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283 - Habit #4: Decide with Data with Peter Horsburgh

 
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Habit #4: Decide with Data with Peter Horsburgh

It’s my pleasure to welcome back Peter Horsburgh. He is the author of the Five Habits of Extraordinary Reliability Engineers.' He has a long history within reliability engineering. He essentially started in manufacturing, then moved to mining, then to power generation, and to aluminum smelting.

In this episode we covered:

  • Now we’re here to discuss habit number four; decide with data. So, what does this mean to you?
  • You mentioned data-driven debate. What is it?
  • In the book, you said problem solving should follow a framework. You mentioned problem-cause-solution-value framework. Can you elaborate a bit on that?

Previously we discussed your book, Five Habits of an Extraordinary Reliability Engineer.' Can you remind us of what those five habits are?

  1. Identify
  2. Understand
  3. Question
  4. Decide with data
  5. Facilitate to implement

Now we’re here to discuss habit number four; decide with data. So, what does this mean to you?

For us as reliability engineers, the thing or the commodity we use to get our message across is data, essentially. We work with the people that make decisions about the plant. What we need to do is use the data that we’ve collected, good or bad. We work with the best information we have at the time. We want to have the skills to be able to turn that data into information, as well as the skills to be able to present that data in a form that people agree to it.

You mentioned data-driven debate. What is it?

It is using information that we’ve already gathered or data that we’ve already gathered to manning an argument, and then presenting the data in a way that people can say, yes, we need to do that.

In the book, you said problem solving should follow a framework. You mentioned problem-cause-solution-value framework. Can you elaborate a bit on that?

It’s more of a template of presenting information. So, what I’m trying to do is give reliability engineers a framework to work to. When you’re communicating information that you’ve gathered from data, then turned it into information, you want to turn that into knowledge for others. So, in your presentations, the problem cause solution and value, (PCSV) is the framework that you should use.

PCSV Framework:

  • P is for the problem that you're solving
  • C is for the cause; showing what is causing the problem. Understand the course habit, too.
  • S is the solution that you propose or solutions. Come up with an effective solution.
  • So, the last part of the framework of the P C S V is value. What’s are we here for? What do we need as reliability engineers?

I’ve heard the term publisher perish.' You hear this with academia, professors, research, staff, that type of thing. How does that apply to reliability?

If you don’t publish, i.e., showing people value in what you do even if it’s small little things, but constantly looking for stuff and actively actually getting out there and promoting it yourself. If you’re not out there publishing and showing people value, you’re going to perish.

Take some lessons from the sales and marketing and incorporate that into what you do. You should have the opportunity to speak a lot if you’re good at habit one, which is identifying. As you go along, identifying problems leads you into understanding and habit too. So, you need to be doing that routinely.

So how does one implement this habit in their daily work as a Reliability Engineer?

I would say constantly. One of the skills or skill sets that I believe that reliability engineers need is a little bit of data science. You don’t have to go into the detail of database design or anything like that, but you need to be able to understand how data is formatted. We use data, we take the data, and we turn it into information so that people can make decisions.

We understand how the plant works; we are engineers. We understand what solution needs to be applied. We communicate that to the accountants and managers of what needs to happen, we are unify the plant floor and the management team inside the organization.

What is the one action you could have our listeners take away, one thing they can do differently in their plants?

The one thing I would like people to remember about this conversation is that when you’re presenting your data, ensure the data is presented in a way that people see where the problem is within three seconds of looking at your PowerPoint slide, your diagram, or any visual. I challenge this to all Reliability Engineers.

Where can people find out more about you, your book, and the resources to all these great things?

LinkedIn is my social media channel of choice. The book is not just available in Australia, but also via reliabilityweb.com, and the bookstore as well. They’ve also set it up on Amazon, it is available globally now. Reliabilityextranet.com is our website.

Any other resources you want to share with our listeners around deciding with data?

If you haven’t found power BI yet, I suggest that you do. It is like a PowerPoint style tool for analyzing data. It gives you a full ecosystem, allowing you to publish and automate the process.

Eruditio Links:

Peter Horsburgh Links:

Download RSS iTunesStitcher

Rooted In Reliability podcast is a proud member of Reliability.fm network. We encourage you to please rate and review this podcast on iTunes and Stitcher. It ensures the podcast stays relevant and is easy to find by like-minded professionals. It is only with your ratings and reviews that the Rooted In Reliability podcast can continue to grow. Thank you for providing the small but critical support for the Rooted In Reliability podcast!

