In today’s world, everyone is collecting data. It’s everywhere. Some even say we are innundated with data, so much so that we cannot keep up with the amount of data we can generate and collect. With this in mind, consider the following definition of data:
Given this definition, who among the following are more likely to think of the world as data in their professional work?
We can be fairly safe in saying that mathematicians do not see the world as data in their day-to-day work. Only a relatively few mathematicians deal with the real world at all in their professional work. While they may construct mathematical models that others (such as scientists or business managers) may find very useful in making sense of real-world data, mathematicians themselves are often quite unconcerned about the real-world usefulness of their work.
Scientists, on the other hand, use data extensively in their everyday work, but they use it under carefully controlled circumstances. They are interested in data in terms of its experimental reproducibility. They tend to think of the world in terms of patterns of data that occur and reoccur under certain specified conditions. They tend to think of real-world data in terms of how it conforms to predictable scientific laws.
Reporters think of the world as stories. Not rambling stories, but stories told in a certain way so as to communicate a lot of information in a short space. They efficiently extract information from the cacophony of life’s events by using the five W’s (though not necessarily in this order:
Depending on the nature of the story, experienced reporters usually try to work the answers to the 5-W’s into the first paragraph or so of the story. This enables them to accurately convey the context and gist of the story as soon as possible, so that anything else further down the column is merely an elaboration of what is already known. The point is that without the 5-W’s approach news reporting becomes less focused, more meandering, and results in less accurate information transmitted for the amount of print expended. But do reporters see the world as data in the sense we have defined it above? They certainly see the world as story based on information, but as data?–probably not. Even if a reporter were writing a financial story, for example, and even if that story contained numerical information that was organized in a form that could be analyzed in some way (for example, graphs or charts), that data would not be specific enough or numerous enough to be of much use to a bank or stock brokerage firm for decision making. Indeed, such businesses would probably have their own data analysis staff anyway or would contract out such services. Nevertheless, the 5-W tool for extracting and organizing information from the world is a useful one from which managers can profit. You will get the opportunity to try it out for yourself in this first unit.
Do detectives see the world as data? ”Nothing but the facts, ma’am,” says Joe Friday, the laconic police investigator of that ancient TV show Dragnet. Clearly, detectives think of the world as data. Not management-type data, but certainly as information that is organized for analysis in forms that can be used for making that one bottom-line decision - whodunnit? Of course, there are a host of decisions that precede this big one. The detective makes these decisions by drawing inferences from evidence, which is another way of saying ”by analyzing the data.” So while the data that detectives work with is quite different from the data that managers compile, there is a similarity in what the two do with the data, the way they marshal compelling evidence and draw inferences from that evidence as they argue their case. Everyone knows that detectives cannot make judgments or decisions that will hold up in court without the proper supporting evidence. So it is with business managers. They likewise must present their arguments based on proper supporting evidence. We will be concerned with what constitutes proper evidence and how to present it in almost all of the homework problems.
Because business managers have to constantly make decisions in less-than-certain circumstances, it is to their advantage to think of the world as data, almost to the extent that it becomes second nature to them, a way of seeing. While it is true that certain aspects of business occur with regularity, such as manufacturing processes or financial dealings, it is also true that many important aspects of business, such as sales trends or employee equity issues, are not reducible to known scientific laws. Then too, all aspects of business eventually come down to that one irreducible basic fact, the bottom line. For example, here is a list of bottom-line questions that a manager has to answer on a day-to-day basis that should make clear the case for thinking of the world as data:
Putting the case plainly: Would you place a person in a management position requiring answers to these kinds of bottom-line questionsif they could not see the world as data? This raises another question: Does this mean that managers have to be statisticians?
You may have noticed that the list of professions above does not include statisticians. To be sure, they are the real data professionals and data is their bread and butter. But statisticians are, in a sense, generalists. While they probably do see the world as data in a way that few others do, chances are that they do not see your particular business world as you do. As a business manager, you are in a position of responsibility and you are the one who has to make those bottom-line decisions that often have far-reaching consequences. Nevertheless, you do need to think of the world as data.
Which brings us to this point: is this then a statistics text for business managers? The answer is ”no, not really.” While you will gain experience in dealing with those all-important bottom-line questions listed above by using some rather basic techniques, it would indeed take a lot of statistical background to be able to answer them the way a statistician would. But companies do not, as a rule, hire statisticians as their managers. Similarly, this book is not written for prospective statisticians, but rather prospective managers who will have learned enough from the text to not only appreciate the value of data but also to be able to manage its collection and analysis. This means that they will be expected to understand the technical language of professional data analysts, at least enough to effectively communicate with them, and then to make sense of it all for both their employees and their supervisors. This book takes seriously the assumption that you will be involved either as managers or as team members of a group of professional data analysts in projects similar to those presented in the memo homework problems. This is why the book begins with a unit on thinking of the world as data.