Job Description:

I am working in a logistics company that is working with mainly electronics and white appliances producers like Vestel, TeknoSA, LG, Indesit etc. The company’s name is Tezel Logistics and I am currently working in Business Development Department. There are many small and big trucks go out for deliveries every day, so it is important to follow their volume(fullness) as it is costly if the trucks go out empty, and following deliveries to check if they are completed in lead times is also significant to achieve high KPI results.

1)Real-time weather data. For example, you can pull in real-time weather data from tweets from the National Weather Service. And then you can overlay that data with your supply chain operations to see whether a specific tornado or earthquake will affect your operations.

2)Linear programming. R supports linear programming—a mathematical technique that determines the best outcome (like maximum profit or minimum cost). It’s widely used in supply chain optimization for inventory, strategy, logistics, cost optimization, and other scenarios.

3)Geospatial data. Often, a supply chain’s data warehouse doesn’t have geographic data in it. So you have addresses, but you don’t necessarily have the longitude and latitude to understand exactly where things are positioned in space. You can use R to get the geospatial data, and incorporate it into your data warehouse. You can have much deeper analytics across several scenarios.

4)Text analytics. For example, if you have feedback from your customers in your database, you can do root-cause analysis on why they’re returning products.

5)An ensemble of forecasting models. You can use a broad range of forecasting models together in a group—commonly referred to as an ensemble. This way, you can create more accurate forecasts—whether that’s demand forecasting or supply forecasting—than you’d have with an individual model that’s working in isolation.

6)Proactive monitoring of service levels. Imagine you have a warehouse that’s packing products and shipping them to customers. You have a daily goal for how much product you’re supposed to ship. You could implement a process that uses R Services to constantly collect information from that warehouse and forecast whether you’ll meet that demand. And if the target isn’t being met, you can alert a supply chain manager, who can communicate with someone in the warehouse to learn what’s happening from an operational perspective.

7)Association rule mining. In the warehouse, a very common process is to pick a product, pack it, and ship it. If products that people often buy together are close together in the warehouse, the process is more efficient. With R Services, you can use association rule mining to determine products that are most commonly bought together.

8)Inventory optimization. In addition to linear programming, another technique you can use with R Services is clustering. You can look at your patterns of demand and shipping, start clustering, and determine if you should change your inventory mix or inventory strategy based on the actual behaviors that you see in the supply chain.

9)Predictive reverse supply chain models. Reverse supply chain, or reverse logistics, involves any process or management that takes place after a product is sold or delivered, such as when a customer returns a product. You can build and train machine learning models to predict—based on customer, product, geography, and channels—what purchases are likely to be returned. You can understand what those behaviors are, and be more proactive to prevent future returns on purchases.

10)Predictive maintenance models. If your company builds products that are costly or difficult to service in the field, predictive maintenance models are very useful. Previously, you might have waited until something broke down before fixing it. But, you can be more proactive. You can use machine learning to create a model and—based on product information—send someone to do maintenance on it, before issues arise or escalate. Retrieved from : https://www.microsoft.com/itshowcase/Article/Content/865/Top-10-ways-SQL-Server-R-Services-helps-to-optimize-supply-chain-operations