Dealing with Complexity


Why do you need Reusable Knowledge and/or Collaboration to implement good Root Cause Analysis, Problem-Solving, Trade Studies, or Decision-Making??


Because the complexity of real-world problems means the first analysis is never the last analysis... so, we need to design our analyses to be reusable over the course of the project.  As more knowledge is learned and more experts get involved, we want to efficiently modify the existing analyses, and then use those to narrow the decisions further (reusing the decision-making tools), and then continue learning in that narrower design space.

And then there's the gravy:  all of those analyses and the related decision-making remains reusable when the next project comes along!  But you need the reusability now, for this project, because that's the only way to efficiently deal with the complexity.

So, "Dealing with Complexity" is the reason our Success Assured™ software integrates the various learning, analysis, and decision-making tools into a knowledge management server that can coordinate and manage all the ongoing collaboration, continuous improvement, and convergent decision-making that needs to go on to succeed in the face of that ever-growing complexity.

See our Reusable Knowledge web page for more on how we achieve true knowledge reuse, unlike traditional search-based Knowledge Management tools.


But more than that, supporting efficient collaboration in the face of ever-growing complexity requires tools that help people see what they need to see by allowing them to focus on the portion of that complexity that is currently of interest without it being occluded by all the rest of that complexity.  

To enable that, our Success Assured™ software makes it easy to:

  • Effectively "zoom out" to see the big picture or "zoom in" to dig into the details... without need for the author to predict what levels of "zoom" different readers will want
  • Prune away the complexities you don't want to think about so that you can focus on the complexities that you do... without the author needing to predict the subsets different readers will want

  • Rearrange the knowledge multiple different ways so that you can see the patterns and the affinities... without the author needing to predict the patterns that might emerge

  • Look at different 3D slices through the multi-dimensional design space... without the author having to predict the slices that will be most effective for different people

If the reusability of the knowledge requires the author of the knowledge to write it or draw it in the right ways for all future re-users of that knowledge, then you are putting a heavy burden on the author and likely dooming yourself to low reuse.

Contact us now to learn more on how we can help your organization better deal with the complexity of its problems.

Contact us now to learn more
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