What 3M Started Case Study

Pages: 6 (1850 words)  ·  Bibliography Sources: 6  ·  File: .docx  ·  Level: Master's  ·  Topic: Business - Management

Entrepreneurship, Innovation, And Statistical Process Control

The advantages and disadvantages of a commitment to efficiency through Six Sigma vs. An orientation to work that encourages and reinforces creativity and innovation depends on the perspective of the observer or investigator. When considering the benefits and drawbacks of each of these two poles of the spectrum of approaches to work, the key to understanding perspective-taking may simply be whether a problem has already been solved and a process has grown up around that problem, or whether a problem exists for which a solution has not been found or a process is so unsatisfactory that it warrants improvement. It seems that the two positions reflect different stages of research, development, and implementation. However, the question still begs: what if the discovery of a better process requires beginer's eyes? That is to say that a clear and overarching vision cannot be achieved without a mindset that exhibits a willingness to question the rules and seek a deeper understanding than simply conforming to a process, particularly when the process seems to have taken on a life of its own.Get full Download Microsoft Word File access
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Case Study on What 3M Started Assignment

There is a fundamental tension in an entrepreneurial endeavor that can perhaps be expressed as the idea of reach: not marketing reach, but the presumption that there is further to go -- that something is yet to be discovered or improved. Discovery and improvement are, at the most basic level, chains of actions or behaviors that lead to some, hopefully important, change. Babineaux and Krumboltz (2013) posed a contrarian theory that suggests the fast track to innovation is best paved by fast failure. In their book, Fail Fast, Fail Often: How Losing Can Help You Win, Babineaux and Krumboltz argue that innovation can't escape its developmental nature, and that getting through the necessarily ignorant and clumsy stages is best done quickly. This type of trajectory can produce the quickest success, and perhaps the highest quality, the author pair argue, since the process enable a creative spewing that gets the obvious, obscure, and nascent mistakes out on the table in short order: from that position, it becomes easier to see what is needed to move forward. Yet, the heart of Six Sigma is that a perfected process is the end goal, and that everything else must coalesce around a previously defined and practically error-free process. It is difficult to reconcile the fundamental proposition of Six Sigma with an entrepreneurial spirit driven by the search for innovation.

Programmed and Non-Programmed Decisions

Reductionist models of decision-making are often seen to use the dichotomy of programmed and non-programmed decisions. In a categorical framework such as this, programmed decisions are considered to be so routine and common that they are practically automatic, whereas non-programmed decision deal with uncommon situations that are not often encountered by the decision-maker (Nelson & Quick, 2015). Programmed decisions can be further explained by these circumstances: Explicit guideline or rules exist for the decision-maker to follow, and the decision-maker has experienced the conditions that trigger the decision many times in the past (Nelson & Quick, 2015). Non-programmed decisions, on the other hand, are not associated with any guidelines or rules to follow since the conditions triggering the need for the decision may be unique, or are at least new to the decision-maker (Nelson & Quick, 2015). In addition, non-programmed decisions are made from the information the decision-maker can gather, and most likely also from their judgment derived from experience or intuition (Nelson & Quick, 2015). When non-programmed decisions must be made in the workplace, trust is an essential element of the relationships of people impacted by non-programmed decisions, which, of necessity, require an element of creativity (Nelson & Quick, 2015). This is particularly true when decisions lead followers outside of their comfort zones and away from their quotidian work habits, some of which may be strengthened by highly controlling processes and inherited mindsets, such as might be experienced in an environment that emphasizes Six Sigma.

"Power is the faculty or capacity to act, the strength and potency to accomplish something. It is the vital energy to make choices and decisions. It also includes the capacity to overcome deeply embedded habits and to cultivate higher, more effective ones" (Covey, 2008).

Rational, Bounded Rationality, and Garbage Can Models Of Decision-Making

Rationality is characterized by step-by-step approaches that logically analyze alternative actions and the consequences of those decisions (Nelson & Quick, 2015). The assumption underlying rational decision-making is that rational decision processes ostensibly produce rational outcomes (Nelson & Quick, 2015). The tenets supporting this belief include a fairly inclusive awareness of the alternatives, the use of a consistent process to determine the best alternatives, and the capacity to formulate the probability of success for each of the alternatives (Nelson & Quick, 2015). It is readily apparent that the rational approach to decision-making is a good fit with the statistical control processes which are designed to eliminate human error and human whimsy.

Bounded rationality suggests that there are limits to the degree of rationality a decision-maker can employ (Nelson & Quick, 2015). Bounded rationality is based on finding the alternative that is a best fit to the criteria and the problem, with the idea that the solution will have to satisfice because the time, effort, and resources that would need to be expended to find a solution beyond that level are simply too great (Nelson & Quick, 2015). When employing bounded rationality, decision-makers understand that their conceptualizations are incomplete, that there is no practical way around that circumstance, and that their decisions will need to be made without considering or examining all the possible alternatives (Nelson & Quick, 2015). From this basis, decision-makers resort to making decisions by rules of thumb or through the use of heuristics, which are basically tools to simplify cognitive tasks such as thinking about decision-making (Nelson & Quick, 2015). Entrepreneurial thinking aligns well with bounded rationality, in that, innovative thinkers are not concerned with moving through a long list of possible alternatives, nor are they concerned with being able to appreciate and understand the universe of possibilities. Accepting the idea of one good fit as opposed to the very best possible fit is a position that enables innovators to move forward: this avoid the situation where the good idea -- or even excellent idea -- falls victim to the perfect.

The garbage can model assumes that decisions made in organizations are both unsystematic and random (Nelson & Quick, 2015). While this garbage can model may seem like a situation that can only lead to chaos and inefficiency, there is an element of chance that elevates the model. Consider the power of disruptive inventions: it is difficult to imagine that an entrepreneur would set out to disrupt technology or some other field of endeavor. Rather, entrepreneurs are viewed as individuals who have a fairly specific idea and run with it. Clearly, intuition and creativity in decision-making can open doors to solutions that have never been on anyone's docket. Indeed, the history of invention is packed with examples of happy, accidental discoveries that occurred while an inventor was preoccupied by some other problem or consideration. This is the essence of 3M's efficiency and creativity conundrum. The idea of devoting time to researching and developing an idea that is of personal interest to an employee is popular, with companies like Google adapting the concept to fit their culture and operations. According to Jeff Atwood of Lifehacker,

"When you're hired at Google, you only have to do the job you were hired for 80% of the time. The other 20% of the time, you can work on whatever you like -- provided it advances Google in some way. When you're hired at Google, you only have to do the job you were hired for 80% of the time. The other 20% of the time, you can work on whatever you like -- provided it advances Google in some way" (Atwood, 2012).

While employees are likely to appreciate the idea, it is unlikely that it would continue within an organization or be replicated in other businesses if it did not bear fruit, so to speak. Some version of the 15% Rule (20% Rule, Hack Day, Ship It Day, lab store convention) has shown up at Atlassian, Hewlett-Packard, and Yahoo -- and, most likely, countless other companies with less public exposure. The occasion for these types reserved and respected discovery times has to come from leaders. As DeMarco, (2002) put it, "Daydreaming is not the antithesis of work; on the contrary, creative problem solving requires it."

I would much rather work in a company where decision-making emphasizes the pursuit of innovative solutions and products that hold the promise of significant commercial return. Inherent in this type of decision-making is the acceptance of risk taking as a way of operating and an understanding that failure will occur. Time spent daydreaming and thinking about problems and solutions pays bigger dividends than time spent looking busy for supervisors and middle managers. Daydreaming that leads to… [END OF PREVIEW] . . . READ MORE

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