Transportation management in Big data using SAP With the rapid development of society, enterprises are facing increasing pressure. Companies need to reduce costs, increase innovation, improve customer service and improve response. SAP Supply Chain Management (SAP SCM) enables collaboration, planning, execution and coordination across the supply chain network (Nissen and Lameter, 2001). SAP SCM is a member of the SAP Business Suite. The kit is modular and can be used with other SAP and non-SAP software. SAP SCM enables organizations to complete basic business processes in a unique way. Organizations and departments in all areas can deploy SAP Business Suite software on their own schedules to address specific business challenges without the need for costly upgrades.

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The importance of Supply chain:

Today, the Supply Chain has become a key area of competition among companies, and it also means that companies will face a series of challenges. These have motivated companies to continually accelerate their pace, launch personalized and configurable products, confident commitment, on-time delivery, and respond quickly to changing customer needs, hobbies and the external economic environment (Reimann and Ketchen, 2017).

There are many questions about the supply chain. For example, companies should respond quickly to demand without having to have large inventories. The synergy between the company and the supplier goes smoothly, so that the operation plan can be changed quickly and at any time. In addition, while maintaining service levels, enterprises also need to minimize existing inventory, fixed assets, and transportation. Then companies will have to bring new products to market faster. And in the case of a best-selling product, it is necessary to speed up the process to meet higher requirements. In addition, the supply chain is at full capacity, turning to Internet-based electronic sales and facing end customers. Finally, companies should also use a powerful data system to ensure supply chain functions to provide customers with a richer choice of space, faster and more reliable production and delivery, thus making them stand out from the competition. In addition, companies must have the ability to meet the needs of all parties, even if the supplier is unable to supply.

Supply chain in different organisations:

Companies must go beyond traditional supply chains. The original linear information processing method between partners is no longer suitable for the development of new and new economy. This type of information processing is too slow, too inaccurate and costly, making it easy for companies to eat away from other competitors with a collaborative supply chain. This shows that companies need to create a collaborative environment, that is, to establish a supply chain network. In this supply chain network, suppliers, manufacturers, distributors, and customers can dynamically share information, collaborate, and move toward common goals.

To help companies create a collaborative supply chain network, SAP offers a powerful, fully integrated SAP Supply Chain Management (SAP SCM) solution. Its comprehensive capabilities help companies manage the entire supply chain network: from supply chain planning to material inquiries, from demand planning to product distribution.

By using SAP SCM, companies and partners can capture customer needs in a timely manner and share information throughout the supply chain. Companies can accurately predict the likelihood of inventory shortages and replenish them in a timely manner to avoid any delays that may result, ensuring synchronization of planning and execution from start to finish.

For example, IMG China has always been at the forefront of corporate IT technology, providing companies with the latest consulting services and landing platforms. IMG China has always been committed to truly building Chinese enterprises through information technology, and can truly expand sales, effectively reduce operating costs and improve operational efficiency (Polyanskii, 2019). IMG China has not allowed it to easily undertake IT projects and make any violations of customer interests for short-term benefits.

A relational database is used to express the technology of storing data warehouses, called ROLAP. Conversely, the technique of storing data warehouses in cubes is called MOLAP (Eavis and Taleb, 2013). The technology that uses both relational databases and cubes to store data warehouses becomes HOLAP. According to the survey statistics of relevant institutions, most of the established BI projects use ROLAP technology. A database model that follows a certain norm of fact tables + dimension tables is called the Multi Dimension data model, or MD model for short.

Support for ad hoc analysis and template analysis:

Ad-hoc

Pre-design

Advantage

1. It is convenient to conduct guessing and verification analysis, which greatly improves the interactive ability of report analysis.

2. Flexible and simple operation, guided operation, no need for report design operation.

3, can meet the needs of burst data analysis.

4, no need to write SQL statements, suitable for business personnel to operate.

1. Meet the preset analysis report business 2. The report form is strong, providing a graphical design interface to fully meet various individual needs.

3, can arbitrarily set a variety of operational relationships, including complex mathematical statistics, function analysis. Can design arbitrarily complex report styles.

Disadvantage

1. The report presentation form is not rich enough, the layout editing ability is weak, and the report format cannot be improved.

