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Kaleidoscope of Data (Part 3)

Mar 24, 2011

Please enjoy the 3rd installment of Kaleidoscope of Data. Look for part 4 next Thursday March 31st.

So what data do we use to inform decision-making? How do we define the amount and variety of that data? What are the criteria necessary to shape that data into information we need and can use? These are pretty interesting questions. They are not simple to answer and it is probable that an answer will generate more questions. They represent the kind of inquiry that is necessary to support a process of continuous improvement. In that arena seeking answers is a journey rather than a destination. They are perplexing, intriguing and thought-provoking. They also provide a link to our last discussion. Remember, we ended last time with this thought. “The data we use to measure and monitor, motivate and manage may exist as discrete pieces of information however that information interacts in a dynamic process we must learn to read and understand.”

For just a moment, let’s try to wrap our brains around that statement of learning how to read and understand a dynamic process. How might we do that? If we accomplish that, will we be on our way to finding solutions for those questions of what data, how much data, and what criteria? For the how part we need to think about producing opportunities that allow us to gather information in one place so we can examine it. For the accomplishing part we will need to think about the enormous diversity of data we have at our fingertips and how all that data impacts our reality. Let’s explore a strategy to help with that. You probably already guessed this, so it won’t be a surprise, we are going to incorporate and extend the concept of a kaleidoscope in this strategy. Why? Well, continuing the image of a kaleidoscope helps to visualize how different kinds of data can and do intermingle. Perhaps most important to this process is developing a perception of the kaleidoscope as not only an entertainment tool, but a thoughtful, creative and useful tool as well. Instead of just observing the color dynamics in a kaleidoscope, what if we could determine the color variety?

Here we go! Suppose we were to build our own kaleidoscope. Why would we do that and how would that work? Well, first we know that if we have any hope of succeeding in addressing those complex questions we have been discussing, we need to focus our thinking. Building a kaleidoscope, which is a tool designed to focus vision, is at least a good start and it gives us a working model of how data can interact. We know that there is a vast array of colors available to produce the crystals in our kaleidoscope.

We also know there are at least that many kinds of data out there with the potential of impacting our decisions. If we are strategic in selecting the data pieces, thoughtful in organizing the data pieces into useful categories represented by color variations, we can expect that our tool will provide some interesting insights for us as we turn the lens. By choosing colors (identifying the data we will observe), we are defining the contents of our kaleidoscope. Are you with me? OK, when we look into the eyepiece we see a multi-colored collection of crystals, or pieces of data. Here is where the dynamic part comes in. By adjusting our lens (turning) we can observe the shifts of the crystals and their interactivity that produces fluid motion. When the lens is still, a unique design appears. We choose the pieces that will interact; we establish the parameters of the interaction by placing those colorful pieces of data into one end of our focusing tool -our kaleidoscope. All the ingredients are present for us to observe how data interacts through the intermingling of those color crystals. By thinking about a simple childhood toy we can establish a model for analyzing data and a process for gaining insight into how the data produces reality and/or results. Now how cool is that?

Returning now to the issue of whether reading and understanding the interaction of data will help us answer our complex questions we need to note that this will only occur if we are successful in choosing our data sets effectively. In our exercise so far with the kaleidoscope we have made mention several times of the significant amount of data that is present around us. How we choose what data to put into our kaleidoscope is a critical and fundamental question. Those decisions will shape the vision we will see through our lens and ultimately shape how we use and respond to that vision and that data. There are models out there to help us with that. These models frame data into categories and generate perspectives on how different sets of data generate information and how to use that interactive information to answer prevailing questions and inform decision-making.

That topic my friends will be the focus of our next talk.

Category: explanatory

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