Business Intelligence and Data Analytics of Wal-Mart

Business Intelligence and Data Analytics of Wal-Mart

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Institution

Abstract

The report offers data analytics and business intelligence plan for Wal-Mart. In recognition of the competitive nature of the retail industry, Wal-Mart must have accurate and actionable information generated from different data that is collected from the firm to promote its value chain’s activities effective and efficient. The blueprint proposes that the company should implement different data analysis systems such as, Sisense, analytical CRM, and GEP software to help generate information that can help improve business efficiency. Additionally, the management of data analytics and business intelligence data should be guided by the AckOff hierarchy of data. Data should be processed through the five phases to ensure that it is valuable and actionable.

Business Intelligence and Data Analytics of Wal-Mart

In the competitive retail industry business environment, where prompt response o market changes and needs are essential, collection and storage of data regularly are very important. The major requirement in the retail sector is the ability to extract valuable information from the collected data. Attaining such a goal needs significant resources and can take a huge time unless business intelligence and data analytics are used. Nonetheless, it is important to note that some of the information collected and interpreted may be incorrect and misleading. Therefore, to enhance the accuracy of information drawn from collected data, businesses such as Wal-Mart must invest in the Business Intelligence and Data Analytics by deploying updated approaches that generate and deliver the right abilities to meet the wants of a given user group. In this view, this report offers business intelligence and data analytic blueprint to help Wal-Mart attain effectiveness and high performance in its value chain.

Objectives

The main objective of this blueprint is to enhance the automation and improvement of information-intensive elements of business planning, variance analysis, performance management, and root cause analysis. It also aims at promoting automation and acceleration of correct and timely generation of business-unit and enterprise KPIs and dashboards to focus the attention of the company on Key customers and primary channels that drive the business’ desired results. The blueprint also seeks to improve the automation of trade promotion through enhancing its analysis effectiveness to cope with the trade promotion’s volume. His will enable a surgical approach to changing the trade support to customer-based marketing and advertising. Through the implementation of Business intelligence tools, the company will be able to offer comprehensive and standardized historical business facts and information for several enterprise budgets and plans. Besides, this blueprint will ensure that there is a cost-effective and timely monitoring of the company’s business operations through a standardized and dynamic view. It shall enhance the generation of business information and analytics in a manner that suits the utilization preferences of various components of the business.

Benefits of BI at Wal-Mart

The implementation of Data analytics and business intelligence in Wal-Mart will enhance the performance of the business since it has many benefits. These components will integrate relevant operational and financial information from different sources to boost their effective management. Besides, these technologies track several multiple aspects of business performance against the established performance metrics. It tracks customer behaviors and offers insightful information that can improve customer relations with the company. It offers multidimensional analyses of different customer traits to generate informative marketing and stocking information that enhances the efficiency of the business on the customers’ end. Furthermore, it offers a sophisticated decision making support since its information is directly based on historical information of business and decision-makers can make decisions from an informed point of view (Sato & Huang, 2015).

Ackoff’s Hierarchy of Data

Ackoff’s knowledge hierarchy of data also known as Knowledge hierarchy or pyramid illustrates different levels of data including wisdom, understanding, knowledge, information, and data. The pyramid was developed with the focus that managers require not more relevant information but little irrelevant information. Knowledge is illustrated as the know-how resulting from learning from experiences, instructions, and adaptation. Therefore, the process from the data to knowledge and wisdom requires an analysis of different issues, why they occur and how to improve them. As such, there is a need to automate information systems within Wal-Mart to generate information from different data that is collected. This will ensure that people can draw knowledge from this information since the systems only apply the knowledge created by people and do not develop it by itself. Besides, it wisdom of the users of the information will add value to the knowledge acquired to ensure that it is effective and applicable (Sleep et al., 2019). In this view, the Ackoff hierarchy of data will be the primary guide of the implementation framework of business intelligence and data analytics in Wal-Mart.

Business Intelligence and Data Analytics Tools for Wal-Mart

Primary Activities

Logistics and Operations

It is recommended that Sisense should be used in data analytics and business intelligence concerning logistics and operations. The system will intelligently manage Wal-Mart’s logistics and operations with analytics that offer accurate and complete insights into various data sources. The system accelerates the process of decision making with operational analytics. With the system, Wal-Mart will get almost real-time visibility into the vital operational performance indicators and maintain the speed of the business through capturing, analyzing, manipulating, and delivering relevant information for operation. The system can be customized into different categories. In the case of Wal-Mart, the system will be categorized to capture and analyze data of three different but inter-twined categories including inbound logistics, operations, and outbound logistics. The system will capture real-time data of in-progress and inbound inventory data. The data can be analyzed based on the location and number of tracks within the company. A combination of analysis with the outbound logistics will ensure that there is effective management of feet to ensure that there is not the truck that comes or leaves the company’s warehouses empty. Besides, these will ensure swift and fast deliveries to the customers and warehouses. The system will also enhance the analysis and generation of actionable information relating to the operations within the company. It will continuously analyze the activities within the company to ensure that similar operating concepts are applied in the company (Sisense.com). Through comparison to other companies and technologies in the market, Wal-Mart can use the system to identify the best operational practices that enhance efficiency and productivity within the company.

