I was first introduced to OEE in 2008. After working with it for 11 years, I’ve decided to summarise my thoughts and experiences with it.

I’ve read several textbooks, consulted corporate manuals and gone back through a stack of notes from meetings with customers and consultants. As I scan all the material, I’ve concluded that OEE is very promising, frustrating, polarising and boring – at the same time!

In this post I’m going to unpack OEE at a high level. Then I’m going to boil it all down to some key questions to help you determine if OEE is something you should be using.

But before that, a brief history and explanation of OEE.

How do you react to data from your manufacturing plant?

A part of my job that I really enjoy is seeing the reaction of customers seeing their first live data come in. There’s usually an immediate comment like, 'why is that not running?' They may get on the phone and ask someone to explain what's going on. It’s a natural reaction, you get excited about the new possibilities.

But if picking up the phone and asking (or ordering) people around is your main strategy, you’re an over-reactor.

For every over-reactor, there’s going to be an under-reactor too. Despite months or years of data that’s telling a very clear story, they seem un-moved. There’s no reaction.

Or perhaps you’ll identify with the pattern of the flip flop person. Months of inaction followed by a frustrated flurry of over-reaction. “The boss in on the war-path”.

This blog article will introduce a tool that will help anyone develop more consistent and appropriate reactions to data. An essentially skill for data-driven managers and evidence-based leaders.

Unlike your car, you can’t get a warrant of fitness for evaluating the condition of your business. In particular, for your manufacturing business in collecting and using data.

As I described in my data pyramid post, simply capturing machine and process data does not automatically lead to improvement. Yes, you may get a bump from the Hawthorne Effect. But settling for that would be a wasted opportunity.

To get the biggest and most sustained benefit, there are multiple moving parts to work with. Our DataWOF makes it easy to evaluate these. It will help you see the whole pyramid and find the areas that need work.

Answer, Regular Review. That might sound like a dull answer. But I think it’s the correct one. In this article I have two jobs to do. The first is to convince you of the significant benefits of regular review. If I can do that, then the second is much easier. Namely, to provide practical help on how to implement it for yourself.

Before we go much further, what is a regular review? One thing it’s not is massaging data in Excel or a BI tool. That’s data analysis. A review is more thoughtful, personal and powerful. It uses various information sources as well as your gut to reach points of clarity. It then moves into planning, so you know what to actually do.

Do you consider yourself an effective data-driven manager? To be one, you need to wrestle with targets and goals.

I’m not just talking about personal targets and goals (which are challenging enough), I’m talking about the use of them in your manufacturing workplace. An environment of people, processes, machines and surprising complexity.

Until recently, I only thought there was one approach. Call it the outcome-based approach. In this article, I’d like to discuss a different approach, one that might suit you better. There is no right answer as to which is better. But don’t blindly adopt option 1 without considering option 2.

The problem of jumbled conversations

Imagine you're in a meeting to plan a new building. There would be discussion about consents, foundations, land, structure, cladding among other things. Now, imagine that the discussion is a jumble of different ideas all being chipped in randomly. One minute you're discussing the grade of steel to be used. The next someone says they've seen a nice new couch that could go in the foyer. From nowhere someone adds a deep and meaningful comment about how the building should lift and empower people.

Now imagine that despite all the energetic talking, a suitable roof isn't included in the project! It's an unlikely example. That's because in general, people are familiar with the design and build process used in construction.

But when the topic is using data and metrics to improve manufacturing.....

Type "running successful meetings" into a search engine. You'll get the usual list of good practices. But putting data at the center of the meeting doesn't seem to get a mention.

Let’s face it, team meetings can be the low-point of the business day. They are often seen as time-wasting opportunities for certain people to over-analyse some recent failure, lay blame on others, or justify their own actions (or inactions).

But it doesn’t have to be that way. Meetings can, and should be an efficient tool for sharing information, ideas and generating action. To achieve this, start running data-driven meetings. If you do, it could turn out to be one of the most productive changes you make to your business this year.

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