What Is Warehouse Management?

Warehouse management is a key part of any supply chain. It primarily focuses on control and storage of the warehouse materials and associated processes, like shipping, receiving products, transaction, picking and cataloguing, etc. with it. The real-time information and stocks put away are optimized with computer support as well as complex warehousing structures are simplified through different efforts. With the help of computer support it is possible to process receipts of goods faster, issue stock transfer quickly and introduce proper management operations for each individual storage bins. This means a warehouse belonging to several owners with mix pallet of belongings can be slotted easily.

Warehouse management systems are imperative part of processing logistics requirements of a company. Applications of SAP warehouse management not only provides flexible support, but it automatically assist in processing goods and maintaining stock inventories. The technology used for information processing is Auto ID data capture. Other than that there are mobile computers, barcode scanners, wireless LANS and also RFID or radio frequency identification for monitoring effective running of product flow. Data is collected and then synchronized through a wireless transmission device into the central database storage. One can acquire information and useful report of goods statuses in the warehouse using the applications.

Objective of setting up a computer support for management is to keep a tab of the material movements and the changes in the material statuses easily. Not only can one inspect statuses quickly but it is also possible to store and release the goods with proper reports much easily. It is also necessary staging materials in order to supply them to production area. Most organizations need a carefully coordinated report of the shipped goods and when and how sales orders were picked from different areas.

Companies can use such support applications for management of warehouse as standalone systems or they can incorporate modules of ERP systems. In its simplest form, warehouse management systems track products during production and acts as an interpreter between Warehouse management systems and ERP systems. The data tracking and information cataloguing is not limited within the boundaries of warehouse. It extends far wider. For instance, together with management of inventory of warehouse, currently warehouse management involves planning of inventory, management of cost and communication through different IT application, the information about different levels to different departments.

When and how container is stored, loading time and place, unloading time and place are part of the information of warehouse management, which is again part of supply chain management as well as demand management. To a great extent the production management is also dependent on warehouse management. So, management of warehouse starts during the initial planning of product design, container design and other strategies.

Logistics professionals use technologies and different applications as well as strategies in organizations, within their supply chain management model. Within this multi-echelon model of distribution of products to final customer, storage and movement of goods, together with receipts and planning of the movement of goods forms a huge part. It optimizes the overall cost of the transportation and processing of the goods through the levels as well as fulfils the order delivery on time. Complex warehousing facilities may include custom designed areas of storage, automatic warehousing, high rack storage, storage in bulk, etc. Adaptation to this limitless variety of storage bins is necessary when managing warehouse.

Genesis of Modern Logistics

Looking back at the genesis of modern logistics, it is pretty clear that World War II military requirements played a major role in the modern system’s development. Many modern solutions have a military base, as the problems became known with multiple effect due to the very size of the organization. During World War II, the entire effort of supplying the troops with equipment, supplies, and food, and knowing where each unit was located was a massive effort.

Obtaining supplies from various suppliers, and a lack of standardization of terms was causing problems that needed to be solved. A whole new language eventually developed due to these problems. During the war, each branch of military Service had their own names for identical items used by each Service. The problem was multiplied by the fact that various manufacturers also had different names for identical items. If an item was short of supply in one branch of Service, another may have had extras, but the two were unaware of the supply situation.

Following World War II, the Hoover Commission determined that a system of standardized reference must be created so each Service would refer to identical supplies by the same name. This became law and the Federal Catalog System was created and used with success. NATO followed suit, and soon other countries did as well. Improvements were made in the 1960′s with the use of computers and standardized information exchange and computer communication. The system became the key to military logistics, ordering and processing, shipping, and supply management.

The genesis of modern logistics in the commercial world occurred somewhat later, with the inroads to business made via the internet and e-business. There were a variety of standardization systems, within industries and at various manufacturer levels. They did not have the advantage of the military organization to demand conformance at all levels. But, the standardization that did exist went a long way to help with improving supply management in the commercial world.

Manufacturers and users may have different coding systems. The bar codes are a great leap forward for inventory management, but those used by a manufacturer and a seller may vary. The user, or seller, will apply their own Stock Keeping Units (SKUs) to inventory as it is received, to work with their electronic systems of inventory counting. The manufacturer bar codes work for both the manufacturer in their processes, and for the buyer to help with purchasing. What the buyer does after receipt of inventory does not have to coordinate with the manufacturer bar codes. This is different than coding systems used by the military, where matching is advantageous. At buyer level having their own internal bar codes helps with the buying process, especially when receiving identical merchandise from different suppliers who will have different bar codes of their own.

