Steve Ballmer

Steve Ballmer / Getty

Late last week, it was revealed that after more than a decade as the head of Microsoft, Steve Ballmer would be stepping down within the next year. Over at Three Star Leadership, Wally Block has put together a few comments from other sources regarding Ballmer’s departure, and I wanted to add mine to the mix.

Ballmer’s resignation at this point in time is a failure of leadership. Barring extenuating circumstances, or a private matter, Ballmer did a disservice to the company he gave his life to and the employees he led. Here’s why:

Steve Ballmer put the company and its employees in a state of limbo.

Had Ballmer wanted to retire or resign, he should have done it before he stood in front of the media and announced Microsoft’s reorganization plan. Or, he should have waited out the transition, hoping it would work. At least give it another year.

By announcing that he was resigning/retiring when he did, he effectively killed the reorganization plan he just announced. There is no successor-in-waiting, so the person leading Microsoft next would not have been part of the reorganization process. It’s a hunt they don’t have a dog in.

As a leader, trying to implement another leader’s strategy is not something I would want to do, regardless of the company. And I wouldn’t do it. I would either develop my own strategy or just not take the position. My leadership style is not like Steve Ballmer’s. In fact, no one’s style or strategy is like Ballmer’s. It can’t be implemented like he would do. They don’t understand the strategy as he did.

Any leader worth his or her salt will implement his or her own strategy. The next CEO should not have …read more


I was reading an article the other day about how companies were using machine learning to keep track of the huge amounts of data that are generated these days. Machine learning is a branch of computer science where “algorithms learn from and react to data just as humans do. Machine-learning software identifies hidden patterns in data and uses those patterns both to group similar data and to make predictions. Each time new data are added and analyzed, the software gains a clearer view of data patterns and gets closer to making the optimal prediction or reaching a meaningful understanding.”

For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages. After learning, it can then be used to classify new email messages into spam and non-spam folders.

Machine language does this by:

turning the conventional data-mining practice on its head. Rather than scientists beginning with a (possibly biased) hypothesis that they then seek to confirm or disprove in a body of data, the machine starts with a definition of an ideal outcome which it uses to decide what data matter and how they should factor into solving problems. The idea is that if we know the optimal way for something to operate, we can figure out exactly what to change in a suboptimal situation.

So machine learning starts with the ideal. It then figures out how to move what is closer to the ideal. I guess you have to be an idealist to be able to think that way.

In the Sermon on the Mount in Matthew 5-7, Jesus likely offers the clearest picture of what life looks like in the Kingdom of God. It’s an idealistic picture, is it not? “Blessed are the poor… for they will…” Jesus then sets out to …read more


Finishing up this short series on rhetoric, persuasion, and leadership, I want to help us rethink and reframe persuasion. After dealing with the question of logic or emotion, now we come to how I think we should look at how to influence and lead others, regardless of the organization you lead.

Utilizing Aristotle’s appeals, neuroscience’s research, Duarte’s common structure, and Kouzes and Posner’s leadership characteristics, a way to integrate all these for effective persuasion can be developed. Why? A big part of a business leader’s responsibilities is to motivate people to achieve certain goals. To do that, the leader has to engage the person’s emotions (Fryer).

Traditional rhetoric, giving statistics and facts and quotes from authorities has two problems, according to screenwriter, professor, and consultant Robert McKee. First, the people spoken to will have their own set of authorities, statistics, and experiences. While the communicator is trying to persuade them, those people are arguing back in their heads. Second, if the leader does succeed in persuading them, they have done so only on an intellectual basis. That’s not good enough, because people are not inspired to act by reason alone (Fryer, para. 5).

McKee continues, stating that a second “way to persuade people—and ultimately a much more powerful way—is by uniting an idea with an emotion. The best way to do that is by telling a compelling story” (Fryer, para. 6). This connects with Duarte’s back and forth resonance concept because leaders not only have to understand their companies’ past, but then they must construct a “what will be if we do this” future.

It might be expressed in the following manner. Each of Aristotle’s appeals have equal weight. One does not have prominence over the other and effective rhetoric not only uses all three appeals …read more