TIBCO Spotfire: Big Data Analytics. Business Intelligence (BI) systems for business analysis Approaches to data analysis business analytics

Every big business and most medium-sized structures are faced with the problem of providing management with inaccurate data on the state of the company. The reasons may be different, but the consequences are always the same - wrong or untimely decisions that adversely affect the effectiveness of financial transactions. To avoid such situations, a professional business intelligence or BI system is designed ( from English. – business intelligence). These high-tech "assistants" contribute to building a system of managerial control of every aspect within the business.

At its core, BI systems are advanced analytical software for business analysis and reporting. These programs can use data from various sources information and provide them in a convenient form and section. As a result, management gets quick access to complete and transparent information about the state of affairs of the company. A feature of the reports obtained with the help of BI is the ability of the manager to independently choose in which context to obtain information.

Modern Business Intelligence systems are multifunctional. That is why in large companies they are gradually replacing other ways of obtaining business reporting. Their main capabilities include:

Connections to various bases data, in particular, to ;
Formation of reports of varying complexity, structure, type and layout with high speed. It is also possible to set a schedule for generating reports on a schedule without direct participation and data distribution;
Transparent work with data;
Ensuring a clear link between information from different sources;
Flexible and intuitive configuration of access rights for employees in the system;
Saving data in any format convenient for you - PDF, Excel, HTML and many others.

The capabilities of business intelligence information systems allow the manager not to depend on the IT department or his assistants to submit the required information. It is also a great opportunity to demonstrate the right direction of your decisions not with words, but with exact numbers. Many large network corporations in the West have been using BI systems for a long time, including the world-famous Amazon, Yahoo, Wall-Mart, etc. The above-mentioned corporations spend decent money on business intelligence, but the implemented BI systems bring invaluable benefits.

The benefits of professional business intelligence systems are based on principles that are supported in all advanced BI applications:

visibility. The main interface of any business analysis software should reflect key metrics. Thanks to this, the manager will quickly be able to assess the state of affairs in the enterprise and begin to do something if necessary;
Customization. Each user should be able to customize the interface and function keys in the most convenient way for themselves;
Layering. Each data set should have several cuts (layers) to provide the detail of information that is needed at a particular level;
Interactivity. Users should be able to collect information from all sources and in several directions at the same time. It is necessary that the system has the function of setting alerts by key parameters;
Multithreading and access control. Simultaneous work must be implemented in the BI system a large number users with the ability to set different access levels for them.

The entire IT community agrees that Information Systems business analytics is one of the most promising areas for the development of the industry. However, their implementation is often hampered by technical and psychological barriers, uncoordinated work of managers and the lack of prescribed areas of responsibility.

When considering the implementation of class BI systems, it is important to remember that the success of the project will largely depend on the attitude of the company's employees to the innovation. This applies to all IT products: skepticism and fear of downsizing can thwart all implementation efforts. Therefore, it is very important to understand how the business intelligence system makes future users feel. The ideal situation will be when the company's employees will treat the system as an assistant and a tool for improving work.

Before starting a project to implement BI technology, it is necessary to conduct a thorough analysis of the company's business processes and the principles of adoption management decisions. After all, it is these data that will be involved in the analysis of the situation in the company. It will also help to make a choice of a BI system along with other main criteria:

Goals and objectives of the implementation of BI systems;
Requirements for data storage and the ability to operate with them;
Data integration functions. Without using data from all sources in the company, management will not be able to get a holistic picture of the state of affairs;
Visualization capabilities. For each person, the ideal BI analytics looks different, and the system must meet the needs of each user;
Universality or narrow specialization. In the world, there are systems aimed at a specific industry, as well as universal solutions that allow you to collect information in any context;
Demanding resources and the price of a software product. The choice of a BI system, like any software, depends on the capabilities of the company.

The above criteria will help management make an informed choice among the variety of known business intelligence systems. There are other parameters (for example, data storage structure, web architecture), but they require skills in narrow IT areas.