In today’s military, logistics specialists utilize PCs and hand held scanners to track material, equipment, and personnel. Every piece of material has to have a tag, and the improvements over the 1991 war are immense. Items and troops can now be found, and shifted around between Services as needed, quickly. Using radio frequency (RF) and Automated Information Technology only works with a system of standardization. A corresponding system at use in the commercial world can be seen in the method of JIT (just in time) delivery of parts. Being able to obtain materials quickly when needed is the objective of all modern logistics.

The military juggles almost five million items, and this system for logistics is the nation’s largest and most controlled. The best way to control logistics is to control the data as it is entered, at the beginning. Planning and implementing a modern logistics system requires thought and planning from the start. Using standardization also helps to maintain quality control of items brought into the system. This also helps reduce defects at the manufacturer level, by requiring strict conformance to specifications that meet the logistics descriptions for that part.

Even with the best logistics system, communication between humans is essential for practical working of the system. The military again is at the forefront of development, working on compatible catalog systems. A system of item names was created with the ability to be translated into other languages, to afford compatibility between nations. They basically created a parts and supplies dictionary and language of its own to facilitate ordering.

In conclusion, standard logistics data is the genesis of modern logistics. The current and future systems for logistics management depend on the standardization of data. A system that has worked well for the immense size of the military has proven its worth and usefulness. It’s success under pressure has made it a hallmark for other systems of inventory management in the commercial world.

7 Data Warehouse Interview Questions

For those who want to learn the basic concepts of data warehouse and warehousing, what better way than to read about common data warehouse interview questions and their answers? These data warehouse interview questions will attempt to explain standard data warehousing terms and important considerations. Below are 7 data warehouse interview questions you can study.

1. What is a data warehouse?

Among all data warehouse interview questions, this is of course the most basic, yet most important. A data warehouse is an electronic data storage used for supporting intelligent business decisions though the collection, consolidation, and organization of data for future evaluation and reporting.

2. Why is it important to use data warehouses?

The use of data warehouses is important since it greatly aids in the accurate reporting of various chief business processes. They considerably help in integrating and historically storing data from a host of various sources to present a point of truth value regarding business decisions in a given period to enhance an organization’s processes. They are likewise commonly utilized for data mining to aid in predicting forecasts and trends, performance evaluations, as well recognition of patterns among others.

3. What is the standard procedure for creating a data warehouse?

This is also one of the most crucial data warehouse interview questions when learning about data warehouses. The standard procedure used to make a data warehouse is very similar to majority of database projects. Below are the common steps:

  • identification and collection of requirements
  • conducting dimensional modeling
  • development of the data warehouse architecture which include the ODS or Operational Data Store
  • designing OLAP cubes and the relational database
  • development of applications to be used for maintaining stored data
  • development of applications to be utilized for analysis
  • testing and deploying the completed data warehouse system

4. What is a data mart?

In general, a data mart is developed for one main subject matter. A business usually have data regarding different business matters such as for sales, marketing, human resources, or finance contained in one data warehouse but stored in separate data marts.

5. Is there a difference between OLAP and OLTP?

OLAP or online analytical processing is the system used for analyzing and reporting data, while OTLP or online transaction processing is the system utilized for the collection of data to be stored in the data warehouse. While OLAP are intentionally de-normalized to implement faster retrieval of data via SELECT functions, OLTP are intentionally normalized for UPDATE and INSERT functions.

6. What is a dimensional model?

A dimensional model is made up of fact and dimension tables. The fact tables are for storing foreign keys and various transactional measurements from dimensional tables in order to qualify data. Its main purpose is to implement easier and faster retrieval of data. It should be designed according to user requirements to fully support direct and easy access, effortless maintenance, and so that it will be capable of adapting to modifications later on.

Likewise, the design model should be a functioning relational database capable of supporting OLAP cubes for providing analysts with immediate results for their queries.

7. What is the Entity Relationship model?

The entity relationship or ER model is a specific data modeling method where the main purpose is data normalization via the redundancy reduction. A dimensional model differs from the ER model since in a dimensional model; the purpose is the de-normalization of data retrieval processes for faster operations.