The impact big and fast data has made on organizations has never been more critical. There is no shortage of data sources or credible insights to help organizations to take action. So the question we asked ourselves at our latest contract with a major manufacturing company was this:
“Why is the compressor that our predictive analytics platform identified as a 90% assurance that complete failure would occur in 6 weeks not on any maintenance team’s list 4 weeks after the first alert was announced?”
The answer to this led us on a six-month journey through an introspection of the organizational structure that would change our client and our perspective forever.
Silo Walls Must Come Down
What once was an organizational structure that worked in 1952 when this company first began manufacturing parts for the automotive industry – was no longer viable in an era of fast moving data and changes by competition and customers.
Operations, Maintenance, Reliability, Accounting, Safety, and Sales Teams were all functioning in isolated units. Each had been created in this fashion to derive efficiency and cost cutting measures. In addition the historical relevance of each independent unit had been created as a vertical distribution of information – mostly in the form of specific instruction from the top down. This is no anomaly in the broad overview of American companies. Without exception manufacturing organizations have been functioning under this model for over 100 years.
The reason this model had been adopted throughout the modernization of manufacturing dates back to the inception of the assembly line and the methodology deployed around improving efficiency and cutting costs. By limiting the view of the assembly line worker to a short list of tasks, companies were able to measure specific movements down to the second. This created a hierarchal approach to managing workers, performance, and above all information.
By employing a “Need-To-Know” mentality around information – these units within the organization had become highly competitive around performance, innovation, efficiency, and control. By most accounts during our discovery phase – managers were incentivized by their individual units “efficiency rating” vs. all other units within the organization.
This culture of competition and lack of sharing and collaboration had created very thick and high walls around and more importantly between the other units.
Introducing Data Exposes The Interface Breakdown
When InCloud Control was first contracted to deliver a predictive failure analytics platform to this client we attacked the problem as we always had – as a system integrator with a focus on the IT function. We understood the manufacturing process. Our platform had already been integrated with the historian that was aggregating all of the machine sensor data. We integrated nicely with their maintenance platform. We had established push notifications to the maintenance team when a failure signature was discovered. We had provided everything a company needed to react to the data.
The problem as we soon discovered was not with the data and information we were providing. The problem was in how that data was being acted upon.
Operations was unwilling to take a machine out of production because that would affect the VP over operations bonus. The maintenance team had an ever growing list of repairs that needed to be completed so that the VP of maintenance didn’t miss her bonus. The reliability team didn’t want to disrupt the efficiency of the performance and longevity of the equipment by taking it out of production because… Yep the VP of reliability would take a hit against his bonus. Why would anyone want to work together to fix a very expensive machine when it would be taking money out their collective pockets?
There was the problem and we needed to first understand the problem before we could figure out how to fix it.
In part 2 we will discuss how we transformed this organization into the data driven team they have become today.
If you would like to learn more about InCloud Control and how we can help your company integrate our great predictive analytics solutions into your organization give us a call at:
(404) 316-0082 or email us at email@example.com