Construction of an operational financial management system.

THE VALUE OF INDIVIDUAL TCM BLOCKS FOR DIFFERENT TYPES OF COMPANIES,
or “We have our own specifics, and everything works differently...”

In every systematically operating company, it is important to pay attention to all blocks TCM, because every company has costs, there are sales, there is operational money management, etc. At the same time, depending on the type of company, individual blocks of the total cash flow management system become especially important [ Table 1].

As can be seen from table 1, blocks such as Management accounting and budgeting, Organization of financial structure, Cost management, have practically same value for all types of businesses.

Sales Management and Marketing. Obviously, this block is especially relevant (or rather, critically important) for trading and service companies. These companies need to pay more attention to sales organization, searching, attracting and retaining customers, customer policy, sales planning, etc.

Working capital management. This block includes the management of accounts receivable, accounts payable and inventory. Management of receivables and payables is most relevant for wholesale trading companies. Companies of this type have many suppliers and many clients, high dynamics of work with clients, and accordingly the volume of work on accounts payable and receivable is several times higher than in other types of companies. At manufacturing enterprises, where the number of customers is relatively small, the issues of managing receivables are less acute, and in retail companies there are no receivables at all.

Inventory management is very important for both wholesale and retail trading companies, where the product range includes tens of thousands of items, and there is a need to maintain a constant supply of goods in the warehouse, which can lead to the freezing of large financial resources.

Attracting funding. The most important block for a manufacturing company, where the issues of finding sources and timely attraction of long-term financing are an important basis for ensuring the continuity of the production process, carrying out major repairs and modernizing equipment. For trading companies, this issue is also important, but the current crisis and, as a consequence, difficulties in attracting financing “to replenish working capital” are making adjustments here.

Operational money management especially important in trading companies. Here, a significant role is played by a large number of transactions within one day, high turnover of goods, which leads to the need for constant, daily planning and control of cash flow. In manufacturing companies, the dynamics of cash transactions, as a rule, is somewhat less than in trading companies. In service companies, planning and control of cash flows can be weekly.

Obviously, each type of business has its own specifics and characteristics. System advantage TCM is that it is possible to take into account all the nuances and, if necessary, place additional emphasis on certain elements of the system, ensuring balanced cash flow management.

RESPONSIBILITY STRUCTURE
or “No money again! Let’s go to the financial director...”

Studying the practice of many domestic enterprises allows us to draw a conclusion about several typical problems of cash flow management:

1. Carrying out cash transactions is not the same as managing cash flow. If operational money management is the clear task of the financial director, then most other elements of the system TCM other managers are responsible. For example, the biggest impact on positive cash flow is the sale of products to the client and the return of accounts receivable, for which the commercial director is responsible. And this is preceded by big job to study customer needs, market conditions, product selection, direct work to find customers, etc. In conditions of high costs or the impossibility of obtaining loans, ensuring the normal operation of the company begins far from the financial department.
2. “Skid” to the extreme. The first extreme: the financial (or general) director is a dictator who alone makes decisions regarding cash flow management. This problem is especially relevant in times of crisis. The result of this approach is “tied hands and feet” sales, logistics, etc. departments, and, accordingly, a decrease in business efficiency. The second extreme is the complete subordination of the financial department to the interests of other departments. Obviously, with this approach, the company will simply run out of money very quickly. Without downplaying the importance of certain management functions and the managers responsible for them, it is necessary to achieve a balance of actions.
3. Blurred responsibility and its shifting to colleagues. To avoid this, you need to very clearly define the role and responsibility of the manager involved in cash flow management. And, naturally, all (especially key) employees need to be able to understand each other and act together in the interests of the business.

Implementation of all system elements TCM depends primarily on the personnel who must take part in its functioning. The action of each employee, and especially the manager, is an operation (business process) that affects the occurrence of costs. Inaction is also a cost. For each of the system blocks TCM a specific manager must be responsible - the director of sales, production, supply, logistics, the head of a business line or branch, etc. For example, there is a very common misconception that only the financial director is responsible for managing costs and cash flow. But its main task is to prepare the conditions for effective management of costs and finances in general. And real management and responsibility should lie with the head of the specific department in which these costs arise or in which the movement of working capital is affected. Any management decision that a manager makes necessarily affects cash flows. Every manager involved in cash flow management must understand as clearly and clearly as possible:

• the essence of the tasks facing him and the degree of their influence on cash flow;
• your role and responsibility for carrying out these tasks;
• their motivation in performing these tasks.

In the process of development, implementation and further use of individual elements of the system TCM Almost all managers of the company take part, since everything is very interconnected, but it is necessary to identify responsible persons who will work in conjunction with the financial director.

