Introduction to Data Trending Objectives
In Introduction to Data Trending Objectives, you'll learn ...
- How to take descriptive alphabetic word-based data and convert it to numerical trends
- How to find areas of improvement from your existing software data collection systems like work orders, incident investigations, reliability, maintenance records, near-miss reporting, and more
- To gain justification for your recommendation for improvement and budget monies that no other project engineer will haveThe options and limitations of trending data
Overview
Why do Professional Engineers collect data about their processes in enormous databanks but never utilize it to its full potential? Past performance and conclusions can be used to drive future improvements. This may not be the most opportune place to find improvement, but it is a resource if you know how to unlock its potential.
Oftentimes, much of the data we collect as Professional Engineers is numerical data. Do you know how to manage alphabetical data, convert it to numerical data, and look for statistical trends? This involves looking at what is going wrong, the efforts expended to change outcomes, and offering real improvement backed by your own data. Some people refer to these data trendings as deep dives, some even audits. This technique includes some aspects of each, but neither provides the full picture.
How valuable would it be to trend what is really going on in your work order system? If you were to take your work order requests and do a dump of the descriptions, you could trend them. Many canned software programs allow you to trend costs, time, resources, but not failures or causes. By dumping three months of data into a spreadsheet due to an uptick in chemical leak repairs, you could perform a Deep Dive, capturing the cause, time of construction, materials of construction, replacement, metallurgy, and so on. If it is all PVC, glued fittings, installed over ten years ago, then you have trends.
This course will train you to perform a trending of your software data collection systems for specific types of data that produce results. Examples of these systems are data collected from reliability failures, audits, incident investigations, or recommendations. However, the techniques can be easily utilized to set up proactive trending once you know where you need to improve on any keyword database. Analyzing past data will point to problem areas. This data is used to not only set up proactive trends moving forward but chart out real-time data or if the recommendations written were effective.
Learning Objectives
Upon completion of this course, participants will be able to:
- Convert descriptive alphabetic data in common language into numerical trends
- Select keywords to define a block of data and make it useful
- Describe methods for moving data across company software systems to add meaning to trended data
- Explain deep dive data trending and its purpose
- Analyze descriptive alphabetic data and convert it into numerical statistical data using keywords
- Describe data trending options and limitations
- Apply data trending methods to organize and trend word-report data from reliability, audits, incident investigations, recommendations, and safety sources
- Explain the bonus pretrending technique
- Identify opportunities to improve other processes
Certificate of Completion
You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 15 questions. PDH credits are not awarded until the course is completed and quiz is passed.
| This course is applicable to professional engineers in: | ||
| Alabama (P.E.) | Alaska (P.E.) | Arkansas (P.E.) |
| Delaware (P.E.) | District of Columbia (P.E.) | Florida (P.E. Area of Practice) |
| Georgia (P.E.) | Idaho (P.E.) | Illinois (P.E.) |
| Illinois (S.E.) | Indiana (P.E.) | Iowa (P.E.) |
| Kansas (P.E.) | Kentucky (P.E.) | Louisiana (P.E.) |
| Maine (P.E.) | Maryland (P.E.) | Michigan (P.E.) |
| Minnesota (P.E.) | Mississippi (P.E.) | Missouri (P.E.) |
| Montana (P.E.) | Nebraska (P.E.) | Nevada (P.E.) |
| New Hampshire (P.E.) | New Jersey (P.E.) | New Mexico (P.E.) |
| New York (P.E.) | North Carolina (P.E.) | North Dakota (P.E.) |
| Ohio (P.E. Self-Paced) | Oklahoma (P.E.) | Oregon (P.E.) |
| Pennsylvania (P.E.) | South Carolina (P.E.) | South Dakota (P.E.) |
| Tennessee (P.E.) | Texas (P.E.) | Utah (P.E.) |
| Vermont (P.E.) | Virginia (P.E.) | West Virginia (P.E.) |
| Wisconsin (P.E.) | Wyoming (P.E.) | |

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