1. Single business model Single business, also known as specialized business, means that an enterprise only designs, produces or sells in one product field, and its business scope is relatively single.
2. Diversified business models Diversified business models can be divided into three basic types: centralized diversification, horizontal diversification and mixed diversification.
In addition, the enterprise operation mode is classified according to the position of the enterprise in the industrial chain:
1. As a supplier of enterprises in the middle and lower reaches of the industrial chain, OEM enterprises process products according to customer orders. In the market, signs sold by other enterprises were put up.
2. Design+sales enterprises are not involved in any business in the production field, but only responsible for design and sales. Enterprises design products and services that customers need in the market, and then look for corresponding production OEM. It requires enterprises to have strong design and sales capabilities and their own well-known brands.
3. Production+Sales Type
4. Design+production+sales. This is a business model involving many nodes in the industrial chain. The characteristic of enterprises adopting this business model is their ability to develop new products.
. 5. Information service Information service enterprises are usually consulting companies. This kind of enterprise or company does not involve all manufacturing activities, but it is closely related to the manufacturing industry to a great extent.
Extended information:
In modern enterprises, enterprise managers use e-commerce platform to greatly improve the efficiency and benefit of traditional business activities. Compared with the traditional business model, this business model has the following advantages:
1. Expand market scope and increase business opportunities.
2. Reduce transaction costs.
3. Reduce inventory. In order to meet the unpredictable market demand, enterprises have to keep a certain product inventory, and because of the uncertainty of enterprise managers on the raw material market, they often keep a certain raw material inventory.
The basic reason of inventory is poor information, and e-commerce based on information technology can solve the problem of inaccurate and untimely information in enterprise decision-making.
4. Reduce the management cost of the enterprise, do not use too many written materials and documents, reduce the expenditure of office supplies and labor costs, and also reduce the communication cost.
5. Communicate well with customers. Consumers can directly contact and communicate with enterprises and directly ask questions about products and services. At the same time, enterprises use words, pictures and images to show customers the contents of products and services, explain and answer customers' inquiries, so that the whole pre-sales and after-sales service is timely and clear.
Enterprises can let consumers put forward their own requirements at a lower cost, and then provide targeted products and services according to different requirements.
Under e-commerce, enterprises can truly meet the different needs of each consumer and meet the personalized needs of customers, which not only increases the difficulty for other enterprises to enter, but also increases the sales rate and satisfaction of products and services. Realize the visualization of the whole supply chain, the informationization of enterprise management, the maximization of overall benefit and the minimization of enterprise management cost, so as to realize the "win-win" between enterprises and customers and achieve the purpose of enterprise management model innovation.
Business logic in the era of big data Business logic in the era of big data
The so-called data mining is a method to analyze a large amount of data stored by enterprises through mathematical models, so as to find out different customers or market segments and analyze consumers' preferences and behaviors. According to IDC, a technology research company, the size of global data is now doubling every two years. The drastic changes that followed are reflected in the changes of the four V's. First, the amount of data is huge, jumping from TB level to PB level; Second, the data types are diverse, and web logs, videos, pictures and geographic information have become huge new data sources. Third, the value density is low. Take video as an example. In the process of continuous monitoring, useful data may only be one or two seconds. Fourthly, the processing speed is fast, and the "1 second law" is essentially different from the traditional data mining technology.
Obviously, the rise of "big data" has opened a new door for business.
Undoubtedly, the data-oriented way of thinking has brought high returns to all aspects. For example, super retailers such as Wal-Mart have already begun to analyze sales, pricing, economy, demographics and weather data, so as to select suitable products to be put on shelves in specific chain stores, and determine the timing of price reduction according to these analyses; UPS and other freight companies are also analyzing data such as truck delivery time and transportation mode to fine-tune their transportation routes. However, some social dating websites often carefully check the personal characteristics, responses and exchange information listed on their websites to improve their algorithms and provide better matches for men and women who want to date. Today's "massive data" has brought about a turning point in scale and scope: Internet of Things, cloud computing, mobile Internet, car networking, mobile phones, tablets, PCs and sensors all over the world, all of which are data sources or bearing methods. They are gathered together because of "data", and then become a new competitive field that enterprises need to pay attention to in future value upgrading.