The post 283 – Habit #4: Decide with Data with Peter Horsburgh appeared first on Accendo Reliability.

  continue reading

336 episodes

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What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 304865945 series 2359258
Content provided by James Kovacevic. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by James Kovacevic or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Habit #4: Decide with Data with Peter Horsburgh

It’s my pleasure to welcome back Peter Horsburgh. He is the author of the Five Habits of Extraordinary Reliability Engineers.' He has a long history within reliability engineering. He essentially started in manufacturing, then moved to mining, then to power generation, and to aluminum smelting.

In this episode we covered:

  • Now we’re here to discuss habit number four; decide with data. So, what does this mean to you?
  • You mentioned data-driven debate. What is it?
  • In the book, you said problem solving should follow a framework. You mentioned problem-cause-solution-value framework. Can you elaborate a bit on that?

Previously we discussed your book, Five Habits of an Extraordinary Reliability Engineer.' Can you remind us of what those five habits are?

  1. Identify
  2. Understand
  3. Question
  4. Decide with data
  5. Facilitate to implement

Now we’re here to discuss habit number four; decide with data. So, what does this mean to you?

For us as reliability engineers, the thing or the commodity we use to get our message across is data, essentially. We work with the people that make decisions about the plant. What we need to do is use the data that we’ve collected, good or bad. We work with the best information we have at the time. We want to have the skills to be able to turn that data into information, as well as the skills to be able to present that data in a form that people agree to it.

You mentioned data-driven debate. What is it?

It is using information that we’ve already gathered or data that we’ve already gathered to manning an argument, and then presenting the data in a way that people can say, yes, we need to do that.

In the book, you said problem solving should follow a framework. You mentioned problem-cause-solution-value framework. Can you elaborate a bit on that?

It’s more of a template of presenting information. So, what I’m trying to do is give reliability engineers a framework to work to. When you’re communicating information that you’ve gathered from data, then turned it into information, you want to turn that into knowledge for others. So, in your presentations, the problem cause solution and value, (PCSV) is the framework that you should use.

PCSV Framework:

  • P is for the problem that you're solving
  • C is for the cause; showing what is causing the problem. Understand the course habit, too.
  • S is the solution that you propose or solutions. Come up with an effective solution.
  • So, the last part of the framework of the P C S V is value. What’s are we here for? What do we need as reliability engineers?

I’ve heard the term publisher perish.' You hear this with academia, professors, research, staff, that type of thing. How does that apply to reliability?

If you don’t publish, i.e., showing people value in what you do even if it’s small little things, but constantly looking for stuff and actively actually getting out there and promoting it yourself. If you’re not out there publishing and showing people value, you’re going to perish.

Take some lessons from the sales and marketing and incorporate that into what you do. You should have the opportunity to speak a lot if you’re good at habit one, which is identifying. As you go along, identifying problems leads you into understanding and habit too. So, you need to be doing that routinely.

So how does one implement this habit in their daily work as a Reliability Engineer?

I would say constantly. One of the skills or skill sets that I believe that reliability engineers need is a little bit of data science. You don’t have to go into the detail of database design or anything like that, but you need to be able to understand how data is formatted. We use data, we take the data, and we turn it into information so that people can make decisions.

We understand how the plant works; we are engineers. We understand what solution needs to be applied. We communicate that to the accountants and managers of what needs to happen, we are unify the plant floor and the management team inside the organization.

What is the one action you could have our listeners take away, one thing they can do differently in their plants?

The one thing I would like people to remember about this conversation is that when you’re presenting your data, ensure the data is presented in a way that people see where the problem is within three seconds of looking at your PowerPoint slide, your diagram, or any visual. I challenge this to all Reliability Engineers.

Where can people find out more about you, your book, and the resources to all these great things?

LinkedIn is my social media channel of choice. The book is not just available in Australia, but also via reliabilityweb.com, and the bookstore as well. They’ve also set it up on Amazon, it is available globally now. Reliabilityextranet.com is our website.

Any other resources you want to share with our listeners around deciding with data?

If you haven’t found power BI yet, I suggest that you do. It is like a PowerPoint style tool for analyzing data. It gives you a full ecosystem, allowing you to publish and automate the process.

Eruditio Links:

Peter Horsburgh Links:

Download RSS iTunesStitcher

Rooted In Reliability podcast is a proud member of Reliability.fm network. We encourage you to please rate and review this podcast on iTunes and Stitcher. It ensures the podcast stays relevant and is easy to find by like-minded professionals. It is only with your ratings and reviews that the Rooted In Reliability podcast can continue to grow. Thank you for providing the small but critical support for the Rooted In Reliability podcast!

The post 283 – Habit #4: Decide with Data with Peter Horsburgh appeared first on Accendo Reliability.

  continue reading

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