Join Wayne Winston for an in-depth discussion in this video On supply chain analytics, part of Wayne Winston on Analytics.
Well, first, we should probably talk about what a supply chain is. So a supply chain is basically how the stuff gets from where it's made to where it's going. So you think about diapers sold at a Walmart. They are made by P&G somewhere in the United States, I don't know where. But how do they most efficiently get from where they're made to where they're going? So how you can make that process more efficient is the supply chain. So supply chain analytics is using data. To make that process more efficient. So, let's look at some examples. So, let's consider the supply chain in the automobile industry.
So, our car companies have places where they make cars in the United States. They also have plants where they make components that go into the cars, like in a radio, an air conditioner compressor. And basically, if one of those component plants goes down. And causes the plants that make the cars to go down. It might cost the auto companies more than $1 million a day. So you really don't want to see an unplanned machine failure to component plan. And so basically is, one aspect that supply chain analytics is analyzing the data on the machines that produce the components.
So you can decide when you should do preventative maintenance or when you should replace them. Because you don't want an unplanned failure because that can cost you over a million dollars a day. So another example of supply chain analytics would be, installation of an ERP system such as SAP or PeopleSoft. So basically if your company is trying to install that, you would like maybe your goals to get it done in 6 months, I do not know the time frame. So you would like to know what's the probability it will get done on time. And also, what are the critical activities, that you need to monitor, to increase the chances it gets installed on time.
That's an example of project management analytics that applies to supply chains. Another example of supply chain analytics is, where does a company like P&G or an auto company put their plants and their warehouses, their plants where they produce the products. Does P&G need more plants to make diapers, or does an auto company need more plants to make cars? You really have to do an analytic model for that. Production schedule. If you're an automobile company, suppose you're making a two-door, couple of two-door white cars and then you're making some four-door red cars.
What order should you make those cars? You don't want to go from a two door, white to a four door red, because you have to shut down the paint operation, and you have to shut down change the car door operation. So scheduling the order of the production, so that you will minimize the downtime is very important. There's a great IBM ad on the smarter planet campaign, for improving performance of bakery in Europe. So they say hidden connections between the weather and the demand for their products increased profitability to 20%.
For example, they would find, we sell more cakes when it's sunny out. We sale more, sell more pastries when it's rainy out. And so these hitting connections of the words, of the ad, have increased profitability 20%. So analytics is involved in developing that model, and then telling the bakery, how many pastries should I bake on a day, how, when it's rainy out? How many cakes should I bake on a day when it's sunny out?
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