Login Services also introduce digital technologies

Introduction

Login service is a logistics provider that recently had different successful marketing initiatives they secure many service contracts with retailers in the UK. To support these changes the organization’s changes in management also change the delivery system and decrease delivery time to provide enhanced quality services. Logi Services also introduce digital technologies like analytics software so with the change in the system many employees need to improve their digital literacy skills. To overcome the situation Logi Services a consultant will be employed to provide training programs for the organization also ranging from technological and human support where cultural aspect processes and information flows of the business system. Now the firm wants to assess the operations of their major partner, customer’s database sales report then they make a database and dashboard where the data is analysed with business intelligence. This report also provides the main features of Power Bi then identify the concept of the fact and dimensions and the relationship between them present a dashboard using intelligence software finally reflects on Ligi Service using Gibb’s reflective framework. In reflection, the consultant emphasizes providing a proper training program to cope with digital technologies and proper use of analytics software.

Part 1

Facts and data table relationships

Here present the relationship between the fact tables and the Dimension tables. Here all their calculations are shown in different units along the columns and details of each order are given in row form.Here is a little table for profit, an integral part of which is shipping cost. Without shipping cost data, the profit dimension will be wrong. Similarly, each sales table has a relationship between profit and shipping cost. All this data creates a primary key with each tables Oder ID, which makes it easy to create a tabletotable relationship(Gupta et al., 2021).

Table 1.1= Data table Relationships

Also, here the table data can be filtered with the clickers, which have created a relationship with one another. In this way, the data of all the tables is being filtered by the order ID.If there follow and analyze the first order id, then know that this order resulted in £261.54 worth of sales, their shipping cost was £35 behind this sale, and their profit was £213.25. By reviewing these three orders, it can be understood that the orders that had higher profits were on their highpriority list. By reviewing these three orders, it is clear that the orders that had higher profits were on their highpriority list. Also, after focusing on discounts it scaled up and down according to customer orders, i.e. if someone buys more units, the perunit discount is higher, and it all depends on how much they are buying. Almost of their maximum customers belong to the corporate field, from which they derive a large portion of their profits(Kazancoglu et al., 2021).

Analyze Organizational Performance: The Essential Guide

KPI means Key Performance Indicator. It shows how a company improves its sales rate. If analyze the Graph, there can easily measure its KPI. “KPI” generally means, if a company targets to sell 1000 units this month, then it has to sell 250 units in 1 week, if it sells 500 units in 3 days, then it means that it is sticking to its sales target. Here will analyze the graph and see how their KPIs are and how the company is performing. In the case of order No. 32, it was an order from the province of Alberta, totaling 24 units, their profit excluding shipping cost and other expenses was £1748.56. Then if review order number 96, can see that it was an order from Manitoba Province, in this order they sold a total of 37 units, and after deducting all expenses, their profit was about £1228. Finally, if looking at order no 548, can see that in this sale they sold a total of 29 units and made a profit of around $50, after deducting all costs. In January 2009, their sales were 5552 units, where their profit was £62256. In the following month of the same year i.e. in February, their sales were 4027 units, from which their profit was £30422. Again if consider all aspects of March 2012, can see that their total sales in this month were 4837 units from which their profit was £37786.

Figure 1.1= Dashboard Analysis

A rough analysis shows that the scale or graph of their profit was quite good, but due to some of their associated costs, the profit was affected. For example, their profits are higher on those orders that can be delivered by truck, which can be delivered to the customer in a much faster time, thereby increasing the profit margin(Awan et al., 2021).  They should look into their delivery service. Then it can be seen that there are some financial issues in their region, for example, their orders are high in some specific regions, and they should increase the quality of their products in these places and have the highest customer response so that the customer shows interest in buying their products. As a result, their product will sell more and KPI will also increase. Looking at this database of their sales, it can be understood that the current performance of their company which we usually consider as KPI is in a good position, but if pay attention to some things, their performance can be expected to be better(Kandula et al., 2021). For example, to ensure the maximum response of the customer, to ensure the quality while reducing the shipping cost so that the customer is 100% satisfied, then to do marketing especially in some specific regions (like they can organize a unity seminar there). Focusing on these will increase their key performance data KPIs(Choi et al., 2022).

Part 2

The importance of integration of data analytics software

Analyzing data collections to identify trends and make judgments about the information consumers represent is known as data analytics (DA). Data analytics is frequently carried out with the use of specialist hardware and software(Song et al., 2021). In order to help businesses make better business decisions, data analytics tools and methodologies are widely employed in the corporate sector.It is hard to exaggerate the value of technology in data analysis(Aspin, 2021). The software will either enable a firm to save money or help them to make more. This is so that Logi Service may examine the company utilizing these technologies(Kumar et al., 2021). Logi Service can combine all the sets of data from many economic areas to produce findings that can guide us in choosing the best course of action in any given circumstance. Without this software, a corporation would have to carry out all tasks manually and rely heavily on guessing(MoraArciniegas and Luna, 2022).