2, the index calculation ability of the table is relatively weak

1. All template analysis needs to be defined in advance, the operation is relatively complicated, but has powerful layout editing ability.

2. It is difficult to respond quickly to sudden demands.

Support OLTP reports and OLAP reports

MOLAP cube model, ROLAP star model, snowflake model, etc. All OLAP databases built are in compliance with the standard data model (Zhang et al., 2018). Different analysis software can implement standard analysis functions. That is, the front-end analysis and display tool software is interchangeable. The difference is only different software cost performance, display capabilities, performance and so on. In addition, because OLAP conforms to a unified model, it is possible to generate reports directly using interface operations without coding.

For example, Adidas’ “Golden Compass”. After the “emergency measures” for initial price reduction, discounting, etc., based on the external environment, consumer research and store sales data collection and analysis, it became the “golden compass” that brought Adidas on the right track (West et al., 2019). Every day, the company collects sales data from stores and uploads them to Adidas. After receiving the data, Adidas integrated and analyzed the data and used it to guide the dealers to sell the goods. Studying this data allows Adidas and dealers to more accurately understand local consumers’ preferences for the color, style, and function of their products, and to know what price-priced products are more acceptable.

The big data of logistics companies has two major values:

On the one hand, optimize logistics companies’ own operations and resolution plans; on the other hand, logistics big data can be used in non-logistics areas, such as credit reporting and financial utilization.

The first aspect is to optimize the logistics company’s own operations and resolution plans.

The data of the logistics enterprise includes data such as transportation, warehousing, distribution, packaging, and circulation processing.

For logistics enterprises, through the analysis of big data, it can help improve the efficiency of business management, reduce the logistics inventory rate, improve the processing efficiency of goods, transportation efficiency, delivery accuracy and so on.

In the second aspect, logistics big data can be used in non-logistics, especially for credit reporting and financial use.

Taking the logistics delivery order as an example, we can implement a simple data analysis to realize the customer image as the root data of the credit model. There are at most two types of information on logistics distribution orders.

SAP Simple Logistics is also known as SAP S / 4 HANA Enterprise Management. It includes all key modules in the SAP ERP Business Suite – Materials Management, Supply Chain, Demand Planning, Purchasing and Purchasing, Contract Management and Manufacturing.

The following business processes can be managed using SAP S / 4 HANA Enterprise Management to improve the performance and efficiency of all of these processes

Inventory Management – SAP S / 4 HANA Enterprise Management provides a simplified data model that maximizes throughput and flexible analysis.

Purchasing – With SAP S / 4 HANA Enterprise Management, you can increase the efficiency of Ariba network integration from purchasing to payment processes, new analytics applications and spending KPIs, A orders and IV orders.

Material Requirements Planning – You can perform fast MRP runs and new working models of MRP controllers based on decision support.

Order Management and Billing – With S/4 HANA Enterprise Management, you can perform end-to-end order-to-cash processes and take action on any anomalies to resolve problem anomalies, reduce TCO due to data model simplification, and support the latest version of the business Features such as FSCM Credit Management, GTS Foreign Trade, SFIN Income Accounting and new analytics features.

Analytical Dataset:

Transportation management has been explained with great depth in above sections. We have a basic understanding of what transportation management is, now in this section, we will learn why SAP is essential for transportation management datasets. We will learn what kind of facilities and features SAP can provide for understanding the datasets better.

Use of SAP for Transportation management Datasets:

Uses of SAP for TM datasets can be divided into 5 main points:

Precisely forecast and display resource supply & demand
Improve the sites and dates for resource acquire and return
Dodge or improve the repositioning of empty resources
Assimilate with a fundamental logistics system, for example SAP Transportation Management
Acquire comprehensive data and KPIs about distribution containers and additional resources

Functional capabilities:

Track and observe transportation resources
keep an observation of the on-going and upcoming status of your transportation details and resources related to their category and position. And, this can also mean that you can use it for observing resource-related key performance indicators.

Predict supply and demand
Use improved computation models to produce precise predictions of your resource supply and demand condition.

Increase transportation resource development
Mimic situations to correct and avert inequities in the supply and demand of transportation resources, in addition to that also benefit your planners in creating more knowledgeable decisions.

Improve empty resource movement
Discover the ideal locations and times for the pick-up and return of all the transportation resources.

