Tableau: What are the data challenges in manufacturing?
Dan Meier, Manufacturing IT Expert: Manufacturers in general have a lot of data but they don't use it very effectively. Tableau has a terrific environment to be able to make information out of that data.
Tableau: What kinds of data are involved?
Dan: Data is used in many different areas. We use data from the perspective of monitoring the flow of work in progress through the manufacturing area. We monitor the time at step, individual steps, and monitor whether a step is taking more or less time over time. We monitor how many orders we get from customers and the order flow rate. We monitor the rate at which we ship orders to customers and the revenue that's generated from that.
So it really permeates every part of the commercial perspective of the business, but we can also look at it from a process engineering standpoint as well. We can look at scrap. We can look at improving yield within the manufacturing environment. And we can dig down deeply into the data to make associations that help us determine root cause for a lot of the issues.
Tableau: What does Tableau help you do with that data?
Dan: Tableau really allows us to be able to get a good picture about the causes, the problems, and allows us to quickly identify and correct them to be able to improve our manufacturing processes.
Tableau really allows us to be able to get a good picture about the causes, the problems, and allows us to quickly identify and correct them to be able to improve our manufacturing processes.
Tableau: Does any philosophy influence your analysis of data?
Dan: We use lean manufacturing principles. These are very key within our environment. To be able to perform the analysis on the data, to be able to look at problems, and again one of the core competencies of Six Sigma is being able to determine root cause and to be able to address root cause. Tableau is really very, very effective for that.
Part of the guiding principle of the ISO9001 quality system within manufacturing is that everybody needs to understand the progress of manufacturing, how you're doing against your goals. And Tableau for us was a key part of not only managing goals but also managing our performance against the goals. So ultimately, we wanted everybody in the facility to be able to have access to that kind of information.
And so everybody then begins to not only work with the same sets of data, a single source of truth, but also begins to see the possibilities and options that they can have through exploring this information, looking at the data in ways that they were never able to before.
Tableau: How often do you work with data?
Dan: We slice and dice the data all the time, and through slicing and dicing the data being able to turn it upside down on its head we frequently find insights.
Tableau: Why are self-service analytics so important?
Dan: If we have 100 engineers in manufacturing, maybe 20 of those engineers know how to write a SQL query, but maybe only three or four or five of those engineers have access to the database to be able to get the information that they need.