Statistics for Qualified Decisions

"You can't manage anything that you don't measure." That's a general principle valid in almost every area of life. It sounds obvious, but, in reality, we don't usually use or follow it. The reason is straightforward. Managers don't have enough information and statistics for making the proper decision. Instead, they use their experience, feeling, and intuition. While intuition shouldn't be overlooked, I am always happy if I can base my decisions on the analysis of reliable data.

I want to share with you my recent experience. Last week, I met one Director of Engineering of a luxury remote island resort. He just took over the management of the department and one of his first tasks to prepare the budget for the next fiscal year. You know, manning, operating expenses and more. One of the most significant unknown areas for him was manning of the engineering department. The resort is six years old, and the headcount of engineering in the last three years was the same.

He is a lucky guy because the resort implemented a very sophisticated maintenance management software since the beginning of the operation. The engineering staff uses the software properly, so all work orders were tracked in the software. He has involved me in helping him to analyze resort maintenance behavior and work orders history.

When you have structured data about maintenance, your answers are accurate

In the beginning, the new Director of Engineering and I couldn't find the reports we needed. Luckily, I was in a similar situation many times. Even if in the beginning, it might seem like a big mess of data, there is always a way to find what you want. That is, if there is a case structured database, the data includes the structure of your all property assets, and it is linked to proper work orders.

Here are two key indicators you can use to decide the best headcount for next year:

1. Monthly count of work orders - corrective maintenance and other departments requests

2. Monthly count of work orders - preventive maintenance

I used the same approach to help my friend. When we looked at the data in this way, it was quite easy to collect all the statistics from the last four years of operation and make a decision based not only on the most recent data but also on the trend it showed us.

We analyzed the data and looked at summaries in three main areas:

Engineering sections work orders from history

Monthly count of work orders based on Engineering sections was crucial to assess if we needed to hire more staff or not. It took only a couple of minutes to find out that all sections of the Engineering department are dealing with a similar count of work orders all the time. The summary nicely showed us that the increase of the Engineering headcount isn't necessary, even as the resort is getting older.

Assets - Locality/Equipment

The second summary was split as per the assets of the property. It showed us again that the count of work orders on individual assets is almost the same all the time.

Requests type

The last summary split the work orders into three groups, based on their type.

- Guest-related requests

- Other department requests

- Internal Engineering department requests

The situation was the same as with the other summaries - in the past four years, there was no significant change.

Conclusion

General Manager, as well as the Director of Operations, was satisfied when my friend DoE brought the statistical summary on their meeting. The figures have shown precisely how to decide how many staff should the Engineering department have in the next year. For the last four years, the total number of work orders is almost the same every month, which means that the engineering team is appropriately set up for standard maintenance operation. The discussion was short, effective, and based on real data, and nobody doubted that the decision was the right one. 


WRITE ME A MESSAGE

Do you have any questions, remarks, or would you like me to help you with something? 
Send me a message!