6 Common Data-related ITSM Implementation Mistakes
No company ever has a “perfect” ITSM implementation. Eventually, a company realizes that mistakes were made and learns lessons from its experience. Because ITSM processes are highly dependent on complete, accurate, current and integrated data being available to support both operations and decision making, this is an area where many lessons are learned. Here are 6 common ITSM implementation mistakes relating to data to help your implementation be more efficient and error-free.
ITSM Implementation Mistakes:
Underestimating administrative overhead
An ITSM system is only as valuable as the data it contains. It requires a large amount of “care and feeding” to maintain its prime condition to support the operational activities of your organization. From user and group management to CMDB data quality to keeping knowledge repositories current, there are many administration tasks which must be performed regularly to ensure that users have quick and effective access to the data they need to support your IT systems and services. When companies implement ITSM solutions, they spend considerable time loading data into their system and discussing how it will be used; however, planning for administrative activities often don’t occur until later when problems start. As part of your implementation checklist, you should be developing a maintenance and administration plan – ensuring clear accountability for all of the critical data within your system to avoid ITSM implementation mistakes.
Loading garbage data into the system
Most companies do not have the luxury of a “clean-slate” ITSM system implementation – they have various existing tools and data that are migrated into the new system. When implementation activities aren’t completed according to the schedule, one of the most common ways that companies “recover” to hit their deadlines is to forego data-cleaning activities. They migrate poor quality data into the new system – claiming that they can clean it after go-live. The problem with this approach is that data within an ITSM system has many complex dependencies and relationships. When the garbage data is imported, it doesn’t stay contained – it creates a web of related records that can compromise the quality of data in other parts of the system as well. Cleaning the mess after it has been made is far more costly and cumbersome than scrubbing the data before import.
Not having a data archive/purge strategy
ITSM data is a digital reflection of your company’s IT environment as a whole – it is continuously changing. As the environment changes, the data in your ITSM system (CIs, User Records, Knowledge, Problems, etc.) becomes outdated and obsolete. As this happens, you need a process and set of rules to purge old data systematically, archiving those items that have future analytical value, but keeping the operational system clean and current. Most companies wait until they encounter performance problems before implementing a data archive/purge strategy on their ITSM system, but with some advance planning, performance impacts are easily avoided.
Making customizations that prevent clean upgrades
Software vendors are continuously making changes and releasing patches and version upgrades to improve their offerings, add new features, resolve bugs and address security issues. The expectation is that your company will implement these patches and keep your system current. Decisions to deviate from the out-of-box offering through either configuration or customization makes the patching and upgrade process more difficult. Impacts may range from regression testing to re-work of custom code, depending on what changes your company has made. To avoid ITSM implementation mistakes, the best approach is to avoid customization, making the (frequent) update process as clean and simple as possible.
Not planning for change
The modern business environment changes quickly and, when it does, your ITSM system (as a key enabler of your business) must have the capability to change quickly with it. During ITSM implementation projects, companies spend considerable time discussing how to configure the system to match the current structure of the organization accurately, but rarely devote enough attention to how the system will support scenarios, such as re-organizations, growth and mergers. Ironically, if the ITSM system is optimized to change, then it doesn’t matter if the current implementation is correct, because it can be easily fixed. Because the system, however, is implemented-based on a static-state organization, supporting change is difficult.
Failing to automate processes
One of the key benefits of implementing an ITSM system is gaining process efficiency in managing data. The workflow-enablement capabilities of the service management platform combined with industry standard processes (from ITIL, for example) provide an opportunity for your company to unwind some of the cumbersome manual processes that have developed organically as your company has grown, allowing you to begin to manage your operational data more efficiently. Failing to take advantage of process-automation capabilities causes companies to dilute the value of their ITSM investments by perpetuating the manual processes, and then duplicating them in the system. When this happens, the implementation is slowed and the ITSM platform is blamed for inefficiencies that were always present. By leveraging the new automation capabilities, this can be avoided.
By learning lessons from those who have made the same ITSM implementation mistakes, you are more likely to avoid repeating them in your company’s ITSM implementation. The better the quality of the data you can create and maintain in your ITSM system, the more effective your IT staff will be supporting your company’s IT systems and services – and you leaders will be able to make better quality decisions.