues will hopefully be resolved through self-help. Instead of maximizing the LZS score, the aim is now to minimize it.
Applying LZS to IT service desk knowledge management and bounced tickets
There are various root causes for bounced tickets, where the allocated service desk agent can’t help, including ticket categorization and routing issues. For example, a lack of clarity and interpretation issues.
An alternative root cause is knowledge management issues such as:
- The knowledge base is missing relevant content
- Search failures, where content doesn’t readily present itself (via a manual or automated knowledge search)
- A service desk agent doesn’t regularly access the knowledge base when tackling tickets (for various reasons).
Whatever the root cause of the knowledge-management-related issues, the same LZS approach used for service portal introduction can be applied. This time, project staff retrospectively assess the efficacy of the IT service desk knowledge base in the context of bounced tickets.
Of course, some bounced tickets will be outside a service desk agent’s ability to resolve them using a knowledge article. For example, where it’s a significant categorization mistake. However, there will be instances where the initially bounced ticket could have been solved if a suitable knowledge article had been available, retrievable, and understandable.
It’s not really “level zero solvable” because it’s not an end-user self-helping. However, the same approach can be used to improve the quality of the IT service desk knowledge base and reduce the number of bounced tickets.
This was a quickly written article, but hopefully it makes sense. Let me know if it doesn’t, and I’ll try a rewrite.
Further Reading
Please use the website search capability to find more helpful ITSM articles on topics such as knowledge base software, knowledge base articles, search functionality, real-time support team performance measurement, how to create a knowledge base, refining frequently asked questions, improving business operations, improving IT support search engines, knowledge management strategy development, and knowledge base content.
There are also helpful ITSM articles on knowledge management platforms, tacit knowledge capture, product or service delivery, IT service management (ITSM) processes, knowledge management tools, improving customer satisfaction, how to manage software assets, developing team members, how automation saves time, knowledge base solutions, collective knowledge, content creation, continual or continuous improvement, making knowledge sharing less time-consuming, cloud-based ITSM tools, and knowledge management solutions.
Stephen Mann
Principal Analyst and Content Director at the ITSM-focused industry analyst firm ITSM.tools. Also an independent IT and IT service management marketing content creator, and a frequent blogger, writer, and presenter on the challenges and opportunities for IT service management professionals.
Previously held positions in IT research and analysis (at IT industry analyst firms Ovum and Forrester and the UK Post Office), IT service management consultancy, enterprise IT service desk and IT service management, IT asset management, innovation and creativity facilitation, project management, finance consultancy, internal audit, and product marketing for a SaaS IT service management technology vendor.
