In a previous article, we explained how companies can build BI projects from 0-1.
Article Guide: BI System Construction Guide: Analysis of the Whole Stage of Construction from 0-1! The first task when starting a BI project is to conduct a requirements study. Companies need to carefully understand the specific use cases they plan to build for their BI project, as this is critical to the success of the project. In short, it is about figuring out what business and management problems the BI project aims to solve, and only with a clear understanding of this aspect can the BI project be successful.
So what are the specific business scenarios that BI can be applied to in enterprises?
Considering the size and business differences of different enterprises, as well as the fact that they usually have strong industry attributes, we will focus on four main industries, which are typical BI business application scenarios.
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Among the many industries, the retail industry has the most abundant business forms, including department stores, large comprehensive supermarkets, convenience stores, specialty market (theme**) specialty stores, shopping malls and warehouse shopping malls. However, no matter what kind of business is operated, it is inseparable from the four elements of people, goods, fields and money. Therefore, the BI application scenarios of the retail industry can be summarized into five aspects: goods, stores, inventory, activities, and members.
Scenario 1: Fresh food sales management
Because fresh goods often have a short shelf life and varying standards, a lot of manpower is required to maintain and manage the shelves. Deciding when, where, and what operational strategy to adopt is a test for fresh sales managers. Once the wrong decision is made, it can lead to huge losses. Therefore, effective loss control is regarded as the core task of fresh sales management. If not properly controlled, not only will gross profit be lost, but sales opportunities will also be severely impacted.
The following figure shows the fresh inventory stop-loss scheme developed by BI applications in the retail industry with the help of FineBI, which first guides the purchase SKU and quantity through store customer flow** and commodity sales**, and then guides the reduction of inventory loss through the whole process of commodity point-to-point quality inspection, commodity inventory early warning, dynamic clearance and commodity inventory stop-loss analysis and review.
Scenario 2: Differentiated marketing of members
For retail enterprises, when sales goals are difficult to achieve, they usually adopt the method of developing multiple marketing campaigns to increase the repurchase rate of members and increase the average customer value, so as to achieve the ultimate goal. However, in this process, how to maximize the value of activities has become a common problem faced by retail enterprises. One of the most effective ways to solve this problem is to drive the growth of affiliate sales through differentiated affiliate marketing.
The diagram below illustrates the membership differentiation dashboard developed by BI applications in the retail industry with the help of FineBI. The business staff first identifies different types of members by classifying and screening them, and monitors them. Then, by analyzing the consumption habits, preferences and values of members, we can determine the target group of marketing activities and develop differentiated marketing strategies. Finally, monitor activity and evaluate its value in order to optimize your membership structure.
Scenario 3: Convenience store automatic fulfillment
The core competitiveness of the retail industry is mainly reflected in the management ability of the first chain, and the optimization focus of the first chain usually includes convenience, accurate adaptation of goods and destocking. Among them, ** is a very critical link. The strategy of most retail businesses is usually traditional and simple, relying mainly on human experience, especially some convenience store chains. However, due to the small space, the large number of SKUs, the small number of salespeople and other reasons, the traditional empirical method can no longer meet the needs of large-scale development. In order to solve this problem, the BI automatic distribution application came into being.
The diagram below illustrates the automated fulfillment kanban developed by FineBI for BI applications in the retail industry. The automatic packing application first rejects the eliminated goods through the distribution task analysis model, and then enters the indicators and sets the calculation logic behind them in the automatic packing form according to the distribution association analysis model and the automatic distribution model. Eventually, the system will automatically send a pop-up reminder when the item is out of stock, based on the recommendations**.
The financial industry covers many subdivisions such as banking, insurance, trust, ** industry, and leasing industry. In different types of financial institutions, BI is widely used, including general comprehensive risk management, bank branch business volume analysis, institutional user map, roadshows, etc.
Scenario 1: Comprehensive risk management
Risk management is an indispensable task for all types of financial institutions. Due to its complex trading scenarios and wide coverage, the financial industry faces more risks than other industries. At the same time, with the rapid development of science and technology, various new businesses have emerged in financial institutions, such as Internet finance and electronic payment, which have also brought new challenges. Therefore, in order to minimize or avoid risks, businesses need to conduct comprehensive risk management.
The diagram below illustrates the BI application in the financial industry with the help of a comprehensive risk management platform developed by FineBI. Through this platform, risk management personnel can easily access a central platform to centrally monitor all the metrics that need to be controlled and the risk profile of different lines of business. This provides a more efficient risk management tool for enterprises.
Scenario 2: Loan overdue monitoring and early warning
In the market economy environment, banks, as the main force of financial institutions, an indispensable part of their business is to provide loan support for individuals and enterprises. To ensure that the loan overdue rate is within a safe range, banks need to conduct strict loan overdue monitoring.