Marketing and Sales

The analytical CRM is the best system that can enhance the business intelligence of Wal-Mart. The system is the most viable because it gathers information about customers, stores, and analyzes it to enhance business operations internally and externally. The analytical CRM always collects huge data and processed to generate valuable insights. These insights help the marketing and sales team to make more informed and strategic marketing plans for Wal-Mart. The sales and marketing departments move from the insights to tangible actions which can streamline business process such as the sales pipeline. The system is the most appropriate for data analytics and business intelligence because it offers a systematic aid to decision making in the business. It aggregates customer information to create customer behavioral knowledge via data analysis and scouting for new sales opportunities. The benefits of this system are that it ensures that Wal-Mart discovers new forecasting and trends. It allows the company to conduct sales trends predictions and forecasts including geographical location and speeds at which they are created. The system not only creates an opportunity to develop effective sales and marketing plans but also informs online and warehouse analytics. The reports that it generates includes, customer analysis, sales analysis, market analysis, and service and channel analysis (Crm.com). These reports will ensure that the management and the concerned users add their value to make them actionable and promote low prices and tailor product categorization based on communities and the layout of the stores.

Services

The analytical CRM software shall be used to ensure the efficiency and effectiveness of services within Wal-Mart. The system tracks the behaviors of the customers and provides analysis to ensure that the needs of the customers are satisfied. The customer satisfaction category of CRM focuses on the collection and analysis of customer information to build customer profiles and enhance understanding of their preferences, values, and determine geographic as well as demographic information. Indeed, being able to acknowledge the customer life cycle based on quantitative data creates a holistic opportunity to understand how to engage leads, convert them to customers, and also retain them. The system generates a service analysis report which combines information from customer sentiments, polls and other channels to identify customer satisfaction rates and perceptions (Crm.com). This allows Wal-Mart to work on its customer service offerings and directing efforts and resources to the right places. This can also allow the management to breakdown the cost of service and work on the balance between revenues earned and the service costs.

Support Activities

It is recommended that Wal-Mart incorporate Sisense software in its operations to help in deriving important information about the support activities of the company. The software enhances the cleaning of data without changing the original data; thus, it facilitates error-free analysis. The system also generates information which users can share to collaborate then, the goals of the company, and KPIs. The system uncovers actionable insights since it analyses the trends of collected data and identifies patterns that can be used by the users to make business decisions and predictions (Selecthub.com). The system can improve the firm’s infrastructure practices since it streamlines business efficiency. However, the system can only generate actionable insights that help managers to draw knowledge from them. It is, therefore, important that the managers add their wisdom, insights and what they know to ensure that the information becomes more actionable. The system will ensure that there is information that can boost the integrations of activities and enhance a balanced scorecard in the value chain.

The system is highly recommended because it is considered as fast and secure. Sisense delivers its analysis fast through single-stack technology which eliminates bottlenecks between data and the analysts. Besides, the system stores data securely using the advanced learning machines which detect anomalies in the data and instantly transmits an alert. These components are very important since there is a need for the data and information generated to be remitted fast and in a secure manner to benefit Wal-Mart’s business. The system has in-chip analytics which combines the smart algorithms, and columnar database as well as a combination of either ram or disk as opposed to disk or ram only. This feature allows the processing of other tasks and improves speed. The software also enhances the ability of users to blend big datasets from various sources promptly. Users can do dicing, slicing, and exploration of data in an accessible interface. After analysis of data, the system organizes it into visual information, for instance, line graphs, pie charts, and bar charts to facilitate easy interpretation. It has machine learning abilities that allow the system to learn previous analysis patterns and actions to provide a suggestion for performing recurring reports (Selecthub.com).

The system will enhance the overall operations of the business, particularly in the support activities because it is effective in collecting and analyzing data on operations of businesses. The system has an API framework that allows users to customize and standardize the platform to meet their business wants to ensure that they attain their expected results out of it. In this view, the software can be customized to gather and analyze information on different components including firm infrastructure, human resource management, technology development, and procurement. The system can offer information concerning different infrastructures of the company visa via its competitors and new infrastructures in the market to enhance efficiency in its management. It shall help create an efficient management process of employees through the collection of their reviews and feedbacks to understand their needs and deliver on them promptly (Kocakoç & Erdem, 2010). Besides, it will enhance the analysis of the compensation strategies of the employees to ensure that they are remunerated well. It shall facilitate the comparison of different technologies in the market to ensure that the most efficient ones are utilized within the company.