It is not enough just to make a choice, buy software, install and configure it. Successful implementation of BI systems of any direction is based on the following rules:

Data correctness. If the data for analysis is incorrect, then there is a possibility of a serious system error;
Full training for each user;
Rapid implementation. It is necessary to focus on the correct formation of the necessary reports in all key places, and not on the ideal service for one user. Adjust appearance report or add another section for convenience, you can always after implementation;
Understand the return on investment in your BI system. The effect depends on many factors and in some cases is visible only after a few months;
The equipment should be designed not only for the current situation, but also for the near future;
Understand why the BI implementation was started, and do not demand the impossible from the software.

According to statistics, only 30% of company executives are satisfied with the implementation of BI systems. Over the long years of the existence of business analysis software, experts have formulated 9 key mistakes that can reduce efficiency to a minimum:

Non-obviousness of the purpose of implementation for management. Often the project is created by the IT department without the close participation of managers. In most cases, in the process of implementation and operation, questions arise regarding the purpose and objectives of the BI system, the benefits and ease of use;
Lack of transparency in management, work of employees and decision-making. Managers may not know the algorithms of the work of employees in the field, and management decisions may be made not only on the basis of dry facts. This will lead to the impossibility of maintaining the existing paradigm as a result of the implementation of the BI system. And often break the culture that has developed over the years corporate governance impossible;
Insufficient reliability of data. It is unacceptable for false information to enter the business analysis system, otherwise employees will not be able to trust it and use it;
Wrong choice of a professional business intelligence system. Many examples in history when management hires a third-party organization to implement a BI system and does not take part in its selection speak for themselves. As a result, a system is being introduced that does not allow obtaining the required report or with which it is impossible to integrate one of the existing software in the company;
Lack of a plan for the future. The peculiarity of BI systems is that it is not static software. It is impossible to finish an implementation project and not think about it. There are many requirements from users and management in terms of improvements;
Transfer of BI system third party organization for support. As practice shows, most often such situations lead to the isolation of the product and the isolation of the system from the real state of affairs. Own service support responds much faster and more efficiently to user feedback and management requirements;
Desire to save. In business, this is normal, but BI analytics only works if it takes into account all aspects of the company's activities. That is why deep analytical systems with high cost are the most effective. The desire to receive several reports on areas of interest leads to frequent errors in the data and a great dependence on the qualifications of IT specialists;
Different terminology in the company. It is important that all users understand the basic terms and their meaning. A simple misunderstanding can lead to misinterpretation of the reports and indicators of the BI system;
Lack of a unified strategy for business analysis in the enterprise. Without a single course selected for all employees, any BI class system will be just a set of disparate reports that meet the requirements of individual managers.

Implementing BI systems is an important step that can help take your business to the next level. But this will require not only a fairly large infusion of finance, but also the time and effort of each employee of the company. Not every business is ready to competently complete the project of implementing a business analysis system.

Small businesses in the CIS countries do not yet use data analysis for business development, determining correlations, searching for hidden patterns: entrepreneurs make do with reports from marketers and accountants. The leaders of small and partially medium-sized enterprises rely more on their intuition than on analysis. But at the same time, analytics has a huge potential: it helps to reduce costs and increase profits, make decisions faster and more objectively, optimize processes, better understand customers and improve the product.

An accountant will not replace an analyst

Small business executives often assume that marketing and accountant reports are a fairly accurate representation of a company's performance. But on the basis of dry statistics, it is very difficult to make a decision, and an error in calculations without specialized education is inevitable.

Case 1. Post-analysis of promotional campaigns. By the New Year, the entrepreneur announced a promotion in which certain goods were offered at a discount. After evaluating the revenue for the New Year period, he saw how sales increased, and was delighted with his resourcefulness. But let's take into account all the factors:

Sales are especially strong on Friday, the day when revenue is maximum - this is a weekly trend.
Compared to sales growth that usually occurs under New Year, then the gain is not so great.
If you filter out promotional items, it turns out that sales figures have deteriorated.