As can be seen from tables 2, for each of the system elements TCM at least two people are responsible, thus ensuring effective interaction the financial department of the company with other divisions.

When determining the structure of responsibility, it is important to understand that the role of the financial director is mainly advisory, analytical, connecting, and training, and decisions on specific areas are made by the immediate managers of divisions, divisions, and business units.

Of all existing elements of the system TCM operational cash management falls entirely within the competence of the financial department employees.

OPERATIONAL CASH MANAGEMENT,
or “Can we pay this bill later?”

In conditions of economic crisis and limited resources, for many companies, operational cash management is one of the most important tasks in the field of cash flow management. This is due to the fact that the situation both in the company and in the market changes very quickly and sometimes unpredictably, the problem of non-synchronization of receipts and payments is becoming more acute, and cash gaps arise. In practice, it happens that a cash flow management system simply comes down to managing money on a daily basis. In these conditions, it is very important to be able to quickly respond to the situation, make adjustments to your plans, and constantly “keep your finger on the pulse” of the business.

THE GOLDEN MEAN IN OPERATIONAL MONEY MANAGEMENT,
or “The main thing is not to go too far in saving…”

Operational cash management is the responsibility of the CEO and CFO. At the same time, the views of the CEO and CFO on operational money management and on the business as a whole may differ slightly (or significantly). For the CEO, it is important that the business is alive and active, that goods are purchased and sold, that managers go on business trips, that promotions take place, new clients are attracted and sales grow. And the financial director in his work is guided by a simple rule: “if you can not pay today, we don’t pay.” This is not about deceiving anyone. It’s just that if there is an opportunity, for example, to pay later, to pay in installments, then the financial director will do everything to pay later or in installments. Each of these approaches is logical, reasonable and important, but individually these approaches are not viable in practice. Hyperactive activity will inevitably lead to huge cash gaps, rising costs and cash shortages. And the position of excessive savings will lead to a deterioration in relations with counterparties.

In the operational management of money, it is necessary to develop a balanced “foreign policy”. Distortions towards the aggressive or sluggish (inert) side can cause negative consequences for the company. For example:

• delayed payments to suppliers can complicate relationships with them, and too active payments deprive them of funds for other needs;
• overly aggressive measures to collect receivables lead to a loss of customer trust and loyalty, and passivity in this matter leads to an increase in overdue receivables.

The golden mean means that an overall balanced approach must be adopted that takes into account the interests of all parties.

OPERATIONAL CASH MANAGEMENT TOOLS,
or “When can my bill be paid?”

To the main tools for operational money management can be attributed:

• drawing up a payment calendar;
• daily reporting on balances and cash flows for all current accounts and cash registers;
• determining the priority of payments;
• regular payment of bills in installments;
• tightening the procedure for confirming and paying for supply, commercial and administrative expenses (cost of raw materials/products, delivery, services, travel, representation, etc.) with the identification of responsible persons;
• introduction of “payment days”;
• development of a business process for making payments.

Let's look at each of the above tools in more detail.

PREPARATION OF A PAYMENT CALENDAR,
or “You need to plan payments in the evening...”

For balanced money management, it is necessary to solve one very important problem - forecasting receipts and payments. Everyone is familiar with the problem of unsynchronized money flows. The situation when the deadline for necessary payments occurs earlier than the receipt of funds becomes especially relevant during a crisis. In essence, the solution to this problem is to learn to see in advance the pessimistic scenario for the development of the situation and to find possible solutions taking this into account.

- most effective tool operational cash flow management. It indicates the planned cash flow for a certain period by day/week, all receipts and payments, as well as a key indicator - net cash flow.

In practice, the payment calendar can be compiled in two forms.

The diagram is shown first on Figure 1, because this is the optimal type of providing information to the owner or general director. They do not need to know every figure for receipts and payments that are shown in the table. It is often enough for them to see the big picture and obtain fundamental information to make investment decisions. For example, the diagram shows the extreme points of the cash balance curve. This immediately signals a cash shortage during a certain period of time. Accordingly, it is necessary to take measures to shift some payments to a later period or accelerate the return of receivables, and possibly shorten the production cycle.

The second version of the payment calendar is presented in table 3— it contains detailed information about planned receipts and payments, broken down by day and by purpose of payment. This table is a tool for the CFO. As a cash flow professional, he needs to see a more detailed picture.

