Auditing and cleaning inconsistent file naming involves reviewing file systems to identify naming variations, then standardizing them based on predefined rules. Inconsistent names stem from multiple contributors using different formats (e.g., mixed case, date styles, abbreviations), leading to confusion and search inefficiencies. The cleaning process systematically renames files to a consistent structure, improving organization and retrieval. This differs from basic sorting by addressing the root cause of disorganization rather than just grouping existing files.

In practice, this might involve scanning a marketing department's asset folders to find images named "campaign_summer23.jpg", "CampaignSummerFinal.png", and "summer_campaign_v3.jpg". Using script-based tools (Python, PowerShell) or specialized software (like Bulk Rename Utility or dedicated DAM systems), these could be standardized to "Campaign_Summer_2023_v[number].[ext]". Software development teams similarly enforce naming conventions (e.g., "module_function.js") across codebases using linters or project templates.

The key advantage is dramatically improved searchability and workflow efficiency. However, the process can be time-intensive for massive systems and risks file misidentification if metadata isn't preserved. Careful planning, comprehensive backups before renaming, and clear documentation of the new standard are essential. Future maintenance involves integrating naming rules into onboarding and automated checks, often aided by metadata tagging alongside filenames for richer context.