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Imagine you call a leadership team meeting to gauge how important the team feels digital transformation is to the company. Would anyone dare say it is not a strategic imperative, even if they privately thought it wasn’t? The meeting ends with seemingly clear agreement that digital transformation is mission critical. But what happens after the meeting, when the person tasked to lead digital transformation asks team members to nominate people to work on the effort? All too frequently, everyone says they can’t spare their scarce resources.

Everyone in the meeting publicly agreed with the direction. But when it came time to allocate resources, the apparent agreement turned into active resistance.

A key to confronting this challenge is to expose misalignments. Rather than letting disagreement simmer beneath the surface, make it crystal clear where your team agrees, and where it doesn’t. We have found that real-time polling tools can bring great clarity to these discussions.

Consider an example from work we did with a privately-held professional services firm. It’s not hard to see how technologies such as blockchain and artificial intelligence could reconfigure the industry. But it’s easy to disagree about the pace and scale of change and therefore the required strategic response. 

Learn more about uniting your senior team with our complimentary HBR article

We brought the top team together to review our analysis of industry trends. After a lengthy discussion, we asked each team member to use Pigeonhole Live, a polling solution offered by a Singaporean company, on his or her smart phone to anonymously enter the  percent of next year’s profits that they thought the firm should invest in new growth innovation (our firm Innosight uses Pigeonhole Live but has no formal relationship with the company). After the votes were cast, we displayed the data (waiting to unveil the votes helps to combat groupthink) as a word cloud, with numbers that had multiple votes appearing larger.

A summarized report would have shown that the average was 10 percent, with a standard deviation of four percent. But we were more interested in the outliers, which ranged from two to 20.

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