The payment calendar is an internal tool of an individual enterprise, so there are no mandatory requirements for its preparation. But from a practical point of view, it is still recommended to make a breakdown in the payment calendar by areas of activity, similar to the cash flow statement (CFS): operating, investment and financial. This type of report is universal and suitable for businesses varying degrees difficulties. The use of this type of payment calendar is fully justified in small companies, and in large holdings, because this format allows you to sort out all cash flow operations: operating activities, work with banks (credit lines, overdrafts, loan repayment), purchase or sale of fixed assets or other capital investments. In large holdings, where, for example, 300-400 payments are made per day, it is simply impossible to do without daily planning. In addition, due to the universality of this type of report, there is no need to rework financial statements when there are changes in the business itself, such as closing or opening new directions, creating branches or merging companies.

It is worth mentioning separately about small and medium-sized businesses, where, for example, investment payments do not arise so often. Correct use of financial statements allows them to clearly see the financial picture of the business. For the owner, the indicator of positive cash flow from operating activities is important for assessing the financial result of the work. Even in a simple business, if inventory are equal to zero, closed accounts receivable and the absence of debts show the equality of funds in the account and profit for the period or project worked. Then the owner can decide how to dispose of it (the profit). All of these planned and actual cash transactions, broken down into different types of activities, make the resulting net cash flow much easier to understand!

The advantages of using a payment calendar are efficiency and flexibility in managing cash flow. It becomes possible to anticipate the situation in advance and take appropriate measures. For example, 2-3 days before the scheduled payment, you see that there simply are not enough funds to make it. It is possible to notify the counterparty in advance, agree to make a payment later, or split the amount into parts. You can try to negotiate with the debtor on early repayment of his debt with some discount. Unfortunately, attracting bank financing in the form of an overdraft to smooth out cash gaps today is not only very problematic, but, most importantly, very expensive. Therefore, in modern conditions, the degree of importance, relevance and thoroughness of cash flow planning has increased significantly.

The proposed approach ensures continuity in the format and structure of articles between the payment calendar and the cash flow report, which is compiled by the direct method. Accordingly, a connection is established between daily planning and monthly budgeting, which makes it possible to control “limits” on individual expense items by responsible persons. On Figure 2 shows a scheme for planning and accounting for cash flows, which is used in modern software products ERP class.

FULL DAILY REPORTING ON BALANCES AND CASH FLOW,
or “Where did all our money go?”

If the cash flow in the company is very “fast” (that is, receipts and payments are made every day in large quantities), then these reports, despite their apparent simplicity, are important and necessary.

It would seem that you can call the chief accountant and ask what the situation is with account balances. But quite often there may be situations when the cash balance on the bank statement in the morning differs from what it was yesterday evening. Some receipts and payments were simply not reflected in the evening, but in the morning they were credited and processed by the bank. Another situation is that if we are talking about a group of companies, then an oral retelling of account balances will take about half an hour.

Therefore, in order to see the complete picture as accurately and quickly as possible, twice a day all managers involved in the cash flow management system must receive reports that contain all the accurate and up-to-date information. This creates a solid basis for effective cash flow management on a daily basis.

Report - Cash balances [table 4].

This report allows you to see the cash balances for each account for each day in the management accounting currency.

Report - Cash flow on the current account [table 5].

This report is intended for all operational managers with access to this data. It allows you to see the most important things - counterparties and the purpose of the payment.

These reports are quite simple, but their use is simply necessary to avoid absurd situations when, for example, a payment was made to a supplier for a product six months ahead of schedule (a real case from practice).

DETERMINING PRIORITY OF PAYMENTS,
or “How long can we go without paying?”

In today's business conditions, a situation often arises when the revenue plan is not fulfilled even by 50%, and the cash expenditure plan must be implemented to the maximum extent; accordingly, the total amount of requests for payment exceeds the actual volume of cash receipts. To avoid cash gaps, it is advisable to rank all payments according to their priority or importance. Items with the highest priority are paid without fail, while items with lower priority are either cut completely or paid off as the opportunity arises.

REGULAR REPAYMENT OF BILLS IN INSTALLATIONS,
or “Cash flow has its own seasonality...”

The point of this approach is that it is much more convenient to have one a large amount(for example, wages) pay in installments several times during the month, rather than accumulate one large amount for a long time for a one-time payment. Only taxes are paid immediately, and wages themselves can be repaid in installments. Of course, this approach must be agreed upon with the company team. But everyone needs to understand that in this case the interests of the enterprise come first. And it is better for employees to receive their salary in four installments than not to receive it at all (if there is no money in the company at all).

This approach can go a long way toward balancing the work of a company and its finance department. Wage in all trading companies it is usually 40-50% total amount all overhead costs. In a manufacturing company this figure is approximately 30-45%. And it is obvious that it is better to break up such a significant cost item and pay in parts rather than the entire amount at once. In this way, it will be possible to smooth out monetary “seasonality” and ensure the synchronization of payments and receipts.