Data transfer

The capability of transferring data via import from input materials to the application. The first step in using a search generator to examine the data is to get it. The essential data will then be automatically matched by the query builder, saving the end user considerable time(Aspin, 2021).

Data visualization

Data analysis may be used to spot some patterns and trends. Through graphical presentations, summaries, and dashboards, the data analysis software provides it a simple to examine and comprehend data(Laurila, 2022).

Basic data analysis

To create valuable information from the raw data, software solutions include statistical analysis and simulation models. One may fiddle with the summary to make one’s own areas of concern and see graphs automatically based on the parameters they choose for the variables they are attempting to assess(MoraArciniegas and Luna, 2022).

Explanations of Power Bi 3 Main features

Power Bi is a collection of intelligent software services where a collection of software services provides application and data connection which is used for business intelligence in this platform businesses can gather their data from various sources into a single data set and the software also uses cloud computing for these operations(Khan et al., 2022). Power Bi also use data set to present data visualization, inspections, and analysis and produce as shareable reports, Dashboards, and application. Power Bi has desktop and mobile apps to use and access these services(Box, 2020).

Power Bi implementations can be done in the cloud or onpremises. It may also import information from its database and data sources. It also collects data from cloudbased big data where they find a large amount of necessary data and the data from excel files and other hybrid sources in the business environment. Power Bi is the pioneer in business intelligence tools that also work very efficiently and effectively. This application allows users to aggregate data from many sources, create dynamic dashboards, analyze data, prepare enlightening reports, and share it with other people(Xiang et al., 2021).

Interface

Range of Attractive Visualizations

Visualizations are vital to Power BI because they provide a visual representation of data. It displays reports and dashboards with a wide range of complex graphics where one can represent their data with basic and sophisticated representation and a collection of original visuals available in this application(Grammenou, 2021).

Customizable Dashboards

Dashboards are collections of graphics that offer illuminating or practical datarelated information. Power BI dashboards frequently use tiles that represent different visualizations. Each page is a separate report. The dashboards provide sharing and printing options(Vásquez et al., 2022).

Flexible Tiles

To provide a clearer view, each instructional graphic is meticulously divided into tiles. Both the shape and size of these tiles are adjustable. They can also be positioned on the dashboard however the user sees fit(Nummela, 2021).

Workflow

Informative Reports

Power Bi provides informative reports where that represent business subjects and represent facts with consecutively and detailed drawings of the important interface from the data(Vásquez et al., 2022).

DAX Data Analysis Function

Power BI offers the Data Analysis Expressions (DAX) functionality. Data may be subjected to certain procedures particular to analytics utilizing analysis functions, which are preset codes(Chen et al., 2021).

Query environment

Datasets Filtration

A dataset is a group of data that has been created by fusing information from many sources. Many other visualizations may be created using the datasets. A dataset is made up of data that has been aggregated from various sources, such as several Excel worksheets(Bag et al., 2021).

Navigation Pane

Navigation bar in the software has a function for presentations, infographics, and databases. An organization may quickly navigate between their datasets, open dashboards, and open reports while working with the conclusion(Bag et al., 2021).

Conclusion

As a result of many recent successful marketing campaigns, the logistics company Logi Service was able to obtain numerous service agreements with UK merchants. To support these modifications, the organizations management adjustments have also resulted in a delivery system change and a reduction in delivery time, resulting in the provision of services of higher quality. Because of the system change and the introduction of digital technologies by Logi Services, such as analytics software, many workers now need to strengthen their digital literacy. To resolve the issue, Logi Services will hire a consultant to provide training programs for the company that covers both technology and human resources, as well as culturally relevant business system procedures and information flows. The company is now looking to evaluate the performance of its principal partner, customer database, and sales report, so they create a database and dashboard where the data is analyzed using business intelligence. This report also lists the key components of Power Bi, after which it defines the terms fact and dimension and their relationships and presents a dashboard created with intelligence software before reflecting on Ligi Service using Gibbs reflective framework. In hindsight, the consultant places a strong emphasis on offering a suitable training program to deal with digital technology and appropriate usage of analytics tools. Using Power Bi Logi limited get their analytics dashboard and navigate the required information from the CSV files they can analyse the data then evaluate the data also take a proper action plan.

Reflective statement

Gibbs’ model of reflection: In Gibbs reflection paradigm, there are six stages: description, feelings, evaluation, analysis, conclusion, and action plan. Im using Gibbs concept of reflection to describe how the Logi Service is reflected.

Description

I can see that Logi Service offers logistical services for SME organizations and the company has been successful in gaining several support contracts with reputable UK stores due to their effective marketing strategies. By doing this marketing initiative the company get a huge number of customers and maintains the company’s use of automation in their services. I suggest providing proper training to the employees and utilizing the technology and human resources effectively.

Feelings

I think the company need to use effective training strategies and train human resource to speed up its delivery system using digital technology and use analytics tools and cuttingedge online interface for direct and direct customers. At the time, I was in a good mood that I thought about providing the training program. It was crucial to the organizations study of the data, but it was also very difficult for the staff to understand when training is employed.

