Week 5 Article Summary

This week as part of the articles, we also have been given a list of questions to focus upon as well as some general reflections. I’ll tackle the required questions, but will also blog about any ideas I found interesting. I’ll blog articles in order of the questions.

Action Learning in Action: Transforming Problems and People for World-Class Organizational Learning. Marquardt.

System thinking is a skill that I have personally been trying hard to master. At work, I strive to look at problems from all aspects and think of how it would impact not only my area of expertise, but all areas. I like reading about system thinking and hope that we discuss more than the short blurb in this article.

The six steps of problem solving that are described in the article are fairly self-evident, but laying them out shows where steps are often missed or skipped. Some problems really do need all these steps, but simple problem-solving often does not lend itself to this formal of a model.

I believe that determining the root cause of the problem is the most important step. Problems will occur and be solved, but until the root cause is known, the problem will likely surface again. Getting to the source of the problem will help to understand the problem itself and will be input into the solution.

There are 2 steps that are before the root cause. The first is presenting the problem. This is likely from the person reporting the problem and may or may not be the true problem at hand. In the second step, “reframing the problem”, a group will validate that the problem presented. This is necessary as some problems may be a result of another or not a problem at all. These two steps are necessary to properly identify the problem before the cause of the problem can be determined. I believe that often reframing will lead directly to the root cause especially when the source of the problem is easily found.

After the root cause, the following 3 steps are important to develop solutions, evaluate them and implement. However, these cannot be properly performed with knowing the root cause.

The pizza man story and subsequent dialog about looking for fresh ideas and alternatives is very interesting. I have seen many times when someone new or unfamiliar with a problem presents a questions or solutions that are often overlooked. I also believe that turnover in a company is a good thing because with the same persons doing the same job, stale thinking results. Having new and outside persons look at a problem is a great idea and something that I will have to keep in mind.

Understanding & Supporting Decision Making. Klein.

Naturalists seek to make observations that are a precursor to the traditional decision-making process. Naturalistic Decision Making (NDM) is a process of solving problems using analysis and observations in the natural setting of the problem. Traditional decision making starts with a theory and NDM observes before forming a theory. NDM studies problems and does not make immediate decisions. Teams are often set in the problem area like a battlefield instead of using traditional problem solving methods.

Klein challenges that abstraction is not a good thing in problem solving and that seeing that actual problem in its setting may make solving it easier. This makes sense, but is different than some of the abstraction premises made in IT.

Situational awareness is a term used that describes how naturalists make decisions. I think this is a very important phenomenon because in order to solve a problem, you have to be aware of that the situation is and act upon it. Every problem is different and knowing the context of it will lead to the cause and decision.

What Data Mining Can and Can’t Do. Alter.

Data mining, modeling, and warehousing cannot capture randomness in the way people behave. Trends about a demographic may be collected, but individual habits may times cannot be explained. The article challenges that the more data that is collected, the more likely the data may be skewed due to random behavior.

To summarize the article I would say that random behavior cannot be caught by looking at data. Data mining is good for collecting information and breaking it into groups, but cannot be depended upon for all decisions. Sometimes keeping things simple can be better than trying to analyze every minor detail. “Situational awareness” from the previous article is applicable in this article as well. “It depends” is another term that I frequently use because every problem is unique and a one-size-fits-all answer never works.

Five Steps to Business Intelligence Project Success. Wise.

The first part of the article talks how it is difficult to measure intangible benefits. It also talks about time and budget in terms of project success. In class we have talked about you retain only certain knowledge from classes. From one project management class, I have retained the notion that it is not just time and money, but also quality that are factors that act upon each other. If you are on time and on budget, but quality may not be there. And high quality can mean higher costs and longer timeframes. BI is an attempt to gather information in a form which can help drive decisions.

The five steps that are described in this article are very similar to the six steps in the previous article. Identify, determine, understand, train, and implement the solution are similar to problem solving. I also think that the premise of the article is similar to the data mining article above in that the solutions it often depends on the situation. BI must be implemented with the solution in mind.

General Reflections.

“Decision-making” versus “Problem Solving”

Decision-making implies that there are alternatives from which to choose while problem-solving is making the alternatives. I do believe that the two work together very closely, but are different in nature. I think that people use the terms interchangeably.

True or false: There are good decisions, and there are bad decisions.

True, but there are many times decisions that are in the middle and have good and bad consequences. Many problems do not have a binary outcome and therefore cannot be either entirely good or bad. The definition of a “wicked problem” accurately describes that there is not always a good and bad alternative.

True or false: Better information yields better decision making.

True, again sometimes. Based on the last two articles, I’ll straddle the fence and say that better information can help, but not always. Randomness dictates that even with much information, decisions do not always follow a pattern.

True or false: Better knowledge yields better decision making.

True, again sometimes for the same reason above. However, I would rather have knowledge than information. Knowledge will have more context than just information. Knowledge is knowing what to do with information. Information alone is useless unless it is interpreted correctly.