By looking in some detail at just one of these systems we will provide you with tips on the things to consider when you set up the functionality requirements for your automated your Lessons Learned System.
The model we will look at in more detail is Model #1 from the earlier post.
This post is a closer look at the COLLECTION element of the process flow.
COLLECTION
Your people are only human; if you minimise the extra effort required to submit lessons to your Lessons Learned System and maximise the flexibility of using the lessons to solve local operational problems; the use of the Lessons Learned System will be maximised.
The RAID™ human factor rca identify’s this process in the context of forces pressing the person to behave in the desired way (the requirement and assignment) and the potentially opposing forces (inducement and disposition).
The recommendations in this post aim to guide your functionality considerations towards minimising resistance and maximising encouragement for use of your Lessons Learned System.
Integrating the collection of data, for your Lessons Learned System, is more likely to be taken up if it can be set up as a next logical next step in the problem resolution process. Wherever possible, we recommend that the submission of lessons to the Lessons Learned System involve only a small amount of extra work, it should mostly be submitting already prepared problem resolution analysis.
We also recommend you consider building into your Lessons Learned System with scalable data-entry options. The amount of time an individual is required to invest in preparing the problem resolution information, ready to submit to the Lessons Learned System, should be scalable to the complexity and criticality of the problem being resolved. To submit the fix for a printer that has repeatedly jammed should not require the same level of analysis as submitting a lesson from a fatality or major outage.
Having data-entry options with a sliding scale of time commitment, you can ensure that you maximise the data collected. With maximum longitudinal data, regular reviews will identify trends before they escalate to critical events.
In line with the recommended systemic approach to data collection, we recommend that enterprises set up a cause code matrix (to identify the classifications of each Lesson) then give as many people as possible the rights to submit relevant data to your Lessons Learned System.
Your Lessons Learned System will be a silent monitor that records all the little failures and near misses so that you can identify the trend and linkages before it becomes a problem. You won’t need to pay an expensive consultant to come in and find out what has been happening; you will know just as soon as the trend is identifiable and before it is a problem.
For enterprise organisations, dealing with multiple worksites and often in different countries, the collection method for a Lessons Learned System should be able to collect information in a way that allows for recording situations that are unique, there is no point in forcing people to chose an answer from a fixed list of possible solutions – this can perpetuate any existing system flaws and limit the opportunity for true innovation or quantum process improvements.
Significant benefit can be derived through the recording contextual information. The capacity to rapidly modify the application of lessons to the unique contextual environment allows users to quickly bypass recommended actions that were linked to erroneous contextual causal factors; allowing them to hone in on only the corrective action options that specifically relate to their situation and context.
Beyond the conceptual considerations, for the Collection stage of the Lessons Learned System process, there is the practical on-the-job collection and recording of the physical data for problem analysis and problem resolution.
Reducing the need for Investigators to re-enter data when they return to the office is a significant consideration for accuracy and take up of the Lessons Learned System.
We recommend that your Lessons Learned System allows for mobile use (without a direct connection the central server). Synchronisation between a laptop and the central server will allow problem resolution data to be collected on operational lessons in any location.
SUMMARY
1. Minimise the extra work required to submit completed problem analysis to the Lessons Learned System.
2. Scale the analysis and detail to fit the complexity and criticality of the Lesson being submitted to the Lessons Learned System.
3. Within a cause code framework, allow as many people as possible to submit their lessons to the Lessons Learned System.
4. Submit lessons to the Lessons Learned System in a way that allows for innovation and quantum improvements in process.
5. Submit lessons to the Lessons Learned System in a way that allows users to quickly identify and discard erroneous contextual data and customise for their own unique situation.
6. Allow independent workers mobility to analyse and record lessons in a format that is ready for upload to the central Lessons Learned System.
If you would like more information about your Lessons Learned System or designing a Lessons Learned System for your enterprise
visit us at www.systemic-resilient-precision.biz
© Systemic-Resilient-Precision Pty Ltd - 2008
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