{"id":6555,"date":"2019-03-13T14:38:45","date_gmt":"2019-03-13T14:38:45","guid":{"rendered":"http:\/\/www.aroraengineers.com\/?p=6555"},"modified":"2019-04-24T17:54:06","modified_gmt":"2019-04-24T17:54:06","slug":"your-cmms-data-is-in-bad-shape","status":"publish","type":"post","link":"https:\/\/www.aroraengineers.com\/your-cmms-data-is-in-bad-shape\/","title":{"rendered":"Your CMMS Data is in Bad Shape – But Everyone Already Knows This"},"content":{"rendered":"

By: John Reeve<\/a><\/p>\n

The Outdated Org Chart Structure is the Main Problem<\/h2>\n

If the current organizational structure continues, there will be\u00a0little to no improvement in CMMS data accuracy in the foreseeable future<\/strong>.\u00a0Stakeholders frequently complain about poor data but fail to take corrective action. Or, they simply load up the Planners with more data-check activities since they are the supposed CMMS gurus. So, even with the vast improvement in CMMS technology and feature-rich products, here we are 30 years later with horrible data. It seems no one wants to be held accountable.<\/p>\n

Everyone Misses the Clerical Staff<\/h2>\n

In the 1980\u2019s clerical staff performed much of the CMMS data entry and work order filing. Not that clerical captured everything we needed, but at least it was a position we could mold on-the-fly to accommodate needs. These positions were mostly eliminated however in subsequent years shifting the\u00a0burden for accuracy<\/strong>\u00a0to the working level, planners,\u00a0<\/strong>and sometimes CMMS administrator.\u00a0The working level never really accepted this\u00a0accuracy role<\/strong>\u00a0\u2013 or understood it.\u00a0In summary, there has been no attempt to improve the capture of failure data in support of\u00a0failure analysis<\/strong>.<\/p>\n

What Information Do We Need from the CMMS?<\/h2>\n

From a reliability standpoint, it would be great to\u00a0know the worst performers<\/strong>. And with that in hand, decisions can be made to eliminate the cause of failure. Better reliability means better availability, which in turn,\u00a0optimizes O&M costs<\/strong>. The 10-step flow chart shows how failure data can be captured, analyzed and acted upon. But, key roles (that are missing) are needed to do this.<\/p>\n

Key Roles (that are missing)<\/h2>\n

Key roles<\/u>\u00a0essential to knowledge management are shown in the post main picture. In addition,\u00a0here<\/a>\u00a0is what a\u00a0High Reliability Organization\u00a0<\/strong>should look like.\u00a0<\/strong>This modern-day organization cares about data and extracting competitive information. As to the new roles, they could be new duties — or new positions. With the emphasis on machine learning, data is all the more important. To put it bluntly, leadership needs to (1) address weak points in data capture, (2) configure software and process to improve data quality, and (3) implement data reviewers such as a Data Analyst<\/strong> to extract knowledge. Failure analysis should be the cornerstone of the CMMS<\/strong>.<\/p>\n

Note: This position or positions could go by many names: Gatekeeper, Reliability Engineer, Business Analyst, Asset Manager, or even\u00a0Data Scientist.<\/strong><\/p>\n

Failure Data Originates at the Working Level<\/h2>\n

Capturing any type of work order feedback is difficult. Examples include work order status, actual labor hours, parts issued, outside service costs, job status, actions performed, and\u00a0failure coding<\/u>. Here is a list of ways to help the working level:<\/p>\n

    \n
  1. Provide\u00a0mobile solution<\/strong>\u00a0with all of the necessary inputs for work order completion.<\/li>\n
  2. Conduct training<\/strong>\u00a0(CMMS navigation and precision maintenance training)<\/li>\n
  3. Listen to their needs<\/strong>; conduct surveys; find out what information they need to do a better job.<\/li>\n
  4. Ensure the\u00a0planning-scheduling process<\/strong>\u00a0is working smoothly.<\/li>\n
  5. Inquire about\u00a0missing foundation data<\/strong>, such as assets. Ask about difficulty searching for parts.<\/li>\n
  6. Ask about\u00a0failure coding<\/strong>. Is the data capture process clear? An example would be:\u00a0Failed component<\/u>\u00a0should be entered by Technician. The\u00a0component problem<\/u>\u00a0could be entered by Technician but possibly by Supervisor. The\u00a0cause code<\/u>\u00a0could be entered by Technician, Supervisor, or Reliability Engineer. Capturing the failure mode on the work order is best practice.<\/li>\n<\/ol>\n

    Where Has Leadership Failed?<\/h2>\n