Set up event-triggered alerts
Obtain comprehensive alert material and timely cautions about serious resource circumstances.

Dashboard:

Technical capabilities:

Databases

SAP HANA Platform Edition 1.0, SPS 10
SAP HANA Rules Framework 1.0, SPS 06

Web Browsers

Mostly Mozilla Firefox, Apple safari, Google chrome and most obviously Microsoft internet explorer are used.

Figure 1- transportation manager’s KPI

SAP Transportation Management application

Unite orders and make the most of the return on your transference spend. Predict demand and delivery volumes precisely to perfect transportation planning. Improve freight and logistics management to increase real-time reflectiveness into worldwide transportation and local shipping through all transportation ways and industries.

Increase business efficiency

Accomplish transportation supplies with more effectiveness and less redundancy via computerisation and electronic association from order access to settlement.

Improve end-to-end visibility and service

Helps us lower the expenses on expedites and especially with automated pursuing and findings of cross-system documentation flow, rate negotiation of data- driven processes and lastly freight consolidation.

Improve cash-flow for freight transportation

Reduce unplanned overcharges and eliminate invoice errors by settling costs accurately and automating accrual generation, auditing, and charge tracking.

Normalize logistics procedures and operations

Supply a steady logistics involvement. Unify rate and data management with a shared platform that is easy to assimilate, cover, deploy, and contact.

Quicken decision-making with the help of real-time vision

Supply flexible broadcasting to measure all freight charges. Estimate transportation brainpower with graphical and collaborating dashboards consecutively on SAP HANA.

Figure 2- freight order

Figure 3- victorian ambulance transportation

Figure 4- ambulance transportation chart

This data gives us the information about how many patients were transferred to the hospitals by all the working ambulance services. It can also be added into the data as compensable which technically means that it was not funded by the health department of Australia, or a patient or any 3^rd parties like hospitals, department of veterans’ affair etc. We can also include member subscription scheme and transport accident commission as a 3^rd party. These parties are responsible for fees and we can also call it community service obligation which is not fully yet partially funded by health department for even pensioner or for a health care card holder.

Figure 5- suburb buses transportation

The given map is made public by the australian government to help people of australia in assisting with making plans and developing the enquiries in the city which is called Logan. It shows us key maps which are taken from the current versions of the city’s Planning scheme 2015, which also includes zones and precincts of those zones, in addition to that it also includes local plans with local plan precincts. We can also see overlays, LGIP which is known as local government infrastructure plan

Figure 6- long distance corridor

Figure 7- axial presentation of the long distance corridor

References:

[1] Data.gov, https://data.gov.au/dataset/ds-vic-6f02113a-908e-42f8-bc08-1724652bde49/details?q=transportation

SAP transportation management, https://www.sap.com/products/transportation-logistics.html

[2] Talend. (2013). How Big Is Big Data Adoption? [Online]. Available: http://www.talend.com

[3] Nissen, V. and Lameter, F. (2001). Supply Chain Management mit SAP. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, 96(1-2), pp.71-73.

[4] Reimann, F. and Ketchen, D. (2017). Power in Supply Chain Management. Journal of Supply Chain Management, 53(2), pp.3-9.

[5] Polyanskii, A. (2019). On simultaneous approximations of [IMG align=ABSMIDDLE alt=$ ln 3$]tex_sm_4783_img1[/IMG] and [IMG align=ABSMIDDLE alt=$ pi/sqrt{3}$]tex_sm_4783_img2[/IMG] by rational numbers. Sbornik: Mathematics, 210(4).

[6] Eavis, T. and Taleb, A. (2013). Minimizing the MOLAP/ROLAP Divide: You Can Have Your Performance and Scale It Too. Journal of Computing Science and Engineering, 7(1), pp.1-20.

[7] West, A., Schönfisch, D., Picard, A., Tarrier, J., Hodder, S. and Havenith, G. (2019). Shoe microclimate: An objective characterisation and subjective evaluation. Applied Ergonomics, 78, pp.1-12.

[8] Zhang, Y., Zhang, Y., Wang, S. and Lu, J. (2018). Fusion OLAP: Fusing the Pros of MOLAP and ROLAP Together for In-memory OLAP. IEEE Transactions on Knowledge and Data Engineering, pp.1-1.