Have you ever gone to a meeting and it started with random ideas in search of a problem, or maybe one idea that takes over the agenda? Do you ever get questionable ideas from your boss, peers or employees for the web site, adding to a backlog?
Perhaps you’ve launched something that has an unintended impact on your team’s time, or bought/built technology that sits stagnant. Maybe you find yourself wondering if you’re working on the right problems that impact agreed-upon goals, or if the ideas to solve those problems have any basis for impact.
When I ran Dell.com I had ideas flying my way in every day meetings and hallway conversations. Things move fast. Of course, there weren’t extra cycles to accommodate all ideas. There was skepticism on what problems new ideas would solve, and how much impact they would make.
We, as leaders, need to understand effort vs. impact before teams get to work. We need to understand an activity’s likelihood of impacting a relevant problem and goal. We need to understand downstream consequences. We might be skeptical and frustrated when new ideas come from left field, but taking a socratic method is an effective way to get things moving in the right direction. Or stopping something, if need be.
These hallway conversations and daily meetings are how initiatives are set in motion. So, before things go too far, you can take the Stephen Covey “seek to understand” approach to get on the same page with employees, peers and executives.
As such, you can choose from these 12 quick questions to ask in meetings, one on ones or in the hallways to direct conversations to high-impact outcomes.
What problem are you trying to solve?
What goal does that help us achieve?
How does this align to your priorities?
What will success look like?
What action(s) will follow after your idea goes live?
If you were to think bigger, what else would we consider?
What would happen if we didn’t do this?
What other solutions to this problem were considered?
What would you drop to do this?
Who else needs to be involved?
What is the data we can use to support this will work?
What data do we have to support this problem is important?