Case 2. Study of turnover. At the store women's clothing difficulties with logistics: the goods in some warehouses are in short supply, and in others they lie for months. How to determine, without analyzing sales, how many trousers to bring to one region, and how many coats to send to another, while getting the maximum profit? To do this, you need to calculate the turnover, the ratio of the speed of sales and the average inventory for a certain period. To put it simply, the turnover is an indicator of how many days the store will sell the goods, how quickly the average stock is sold, how quickly the goods pay off. It is economically unprofitable to store large reserves, as this freezes capital and slows down development. If the stock is reduced, there may be a shortage, and the company will again lose profits. Where to find the golden mean, the ratio at which the product does not stagnate in the warehouse, and at the same time you can give a certain guarantee that the customer will find the right unit in the store? To do this, the analyst should help you determine:

desired turnover,
turnover dynamics.

When settling with suppliers with a delay, you must also calculate the ratio of the credit line and turnover. Turnover in days = Average inventory* number of days / Turnover for this period.

Calculation of assortment balances and total turnover in stores helps to understand where it is necessary to move part of the goods. It is also worth calculating what turnover each unit of the assortment has in order to make a decision: markdown with reduced demand, re-order with increased demand, relocation to another warehouse. By category, you can develop a report on turnover in this form. It can be seen that T-shirts and jumpers are sold faster, but coats are sold for a long time. Can an ordinary accountant do this job? We doubt. At the same time, regular calculation of turnover and application of the results can increase profits by 8-10%.

In what areas is data analysis applicable?

Sales. It is important to understand why sales are going well (or badly), what are the dynamics. To solve this problem, it is necessary to investigate the factors influencing profit and revenue - for example, to analyze the length of the receipt and revenue per customer. Such factors can be investigated by groups of goods, seasons, stores. You can identify sales peaks and pits by analyzing returns, cancellations, and other transactions.
Finance. Monitoring of indicators is necessary for any financier to monitor cash flow and distribute assets across various business areas. This helps to evaluate the effectiveness of taxation and other parameters.
Marketing. Any marketing company needs forecasts and post-analysis of stocks. At the stage of developing the idea, it is necessary to determine the groups of goods (control and target) for which we are creating an offer. This is also a job for a data analyst, since an ordinary marketer does not have the necessary tools and skills for good analysis. For example, if for the control group the amount of revenue and the number of customers are the same as the target group, the promotion did not work. To determine this, interval analysis is needed.
Control. Have leadership skills not enough for the leader of the company. In any case, quantitative assessments of the work of personnel are necessary for the competent management of the enterprise. It is important to understand the effectiveness of wage fund management, the ratio of wages and sales, as well as the efficiency of processes - for example, the workload of cash desks or the employment of loaders during the day. This helps to properly distribute working hours.
Web analysis. The site needs to be properly promoted so that it becomes a sales channel, and this requires the right promotion strategy. This is where web analysis can help you. How to apply it? To study the behavior, age, gender and other characteristics of customers, activity on certain pages, clicks, traffic channel, mailing performance, etc. This will help improve the business and website.
Assortment management. ABC analysis is essential for assortment management. The analyst must distribute the product by characteristics in order to conduct this type of analysis and understand which product is the most profitable, which is the basis, and which should be discarded. To understand the stability of sales, it is good to conduct an XYZ analysis.
Logistics. More understanding about procurement, goods, their storage and availability will be given by the study of logistics indicators. Losses and needs of goods, inventory is also important to understand for successful business management.

These examples show how powerful data analysis is, even for small businesses. An experienced director will increase the company's profits and benefit from the most insignificant data, using data analysis correctly, and visual reports will greatly simplify the work of a manager.

