Probability For Professionals

dice In a previous post, I pointed out that manufacturing professionals’ eyes glaze over when they hear the word “probability.” Even outside manufacturing, most professionals’ idea of probability is that, if you throw a die, you have one chance in six of getting an ace.  2000 years ago, Claudius wrote a book on how to win at dice but the field of inquiry has broadened since, producing results that affect business, technology, science, politics, and everyday life.

In the age of big data, all professionals would benefit from digging deeper and becoming, at least, savvy recipients of probabilistic arguments prepared by others. The analysts themselves need a deeper understanding than their audience. With the software available today in the broad categories of data science or machine learning, however, they don’t need to master 1,000 pages of math in order to apply probability theory, any more than you need to understand the mechanics of gearboxes to drive a car.

It wasn’t the case in earlier decades, when you needed to learn the math and implement it in your own code. Not only is it now unnecessary, but many new tools have been added to the kit. You still need to learn what the math doesn’t tell you: which tools to apply, when and how, in order to solve your actual problems. It’s no longer about computing, but about figuring out what to compute and acting on the results.

Following are a few examples that illustrate these ideas, and pointers on concepts I have personally found most enlightening on this subject. There is more to come, if there is popular demand.

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How Does This All Play Out?

It is a seemingly simple question, but one that is not asked as often as it should be. It challenges managers to consider the responses of other stakeholders and think beyond immediate consequences. It checks their “bias for action,” and makes them take a pause to think farther than one move ahead.

If you outsource an item, for example, will the new supplier eventually morph into a competitor? What know-how might you lose? How will it affect employee morale? Are you putting your quality reputation at risk?  The question is an invitation to work through multiple scenarios of responses by your suppliers, your work force, and your customers, reaching into the future.

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What a Plant Manager and Town Mayor Have In Common | Darrell Edwards | Industry Week

leadership-dictionary-page“If there is ever a time to discuss the similarities between plant leadership and politics, perhaps during an election year is as fitting a time as any.  Some time ago I was attending a class at Columbia University, and over a conversation at lunch with a professor, we discussed what a day in the life of a plant manager was like (I was a plant manager at the time).  After a bit of conversation about my typical day, the professor said, ‘It’s like you really are running for election as town mayor, aren’t you?'”

Sourced through from: Plant Manager/Town Mayor

Michel Baudin‘s comments:

In my presentation on the Lean Leadership Role of the Plant Manager at the Lean Leadership Summit last month, I used the ship captain as a metaphor, but the plant manager as town mayor is enlightening as well. The abstract of my talk was as follows:

The plant manager is like a ship captain, in daily contact with a team that may range from a handful to thousands of people, and accountable to an organization that is remote and has entrusted him or her with a valuable asset. The plant manager is the voice of top management to the plant and of the plant to top management, and represents the company to the local community. Of course, the plant manager must know how to pay bills on time and let maintenance use qualified technicians to fix forklifts, but there is more to the job, particularly about Lean leadership. The plant manager implements corporate policy but does not make it. If top management has adopted Lean, the plant managers can make it succeed or fail.

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