For procurement, the GEP software is most appropriate since procurement entails the generation of a huge and specific volume of data. The software offers both ongoing and hoc analytics in different areas. The software is essential because it offers self-service analytics as well as reporting to enable procurement to create reports and analyze different components of procurement. It has predictive analytic features that ensure a forecast of procurement spending and requests based on anticipated changes and previous business history. It also has an offer scorecard that helps monitor the performance of procurement based on the established efficiency and effectiveness metrics. This promotes instantaneous and informed decision-making processes in the procurement sector. The system also identifies risks to the suppliers, including compliance and pricing risk (Gep.com). Therefore, this system will ensure that there is a real-time association between suppliers and store inventories and best company-supplier relations.

Application of Ackoff’s Hierarchy of Data

The recommended systems are only data analytics and business intelligence tools that collect and analyze data of Wal-Mart to help in decision making. However, the generation of actionable reports entails a process that moves beyond these systems. In this case, Ackoff’s hierarchy of order will help the company in converting the information collected into valuable knowledge and actionable information. The data analytic systems and software that are proposed above only offer insights and information that can help the company make critical business decisions. The information generated from the recommended system is often contextualized (Sleep et al., 2019). In this view, it covers the data and information category in the hierarchy of data.

In the knowledge pyramid, knowledge sits above information. In this case, after data has been analyzed and information generated by the system it is upon the users to extract important knowledge from them. Knowledge from the information that is generated by the different systems shall be done by experts in different fields (Sleep et al., 2019). For instance, the marketing and sales personnel shall interpret the information from the analytical CRM to create establish the know-how and convert the information into actionable instructions or plans.

Using the knowledge gained from the interpretation of the generated information from the system; the experts in different departments will develop appropriate and strategic plans to improve on the areas that are identified to have inefficiencies and also strengthen the primary and secondary activities of the Wal-Mart to improve its productivity and profitability (Erickson & Rothberg, 2019). For instance, the logistics and operations personnel use the knowledge gained from the information generated by the Sisense to create operational plans that enhance effectiveness and efficiency in the management of truck fleets and inventories.

The wisdom which is defined as the knowledge that is applied in action is at the peak of the knowledge hierarchy. It is the process through which individuals make comparisons of the proposed actions (Sato & Huang, 2015). Experts at this stage will have to further analyze the proposed actions and determine the reasons why they implement a given action. Besides, the review will determine the best possible actions to be implemented to ensure not only effectiveness but efficiency in different activities within Wal-Mart.

Conclusion

Overall, it is important to acknowledge that the main component of the blueprint which will ensure that there are efficiency and effectiveness in all activities at Wal-Mart is the adoption of Ackoff’s knowledge hierarchy in the analysis and interpretation of data analytics and business intelligence data. The major software that is recommended includes Sisense for support activities, GEP software for procurement activities, Sisense for operations and logistics, and analytical CRM for services, sales, and marketing. These systems will help collect and analyze data that can be used by the management to make key decisions that will improve effectiveness and efficiency. Consequently, the systems will facilitate the creation of actionable plans that can help improve the business operations at Wal-Mart.

References

Crm.com. ‘Analytical CRM Software-Definition and Key features.’ Retrieved from https://crm.org/crmland/analytical-crmErickson, G. S., & Rothberg, H. N. (2019). Big data, knowledge, and business intelligence. In Advanced Methodologies and Technologies in Business Operations and Management (pp. 569-577). IGI Global.

Gep.com. ‘Big Data Analytics for procurement.’ Retrieved from https://www.gep.com/big-data-analytics-procurementKocakoç, I. D., & Erdem, S. (2010). Business intelligence applications in retail business: OLAP, data mining & reporting services. Journal of Information & Knowledge Management, 9(02), 171-181.

Sato, A., & Huang, R. (2015, December). From data to knowledge: A cognitive approach to retail business intelligence. In 2015 IEEE International Conference on Data Science and Data Intensive Systems (pp. 210-217). IEEE.

Selecthub.com ‘Sisense Software.’ Retrieved from https://selecthub.com/business-intelligence-tools/sisense/?from_category=258Sisense.com. ‘Agile to Build Powerful Analytic Apps.’ Retrieved from https://www.sisense.com/why-sisense/Sleep, S., Hulland, J., & Gooner, R. A. (2019). THE DATA HIERARCHY: factors influencing the adoption and implementation of data-driven decision making. AMS Review, 1-19.