Business intelligence and data analysis. Effective consulting is what is necessary for the qualitative development of any business. Solving existing problems and crises, preventing potential ones, finding ways to increase profits and efficiency in general: all this provides you with quality consulting.

The consulting process is complex, multi-stage, multi-level, there is no clear and universal approach to absolutely any business: the business context, its niche, industry, target audience, features and much more: all this affects how business processes will be diagnosed. Naturally, the final stage of consulting is preceded by many other pre-processes, such as preparing a task, describing business processes, business analytics, diagnosing the infrastructure in general and the IT infrastructure of the organization, in particular, data is analyzed, and based on this, a number of recommendations are created. . I must say that it is business analytics and data analysis - milestones in the process of consulting, it is they who lead to the appropriate conclusions, it is on the basis of such an analysis that any recommendations are created.

Data analysis and business analytics: how to implement?

Qualitative analysis, in this case, cannot do without the presence of any quantitative metrics. That is, it is very desirable that some kind of automation be introduced into the work of the enterprise - business processes, relationships with customers, suppliers, intermediaries, so that document flow and all other processes are also automated. It is with a qualitative account of all the processes occurring within the business that reporting and further analytics are greatly facilitated.

How can you automate document flow, customer management and facilitate reporting?

The best option would be exclusive software designed to perform many tasks - from FB Consult. You are offered high-quality customer management systems - various kinds of CRM, designed for various business sectors, effective solution for document flow control - DocsVision, as well as software suitable for business intelligence and data analysis, including - and for identifying dubious financial transactions - QlikView. The implementation of such solutions will significantly increase the efficiency of your business.

(Business Intelligence).

As speakers for the seminar, young professionals who make a successful career as analysts in high-tech companies such as Microsoft, IBM, Google, Yandex, MTS, etc. are invited. At each seminar, students are told about some of the business tasks that are solved in these companies, about how data is accumulated, how data analysis problems arise, what methods they can be solved.

All invited specialists are open for contacts, and students will be able to contact them for advice.

Seminar objectives:

contribute to the elimination of the existing gap between university research and the solution of practical problems in the field of data analysis;
promote the exchange of experience between current and future professionals.

The seminar is held regularly at the faculty of the CMC of Moscow State University on Fridays at 18:20 , audience P5(first floor).

Seminar attendance - free(If you do not have a pass to MSU, please inform the organizers of the seminar in advance of your full name in order to submit the list of participants for rotation).

Seminar program

date of	Speaker and Seminar Topic
September 10, 2010 18:20	Alexander Efimov , head of analytical department retail network MTS. Forecasting the effect of marketing campaigns and optimizing the range of stores. Application page: Optimization of the assortment of outlets (task with data) .
September 17, 2010 18:20	Vadim Strizhov , Researcher Computing Center of the Russian Academy of Sciences. Bank credit scoring: methods for automatic generation and selection of models. Classical and new technology building scorecards. The seminar explains how customer data is structured and how to generate the most plausible scoring model that also meets the requirements of international banking standards.
September 24, 2010 18:20	Vladimir Krekoten , head of the marketing and sales department of the brokerage house Otkritie. Application of mathematical methods to predict and counter customer churn. The practical problems that arise in the analysis of the client base in marketing are considered. The tasks of clustering and segmenting customers, scoring new customers, tracking the dynamics of target segments are set. Application Page: Brokerage Client Clustering (Data Task) .
October 1, 2010 18:20	Nikolay Filipenkov , and about. Head of the Credit Scoring Department of the Bank of Moscow. Application of mathematical methods for retail management credit risk . Some practical aspects of building scoring models and risk assessment are considered. Application Page: Retail Credit Risk Management (Data Task) .
October 8, 2010 18:20	Fedor Romanenko , Search Quality Department Manager, Yandex. History and principles of web search ranking. The issues of using and developing Information Retrieval methods, from text and link ranking to Machine Learning to Rank in the problem of Internet search, are considered. The basic principles behind modern web ranking are set out in relation to search engine success stories. Particular attention is paid to the impact of search quality on market performance and the vital need to constantly work on improving it.
October 15, 2010 18:20	Vitaly Goldstein , developer, Yandex. Geographic information services Yandex. It tells about the Yandex.Probki project and other Yandex geoinformation projects, about where the source data for building comes from geoinformation systems, about a new scalable data processing technology, about the competition of Internet mathematics and some promising tasks. Data are provided and a formal statement of the problem of road map restoration is given. Application Page: Building a Road Graph from Vehicle Track Data (Data Task) .
October 22, 2010	The seminar has been cancelled.
October 29, 2010 18:20	Fedor Krasnov , Vice President of Business Processes and information technology, AKADO. How to get customer data?