The diagram below shows the BI application in the financial industry, which is developed by FineBI to monitor and warn of overdue loans on the mobile terminal. Bank leaders can pay attention to the overall fund arrival rate and customer arrival rate of the month in real time, and once problems are found, they can quickly locate the front-line business manager and supervise them in time. In addition, the app can compare the current month's data with recent months to see if risk management has improved. This provides a convenient and efficient means for banks to better monitor and manage loan overdues.
Manufacturing is a huge industry, including electronic and electrical, energy and chemical industry, machinery and equipment, food, textiles and other fields. However, no matter what kind of manufacturing industry, they are all facing the three core links of production, sales and ** chain. Therefore, the main focus of BI applications in the manufacturing industry is on front-line production, production equipment, material procurement, inventory management, and sales management.
Scenario 1: Production management
Production is the core of manufacturing enterprises, and production management directly affects the manufacturing cost of enterprises, which is related to the cost advantage, competitiveness and profitability of enterprises, as well as product quality and corporate brand reputation. Therefore, production management plays an important management role in manufacturing enterprises. In general, production management includes the query of basic production data and comprehensive analysis of production, such as production workshop analysis, production cost analysis, production product analysis and production cockpit.
The diagram below illustrates the BI application in the manufacturing industry, the production cockpit developed with the help of FineBI tools. The production cockpit is a form of management visualization, which helps enterprises monitor abnormal conditions and ensure the stable operation of production by visualizing and analyzing various production data and indicators in the BI system. This visualization tool helps companies gain a more comprehensive, real-time view of production so they can make more accurate decisions.
Scenario 2: Inventory management
For manufacturing enterprises, inventory has an important impact on the external operation of the entire ** chain and the internal operation of all businesses within the enterprise, so it is essential to effectively manage inventory. In general, enterprises need to use BI tools to understand the overall current inventory level through inventory counting and variance analysis, and then understand the current inventory structure through change analysis and ABC analysis, implement slice management, and finally optimize and improve the inventory management process by reducing unsalable, improving turnover rate, and carrying out early warning management.
The diagram below illustrates the BI application in the manufacturing industry, with the help of the FineBI tool developed for inventory structure analysis Kanban. Stakeholders can visualize the overall inventory structure as well as the inventory structure analysis for each product. This visualization tool helps business personnel to get a more comprehensive and real-time view of inventory so that they can take targeted actions to optimize and improve.
The medical industry is an important industry related to people's livelihood, and hospitals, pharmaceutical companies, and medical device companies all belong to the medical industry. In addition to the general analysis modules such as finance and human resources, BI in the medical industry has also added many applications for patients and drugs, such as nursing management, outpatient process analysis, medical record whiteboard, department analysis, drug circulation management, flow analysis, drug quality analysis of pharmaceutical enterprises, etc.
Scenario 1: Consumables management in medical institutions
In order to achieve profitability, each medical institution increases sales through marketing on the one hand, and increases profitability by reducing costs on the other. Therefore, it is crucial to know in real time how much each department consumes medical consumables and how much they cost: which departments consume the most consumables? How can I reduce my consumption to reduce costs? What are the selling price and cost trends of medical consumables? For consumables with high cost and low selling price, can the price be increased to ensure profitability?
The diagram below illustrates the medical consumables management dashboard developed by the medical industry with Finebi. The dashboard provides detailed analysis and focused monitoring of commonly used, extra-large and non-chargeable consumables to dig deeper into the deeper reasons behind consumables consumption. This visualization tool helps healthcare organizations gain a more complete picture of consumables usage, allowing them to develop more effective cost management and profitability strategies.
Scenario 2: Pharmaceutical risk management
In the highly competitive sales environment of pharmaceutical distribution enterprises, although the total number of customers is relatively limited, credit sales as an important sales method still exists. However, similar to the situation of offering credit to a friend, this type of sales is potentially risky and can lead to losses for the business. Therefore, it is very important for pharmaceutical distribution enterprises to understand the credit status of customers and effectively manage credit risk when selling on credit.
The chart below illustrates the pharmaceutical risk management developed by Finebi in the healthcare industry, which helps pharmaceutical companies to identify and respond to financial risks in a timely manner and ensure their financial health. Secondly, for the complex first-chain system, the system can trace and optimize each link in the first-chain to reduce the potential first-chain risk and ensure the normal circulation of drugs and medical products. In addition, through in-depth analysis of market trends and competitive landscape, the system can also provide enterprises with insights into market risks, helping enterprises flexibly respond to market changes.
This article briefly introduces the four major industries of retail, finance, manufacturing, and healthcare, with a total of eight typical BI business application scenarios, but in fact, there are many BI business application scenarios in different industries, which we summarize here with a diagram.
These typical cases not only highlight the diverse applications of business intelligence in different industries, but also highlight the great potential of BI in improving management efficiency and optimizing the decision-making process. This gives businesses the tools to operate smarter and more agile in a competitive market.
Hopefully, this article will provide you with guidance and help in introducing BI to your business! #bi#