Eric Brynolfson, an economics professor at the Si Long School of Management at MIT, once compared the potential impact of "big data" to "the data measurement revolution in the form of a microscope". In business, economy and other fields, decision-making behavior will be more and more based on data and analysis, rather than on experience and intuition. According to this research report, data-oriented management activities are spreading in the corporate world, and this kind of management activities are beginning to pay off. "Those companies that adopt the data-driven decision-making model can increase their productivity by 5% to 6%, which is difficult to explain by other factors."
It is reported that in the United States alone, there are 1.4 million to 1.9 million professionals with data analysis and management capabilities, and 1.5 million managers and analysts with understanding and decision-making capabilities (based on the study of massive data). The analysis of McKinsey Global Institute shows that in order to make full use of the potential of massive data, enterprises and decision makers must overcome the following challenges:
1. Make massive data more accessible and timely. In manufacturing industry, integrating data from R&D, design and manufacturing units and promoting concurrent engineering can shorten the time to market.
2. Use data and experiments to reveal variability and improve performance. As more and more transaction data are created and stored in digital form, enterprises can collect more accurate and detailed performance information, including all kinds of information from product inventory to employee sick leave.
3. Subdivide consumer groups and tailor services. Massive data enables enterprises to create more subdivided market segments and customize appropriate services to better meet the needs of consumers.
4. Use automated algorithms to replace and support manual decision-making. Advanced analysis algorithms can greatly improve the efficiency and quality of decision-making, reduce risks and find hidden valuable insights.
5. Create new business models, products and services. In order to improve the development level of the next generation products and create innovative after-sales service, manufacturers are making full use of the data obtained from product use. The emergence of real-time positioning data has created a series of new location-based mobile services, from navigation and positioning to personal tracking.
In view of the above topics, the cover of this issue will focus on the following key issues: Where does the new profit of enterprises come from in the data age? What is the new business thinking mode in the era of big data? How to use "big data" to help social marketing? How do traditional enterprises (such as enterprise recruitment) use data technology to realize the optimal allocation of resources? All these questions have the same proposition: Who can win in the era of big data and how?
The data has sat in the driver's position, and it is there, useful and precious, even sexy and fashionable.
The above is what Bian Xiao shared for everyone.
Business logic in the era of big data
More information can be paid attention to.
Sinomenium globosum
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How to make investors climax with a business plan with only 10 pages PPT 1) Summarize the investment highlights of the company in one or two sentences. You should use the most attractive words to explain why your project/company is important. Usually, you can directly and concisely state your solution or product to a major problem. In addition, if you can mention some heavyweight names, it would be best-such as heavyweight consultants, partners, well-known angel investors and so on.
2) Introduce the company's products or services in one or two sentences, and what problems are solved for users. You need to clearly describe a current or upcoming major problem. What products or services does the company provide to customers to solve this problem? Software, Hardware, Services or Integration? Describe the company's products or services in popular language. Don't use various terms, it will only annoy VC. In addition, if the customer is a well-known big company, be sure to say it;
3) Describe clearly the company's business model in one or two sentences-how to make money? You need to know the position of the company in the industrial chain and value chain, who is the partner and why you should cooperate with your company. If you already have income, how much? If not, when will there be?
4) Describe the industry, industry segmentation, huge market scale, growth and driving factors and bright prospects of the company in one or two sentences. Don't use empty and broad statements to describe market opportunities. At present, the small but fast-growing market will be more attractive than the relatively large and stable market;
5) Summarize the company's advantages over competitors in one or two sentences. In any case, you have competitors, at least, you are competing with the products or service providers currently used by your target customers. More often, you face some direct competitors. Don't try to convince VC of your "first Mover advantage", don't even think about it. Use positive words to describe the company's goals and competitive advantages. VC values what you can do, not what others can't. For example: "Compared with Cisco's solution, our solution can";
6) Use tables to show the company's historical financial situation and future financial forecast. If it is a start-up company, the historical financial part can be omitted, but the financial forecast for 3-5 years must meet VC's investment return expectation. In addition, it is best to match the drivers of revenue, such as customer growth. But if the financial forecast is too outrageous for VC to believe, all the work will be in vain;
7) State in one or two sentences the expected financing amount of the company in this round. What is it mainly used for? This is usually the minimum capital required for the company to develop to the next important stage. If VC is willing to invest more, of course it is best.
8) Show the background and "brilliant achievements" of entrepreneurs and core management teams in one or two sentences. Don't use some standard cliches, such as "CEO has 10 years of experience in Internet and new media operation and management", but be specific to "c to has been engaged in data storage research at Intel for 3 years".