Business intelligence, or BI, is a general term that refers to a variety of software products and applications designed to analyze an organization's primary data.

Business analysis as an activity consists of several interconnected processes:

data mining (data mining),
real-time analytical processing (online analytical processing),
getting information from databases (querying),
making report (reporting).

Companies are using BI to make informed decisions, cut costs and find new business opportunities. BI is something more than ordinary corporate reporting or a set of tools for obtaining information from enterprise accounting systems. CIOs use business intelligence to identify underperforming business processes that are ripe for redesign.

Using modern instruments business analysis, businessmen can start analyzing the data themselves and not wait for the IT department to generate complex and confusing reports. This democratization of access to information enables users to back up their business decisions with real numbers that would otherwise be based on intuition and chance.

Despite the fact that BI systems are quite promising, their implementation can be hampered by technical and "cultural" problems. Managers need to provide clear and consistent data to BI applications so that users can trust them.

Which companies use BI systems?

Restaurant chains (for example, Hardee's, Wendy's, Ruby Tuesday and T.G.I. Friday's) actively use business intelligence systems. BI is extremely useful to them for making strategically important decisions. What new products to add to the menu, what dishes to exclude, what inefficient outlets to close, etc. They also use BI for tactical issues such as reviewing contracts with product suppliers and identifying ways to improve inefficient processes. Since restaurant chains are strongly focused on their internal business processes and because BI takes control of these processes central location By helping to manage businesses, restaurants, among all industries, are part of an elite group of companies that really benefit from these systems.

Business intelligence is one of key components B.I. This component is essential to the success of a company in any industry.

In the sector retail Wal-Mart makes extensive use of data analysis and cluster analysis in order to maintain its dominant position in the sector. Harrah's has shifted the fundamentals of its competitive gaming policy to focus on customer loyalty and service levels, rather than maintaining a mega-casino. Amazon and Yahoo are not just big web projects, they are actively using business intelligence and a common “test and understand” approach to streamline their business processes. Capital One conducts over 30,000 experiments annually to identify target audience and evaluating credit card offers.

Where or with whom should the implementation of BI start?

Overall employee engagement is vital to the success of BI projects, as everyone involved in the process must have full access to information in order to be able to change the way they work. BI projects should start with top management and the next group of users should be sales managers. Their main responsibility is to increase sales, and wage often depends on how well they do it. Therefore, they are much more likely to accept any tool that can help them in their work, provided that the tool is easy to use and that they trust the information it provides.

You can order your pilot project on the business analysis platform.

Using BI systems, employees adjust work on individual and group tasks, which leads to more efficient work of sales teams. When sales leaders see a significant difference in the performance of several departments, they try to bring the “lagging” departments to the level at which the “leading” ones are performing.

Having implemented business intelligence in sales departments, you can continue to implement it in other departments of the organization. A positive salesperson experience will encourage other employees to adopt new technologies.

How to implement a BI system?

Before implementing a BI system, companies should analyze the mechanisms for making managerial decisions and understand what information managers need to make these decisions more informed and faster. It is also desirable to analyze in what form managers prefer to receive information (as reports, graphs, online, in paper form). Refinement of these processes will show what information the company needs to receive, analyze and consolidate in its BI systems.

