The tasks of data analysis are to develop rules for the formation and improvement of a theoretical understanding of the object.

To perform data analysis, this data must be collected. The data must be organized in a specific format. For example, the data table should contain an object and its attribute. Attribute may be as quantitative as not.

Data analysis methods are applied to the collected data. Next, the patterns are defined. Results should be based on identified patterns.

Classification of data analysis methods:

Principal component analysis, Independent Component Analysis used to form quantitative concepts.

Сluster analysis is used to form quantitative concepts.

Regression, Classification and Support Vector Machine Methods are used to form patterns and predict based on them.

Modern manufacturing requires data analysis to establish business processes, production, and more. For example, demand forecasting allows you to rationally purchase components. In result, The entire value chain is optimized.

Science and engineering is another area in modern high-tech manufacturing where data analysis techniques can be used. For example, the selection of chemical formulas for future medicinal preparations. Undoubtedly, this requires a large database of accumulated data. Hence a large number of experiments must be carried out. But do not think that only large commercial giants can afford to work with data analysis. For example, scientists and engineers involved in the synthesis of materials have created an open database that anyone can use. The biggest drawback is the inability to check the relevance of the data. However, good results have been achieved in this area.

by Dimerion Steelson

Сообщение Data Analysis for Manufacturing появились сначала на strategic.tools.

According to the survey, fundamental digitization is present in 23% of all enterprises in this area. 41% have a moderate level of internet engagement. A high or advanced level is held by 36% of SMEs. Customers’ engagement grows as a result of digital tools, according to the executives of organizations with a high and advanced level of digitalization. At the same time, such businesses have a fivefold improvement in their chances of attracting overseas clientele.

Companies with a high level of digitization have a better understanding of their customers.

New markets are opened as a result of innovation. There are many more fresh product and service development concepts. According to experts, businesses with a high level of digitalization are three times more likely to penetrate new markets.

Almost all businesses communicate using digital means. Sales management tools are used by less than half of SMEs – 40%**. Email – 75 %, company website – 68 %, social networks – 53 %, video conference – 36 %, and smartphone application are among the most popular digital communication platforms – 24 %. SMEs employ cloud-based technologies for internal management and logistics – 67 %. For these goals, corporate social networks proved to be the least popular – 19 %). Customer relationship management (CRM) tools accounted for 30% of the total, while intranets accounted for 24%, internal software to connect sales and supply-chain processes accounted for 21%, and enterprise resource planning solutions accounted for 20%.

The tools that businesses employ to manage sales are critical. Approximately 40% of SMEs sell their products online. They do this by using websites or marketplaces. 30% of all businesses have their own website. CMEs are sold through marketplaces in 20% of cases. 60 % of internet retailers use client data gathered for their own purposes in order to increase loyalty and revenues. 40% of small businesses sell them in their shops. Internal communications, logistics, and sales management can all benefit from digital solutions, as previously mentioned. Now let’s have a look at the advantages of corporate digitalization. The rise in customer satisfaction is the most favored (60 percent). This can be aided by a more personalized approach, customer service, chat bots, and a variety of other methods. A decrease in operational costs was observed by 22% of CMEs. Attracting new consumer segments, offering products and services, and so on are all major advantages.

The following were identified as the most important tools for attracting customers: the corporate website, social media, CRM, SEO, and a mobile app. All digital technologies are designed to help you earn more money. As a result, the key growth drivers, according to the poll, were existing customers – 61%, existing products or services – 41%, new customers – 80%, and new products or services – 31 %.

by The Editorial Board

^*Final Report, Deloitte Financial Advisory, 2019

^**In brackets is the percentage of surveyed companies that gave positive answer

Сообщение Digitalization of Small and Medium Enterprises появились сначала на strategic.tools.

Probability is an estimate of the event occurring possibility. Probability theory allows you to link random events into a mathematical model. A prime example is the insurance business.

Insurance is a business that is entirely based on the theory of probability. For example, many types of car insurance depend on the driving experience. Why is that? Because insurance companies have statistics. They have calculated from this that the probability of accident with experienced driver is several times less than driver who received a license yesterday.

Product quality assessment is another example of the use of probability theory. For example, recently produced TVs were tested in different way. One type of test were performed as follows. TVs were turned on and they worked without interruption. Gradually, some of the TVs broke down. Thus, it was possible to draw a conclusion about what percentage will fail in the first year of operation, in the second, and so on. Manufacturer’s guarantees must base on assessment of product quality.

You can calculate the probability from statistics. Statistics can be learned from past experience. Everything is clear here. But what if there is no data. For instance, you are planning to open a store, but you do not know which one: candy, grocery or a store with gifts. Sample comes to the rescue here. You need to do a random sample study and approximate this data. For example, study the needs of 100 single people, 100 young families with children and 100 retirees. You will get the preference of each group. You will get the preference of each group. Next, find out how many people live in your area and what group they belong to. For example, in your area there are new buildings with a large number of children. They need a store with milk shakes, which is rarely needed by the elderly because of health problems and by single people, since they, unlike children, are often watch them figure.

The accuracy of your calculation (business model) depends on the amount of data according to the law of large numbers. Namely, the more data you use for a model, the more accurate the model will be. Owner of candy stall took the summer season sales statistics for the future prediction. It is obvious that the data will not be enough, since the Christmas holidays did not be included in the statistics.

The probability can be represented as a graph. The normal distribution is shown in the figure.

It seems that all of nature is under the influence of a normal distribution (for example, a hole in the road in the form of a normal distribution). How can this be used in business? For instance, in women, the average foot size in region A is x inches (and this is the maximum value of the distribution function). Why would a store buy a batch of the same number of shoes of each size? It is very right do order according to a normal distribution, which can be constructed using, for example, a sample or an sales experience.

Your model should always be revised and updated with new data. For example, in early 2019, you made a forecast based on probability theory that your physical store will receive 40 percent more customers in 2020 and you need to increase the area. According to the collected statistics for 2018 and 2019, your calculations are absolutely correct, but already in March 2020, due to the pandemic, everything collapses. And now it is better to direct your money to the development of an online store. Any model requires data updates that takes into account specific factors.

With such simple examples it becomes clear that the theory of probability can be very useful in business.

Сообщение Probability Theory for Business появились сначала на strategic.tools.