Be Helpful

Abstract

Chris and Fred discuss the importance of being helpful when it comes to reliability engineering. After all, it is much easier to have people want to come to you as opposed to forcing them to do something they don’t want to. To be influential is to be helpful.

Key Points

Join Chris and Fred as they discuss how important it is to be helpful as a reliability engineer. Too many reliability engineers complain about not being heard or listened to. And it often starts with them not trying to be helpful.

Topics include:

Influence. Reliability engineers often complain about not being influential enough. That means people don’t listen to them. But the decision to listen or follow is an emotional one. And if reliability engineers aren’t there to help, then people decide to not seek them out. Which means you are not influential.
You still need visionary leaders. And that is because to help employees, designers, managers, and manufacturers out, you often need to help them ‘look good’ in the eyes of their leaders. But if those leaders are so focused on slashing costs and schedule (which means there is a rush to build the ‘wrong thing fast’) then you are not going to be helpful when doing good reliability engineering.
… so sometimes you need to ‘help’ leaders. This means finding ways to convince leaders to complete reliability and quality actions ‘today.’ And this means helping them see the connections. For example, let’s say a leader has historically been against focusing on quality and reliability. But we know that 25 % of their effort is focused on rectifying defects or problems during production. If there are 100 people in this organization, then simply halving the amount of ‘rectification effort’ effectively means that you now have 12.5 more full-time staff who can focus on other things. This might be all the help the leader needs to change direction.

Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.