Evaluation

At the time, I didnt believe the issue had been resolved entirely. I need to start training without finishing all the components. But I started to feel much better after learning about another trainees firsthand experience. I propose outlining current practices to offer a suitable training curriculum. To respond to the new trend, many employees will need to improve their digital literacy skills.

Analysis

In hindsight, there are a few things I would change. After the session, I should have trained HR and made my proposal. Additionally, I ought to have been pushier when I offered the training so I could stay with the company. However, the event helped me understand how important it is to develop a rapport with the technology involved in employing automation with software and online services.

Conclusion

Ill make sure to train the human resources department. During this time, I am collaborating with a variety of training initiatives, and I want to provide each one with a specialized education. I have already provided the organization with useful technology support, and I have created a teamteaching program for the following phases.

Action plan

In future, I initiate to become the Logi Service more successful to provide appropriate training to their employees and make them more efficient and expert in these specific fields they can handle new software expertise on data analysis and this way they use information from their business perspectives.

References

MoraArciniegas, M.B. and Luna, G.A.T., 2022, March. Paper Smart Cities data analysis with Power BI and R. In 2022 IEEE Global Engineering Education Conference (EDUCON) (pp. 18241828). IEEE.

Aspin, A., 2021. Introduction to Power BI Themes. In Pro Power BI Theme Creation (pp. 19). Apress, Berkeley, CA.

Laurila, R., 2022. Development process decisions for Power BI analytics as part of a SaaS product.

Box, A.,2020 Up and Running with DAX for Power BI.

Grammenou, S., 2021. Exploratory Data Analysis and Visualization with Power BI & KNIME.

Vásquez, R.A.D., Espinoza, J.L.A. and Cabrera, M.A.C., 2022. Power bi comoherramienta de apoyo a la toma de decisiones. Universidad y Sociedad, 14(S3), pp.195207.

Nummela, R., 2021. Liiketoimintatiedonanalysointi ja visualisointi Power BItyökalulla.

Chen, Y.T., Sun, E.W., Chang, M.F. and Lin, Y.B., 2021. Pragmatic realtime logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0. International Journal of Production Economics, 238, p.108157.

Bag, S., Luthra, S., Mangla, S.K. and Kazancoglu, Y., 2021. Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance. The International Journal of Logistics Management.

Bag, S., Dhamija, P., Luthra, S. and Huisingh, D., 2021. How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID19 pandemic. The International Journal of Logistics Management.

Maheshwari, S., Gautam, P. and Jaggi, C.K., 2021. Role of Big Data Analytics in supply chain management: current trends and future perspectives. International Journal of Production Research, 59(6), pp.18751900.

Kumar, A., Shrivastav, S.K. and Oberoi, S.S., 2021. Application of analytics in supply chain management from industry and academic perspective. FIIB Business Review, p.23197145211028041.

Choi, T.M. and Siqin, T., 2022. Blockchain in logistics and production from Blockchain 1.0 to Blockchain 5.0: An intrainterorganizational framework. Transportation Research Part E: Logistics and Transportation Review, 160, p.102653.

Awan, U., Kanwal, N., Alawi, S., Huiskonen, J. and Dahanayake, A., 2021. Artificial intelligence for supply chain success in the era of data analytics. In The fourth industrial revolution: Implementation of artificial intelligence for growing business success (pp. 321). Springer, Cham.

Kazancoglu, Y., Pala, M.O., Sezer, M.D., Luthra, S. and Kumar, A., 2021. Drivers of implementing Big Data Analytics in food supply chains for transition to a circular economy and sustainable operations management. Journal of Enterprise Information Management.

Gupta, A., Singh, R.K. and Gupta, S., 2021. Developing human resource for the digitization of logistics operations: readiness index framework. International Journal of Manpower.

Kandula, S., Krishnamoorthy, S. and Roy, D., 2021. A prescriptive analytics framework for efficient Ecommerce order delivery. Decision Support Systems, 147, p.113584.

Song, H., Li, M. and Yu, K., 2021. Big data analytics in digital platforms: how do financial service providers customise supply chain finance?. International journal of operations & production management.

Khan, S.A.R., Piprani, A.Z. and Yu, Z., 2022. Supply chain analytics and postpandemic performance: Mediating role of tripleA supply chain strategies. International Journal of Emerging Markets, (aheadofprint).

Xiang, L.Y., Hwang, H.J., Kim, H.K., Mahmood, M. and Dawi, N.M., 2021. The use of big data analytics to improve the supply chain performance in logistics industry. In Software Engineering in IoT, Big Data, Cloud and Mobile Computing (pp. 1731). Springer, Cham.

Pujiarto, B., Hanafi, M., Setyawan, A., Imani, A.N. and Prasetya, E.R., 2021. A data mining practical approach to inventory management and logistics optimization. International Journal of Informatics and Information Systems, 4(2), pp.112122.

Jintana, J., Sopadang, A. and Ramingwong, S., 2021. Idea selection of new service for courier business: The opportunity of data analytics. International Journal of Engineering Business Management, 13, p.18479790211042191.