Good BI systems should provide users with context. It is not enough to simply report what sales were yesterday and what they were a year ago on the same day. The system should make it possible to understand what factors led to exactly this value of sales on one day and another - on the same day a year ago.

Like many IT projects, BI adoption will not pay off if users feel “threatened” or skeptical about the technology and stop using it as a result. BI, being implemented for "strategic" purposes, should, in theory, fundamentally change how the company functions and the decision-making process, so IT leaders need to pay special attention to the opinions and reactions of users.

7 stages of launching BI systems

Make sure that your data is correct (reliable and suitable for analysis).
Provide comprehensive user training.
Implement the product as quickly as possible, getting used to using it already in the course of implementation. You don't have to spend a huge amount of time developing "perfect" reports, because reports can be added as the system evolves and users need it. Build reports that deliver the most value quickly (user demand for these reports is the highest) and then tweak them.
Take an integrative approach to building a data warehouse. Make sure you don't lock yourself into a data strategy that doesn't work in the long run.
Before you start, clearly estimate the ROI. Determine the specific benefits you intend to achieve and then test them against actual results every quarter or every six months.
Focus on your business goals.
Don't buy analytics software because you think that you need it. Implement BI with the idea that there are indicators among your data that you need to get. At the same time, it is important to have at least a rough idea of where exactly they can be.

What problems might arise?

A major obstacle to the success of BI systems is user resistance. Among other possible problems is the need to "sift through" large amounts of irrelevant information, as well as data of poor quality.

The key to getting meaningful results from BI systems is standardized data. Data is a fundamental component of any BI system. Companies need to get their data warehouses in order before they can start extracting the information they need and trust the results. Without data standardization, there is a risk of getting incorrect results.

Another problem may be an incorrect understanding of the role of the analytical system. BI tools have become more flexible and user-friendly, but their main role is still reporting. Do not expect automated business process management from them. However, certain changes in this direction are still planned.

The third obstacle in the transformation of business processes using the BI system is the lack of understanding by companies of their own business processes. As a result, companies simply do not understand how these processes can be improved. If the process does not have a direct impact on profits, or the company does not intend to standardize processes in all its divisions, the implementation of a BI system may not be effective. Companies need to understand all the activities and all the functions that make up a single business process. It is also important to know how information and data is transferred through several different processes, and how data is transferred between business users, and how people use this data to carry out their tasks within a particular process. If the goal is to optimize the work of employees, all this must be understood before starting a BI project.

Some benefits of using BI solutions

A large number of BI applications have helped companies recoup their investments. Business intelligence systems are used to explore ways to reduce costs, identify new business opportunities, present ERP data in visual form, as well as to quickly respond to changes in demand and optimize prices.

In addition to making data more accessible, BI can provide companies with more value during negotiations by making it easier to evaluate relationships with suppliers and customers.

Within an enterprise, there are many opportunities to save money by optimizing business processes and overall decision-making. BI can effectively help improve these processes by shedding light on the mistakes made in them. For example, employees at a company in Albuquerque used BI to identify ways to reduce the use of mobile phones, work in overtime and other operating expenses, saving the organization $2 million over three years. Also, with the help of BI solutions, Toyota realized that it had overpaid its carriers by half. the total amount$812,000 in 2000 Using BI systems to detect defects in business processes puts the company in a better position, giving competitive advantage to companies that use BI just to keep track of what's going on.

Analyze how leaders make decisions.
Think about what information managers need to optimize their operational decision-making.
Pay attention to data quality.
Consider a performance measure that has highest value for business.
Provide context that influences the performance measure.

And remember, BI is about more than decision support. With advances in technology and how IT leaders implement it, business intelligence systems have the potential to transform organizations. CIOs who successfully use BI to improve business processes make a much more meaningful contribution to their organization, executives who implement basic reporting tools.

Sourced from www.cio.com