Saturday, July 25, 2015

Structured Data in a Complicated Domain

Introduction

This week’s MSLD632 blog is about something that has become one of my favorite topics, the Cynefin Framework for making decisions. Most of the decisions made within my span of control at work are either simple or complicated and knowing which context (or framework) is the best fit has been critical in good decision making. This blog will provide 2 recent examples of how decision making outcomes could have had a better outcome had the Cynefin Framework been utilized in the decision making process as referenced in Snowden & Boone, (2007).

Interactive Fault Isolation Tool Decision – Decision to Stop

My job for the past nine years has been in-charge of writing fault isolation procedures for advanced aircraft in development at the aircraft system level and is largely a deterministic world, one where science and physics rule “The Simple and Complicated share the common scientific assumption that lends much to conventional science and wisdom.” (Obolensky, 2014, p. 54). Until recently these procedures have been produced as in paper manuals. In spring of 2012 someone called me and informed me the static procedures that my team had just completed for our latest and greatest aircraft had been imported into an interactive fault isolation tool and that our customers would soon have access to the procedures. My response “Oh really, that’s great…would you mind if I took a look?” To make a long story short, it only took a few moments to recognize that the import went very badly. Every procedure I opened up was completely out of order when I began answer the interactive questions. Something had gone horribly wrong. The explanation we received from the 3rd party vendor who supplies the interactive fault isolation tool was that the ‘reasoning engine’ was not behaving in a predictable manner.
When this catastrophe occurred (in the context of fault isolation data organization) the Cynefin Framework was not known to me. Reflecting back on this event and using the Cynefin Framework to find what action I should have taken, I find that I took the correct action. Because the fault isolation procedures were in a state of chaos (unorganized mess), the right action was to make a command decision and stop these procedures from going to our customers until we could discover why the order of the steps were not being displayed correctly. Snowden & Boone state this about chaotic states “Take immediate action to reestablish order (command and control)” (p. 73). The immediate action we took was to lock out the reasoning engine by implementing predecessors for each step. In other words, we created rules such that for Step 2 you had to do Step 1 first. In order to get to Step 3 you had to do Step 2 first, etc.

Interactive Fault Isolation Tool Decision – Decision to Use XML and S1000D

In the above decision making example, we used a mark-up language referred to as SGML (Standardized General Mark-up Language). On the most recent project we decided to use XML (X-tensible Mark-up Language) and a global technical writing standard called S1000D and import into the same interactive fault isolation tool using a different import tool.
The decision not to author directly using the interactive fault isolation tool authoring mechanisms was made without having enough or the right experts involved. S1000D is an emerging specification, it’s been around for more than a decade but hasn’t been on solid footing here in the USA in the aviation industry until just recently. Because not enough analyzation was done and the right experts in the decision making process were not involved, it has taken us the better part of 24 months to experiment what style and format allowed within the S1000D specification would work best with the import tool so that our steps would appear in the correct order (same problem as in the first example). Once again we fell victim to not understanding what it would take to make a good decision.
In this example there are two critical points where the Cyenfin Framework could have helped. We could have made a decision to not write using XML and the S1000D specification and used the Spotlight tools to author the fault isolation procedures directly without having to import them, and instead used the import tool to export the procedures from the interactive state into S1000D. The reason behind taking this approach this requires a lengthy explanation not really appropriate for this forum, so you will just have to trust me when comparing the two processes as fitting the data into the framework (importing the XML S1000D into the interactive fault isolation tool) versus designing the framework around the data (exporting the interactive fault isolation tool into the XML S1000D format). So that sums up what critical point number one is about.
Critical point number two is more about analyzing the problem better before jumping into picking a solution. The problem was designing an authoring method that would import properly so the steps of the procedure would show up in the right order (sound familiar?) using XML and our S1000D framework. We thought we had a solution and spent about 12 months developing the procedures using XML and S1000D before the import tool was ready to use. When the import tool was ready, the results were the same as before. What our 3rd party vendor calls the reasoning engine was reordering the steps once again. Not wanting to install predecessors again, I buckled down to find a solution. My intuition told me there had to be one. We went thru several iterations of authoring intricacies before we finally hit the right pattern.
My initial observation about analyzing this problem better before picking a solution comes from Snowden & Boone (2007) in from the Complicated context “Sense, analyze, respond” and needing “Expert diagnosis”. At the time the decision was made, we did not have as much direct contact with the experts as we did when we found a solution and we were perhaps to confident in our original diagnosis. Snowden & Boone (2007) caution against being overly confident in the complicated domain and label this as a “Danger Signal” (p. 73).

Summary

If you are willing to review the Cynefin Framework before making decisions you will reduce the amount of poor or less than optimal decisions you make. I have shared with you two personal examples of how the Cynefin Framework can help with decision making. There is an excellent short video by Snowden The Cynefin Framework that summarizes its. Hopefully reading my blog has had a positive effect on your way of making decisions.

References:
Obolensky, N. (2014). Complex adaptive leadership: Embracing paradox and uncertainty. Burlington, VT: Gower Publishing Company.
Snowden, J., & Boone, E. (2007). A Leader's Framework for Decision Making. Harvard Business Review, 85(11), 68-76.

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