Problem Structure vs. Solution Structure
Wednesday, October 30, 2013
Structuring is at the heart of most problem solving methods. Structuring your problem is probably the most important activity you'll perform in the problem solving process.
The purpose of these structuring activities is to help you create a representation of your problem. This model of your problem becomes the framework that you build your knowledge upon.
In a group setting, structuring allows members to share a similar mental model of the problem. This shared representation of the problem is vital to maximizing everyone's capacity throughout the problem solving process.
"How do I create the most effective structure for my problem?"
I think the best way to create your structure is to use my structured analytical techniques. Yeah, I admit I'm biased towards this approach. But keep in mind, I've done a lot of problem-solving during my 20+ years in the consulting business. I've analyzed problems at 100+ companies and have successfully created 1,000+ solutions. Believe me when I tell you that I've been through the school of hard knocks working on some these problems. And there's been some real pain along the way. I'd really like to save you from experiencing the same, so I created this website to provide you with all the best problem solving tools and techniques.
Most problem solving approaches begin with analyzing the problem. Typically you start by stating your problem in a clear and concise written statement. Next, you decompose your problem into its component parts. Once you've identified the all parts of your problem you're able to manipulate your data using routine functions, such as, sorting, filtering, and prioritizing. Conventional wisdom also suggests you may want to analyze your data by searching for relationships, looking for comparisons, and creating visual representations.
In my proprietary programs, called Solvers, I've strived to demystify the traditional structuring process by creating best practices. I've accomplished this by standardizing the structuring process and basically turning it into a mechanical process.
One of my innovative methodologies is to split the analytical process into two separate branches: objective data and subjective thoughts. Objective data includes your factual and unbiased data (in-other-words, this data is not influenced by your personal feelings, interpretations, or biases). Conversely, your subjective thoughts are your own personal thoughts and feelings.
Your objective data is grouped into major categories. Next, you divide it into interrogatory dimensions (i.e. who, what, when, where, why, how, from where, & to where). It may also be helpful to further classify your data by data type, such as, key questions, information, tasks, and goals.
Your subjective thoughts should also be grouped by the same major categories discussed above. Next, your subjective thoughts are classified by type. Examples of subjective thought types are: expectations, intentions, assumptions, intuitions, opinions, conclusions, judgments, beliefs, hopes, & gut feelings. I generally refer to these types of personal thoughts as predispositions.
One of the most unique and powerful features of my approach is that it superimposes the structure of your problem on to your solutions. This is a really important concept because certain aspects of your solution will mirror specific characteristics of your problem. Within the highly structured environment of my Solvers, you can more effectively evaluate the essential structural elements and critical data relationships between your problem and your solutions.
by Keith Glein, Founder & CEO