STRENGTHENING CONFIRMATION AND PAYMENT PROCEDURES,
or “Why did the expenses for this item exceed the budget? Who is responsible for it?”

We are talking about the inclusion of a certain mechanism of bureaucracy, and in its best manifestations. Especially given the current economic situation, bureaucratic procedures today can bring real benefits to business. According to the concept Total Cash Management, for each expense item there is a clearly defined responsible manager. And this employee, being responsible for expenses, knows that he will be asked why this item was fulfilled in such a volume or was exceeded compared to the budget (plan). In addition, this manager personally signs invoices for payment of cost items under his control. And before putting his signature or stamp, the employee has every reason to ask himself the question “Is it possible to do without these expenses in this period?” Practice shows that this simple question sweeps away some bills right away. The invoices then go to a higher-level manager or employee, and some of them may also be rejected at this stage. As a result, we get a situation in which each employee in his area begins to think about the real feasibility of certain costs, and some of them very often turn out to be not so critical, or another more profitable solution for each of them is found. Only thanks to this principle can cost savings of about 20-30% occur. After all, in fact, you can always find opportunities to save.

It turns out that introducing clear responsibility for each employee is a conscious effort to improve the efficiency of business processes. If managers lack motivation, it will not be possible to reduce costs and no directive methods will help. And the introduction of common procedures for all employees allows you to involve staff in the process of optimizing the company’s costs.

INTRODUCTION OF “PAYMENT DAYS”,
or “Come see us next week...”

With an average small number of payments per day, and if the specifics of the business allow it, it makes sense to introduce so-called “payment days”. This means that bills for certain expense items or assigned statuses are paid on strictly designated days of the week or month.

This approach has a number of quite significant advantages:

• improves the accuracy of cash flow planning and eliminates cash gaps;
• internal processes in the company are automatically simplified;
• the time of controllers and accountants is freed up due to a reduction in document flow;
• managers spend less time on all approvals;
• There is an opportunity to save on banking costs, which are constantly increasing today.

There are also indirect, one might say “political” advantages of introducing payment days. Work with suppliers is simplified - there is no need to discuss the same issues every day: “Our payment day is on Thursday.” In addition, if, for example, the purchasing manager somehow managed to “skip” Thursday or postpone the payment to a later date, then the next payment due date is not earlier than the end of the next week, AND all claims that the supplier could make are redirected to the financial director, and he is no stranger to this. Therefore, today the use of “payment days” is a very good way both for direct cost optimization and for various “maneuvers”.

DEVELOPMENT OF A BUSINESS PROCESS FOR IMPLEMENTING PAYMENTS,
or “You didn’t submit your bill payment request on time...”

Despite the fact that this tool is given last, it is often one of the main ones. It is extremely important for a business that all procedures are spelled out in detail in a special document - “Regulations for operational cash management”. As a rule, it defines the following points:

• a list of financial responsibility centers for planning and monitoring cash flows;
• responsibility matrix, which provides a list of participants in the process (payment initiator, controller, acceptor), assigning their responsibilities and powers;
• development of a time schedule for payments - establishing the timing and sequence of processing applications for payment.

Every manager involved in cash flow management in his place should know:

• monthly budget preparation procedure;
• sequence of preparation, approval and implementation of payments.

The main result of introducing a business process for making payments is saving time on approvals, and, accordingly, increasing the efficiency of work performed by employees in the area of ​​their immediate responsibilities.

IMPLEMENTATION OF OPERATIONAL CASH MANAGEMENT,
or “Where to start?”

The sequence of steps for establishing operational cash management may differ depending on the specifics of the enterprise, but will always include the following actions:

1. Identification of all accounts and cash desks with the appointment of responsible persons for accounting and control over them.
2. Direct daily accounting of cash flows in a simple form to strengthen control and eliminate technical errors.
3. Determining the materiality of payments by amount or type/item of payment and/or counterparty.
4. Appointment of authorized persons for the formation and approval of applications for the expenditure of funds.
5. Development of a business process for making payments and the document “Regulations for operational cash management”.
6. Introduction of weekly control by the financial department over budget implementation with a forecast until the end of the month.
7. Carrying out daily cash flow planning.

An essential factor in ensuring speed and High Quality preparing information for operational cash management is the automation of this business process. For companies with a large number of operations application MS EXCEL today can take place at the initial stage of system implementation TCM. This is a very labor-intensive process. Therefore, it is advisable to take conscious action to implement ERP-systems. Then it will be possible to involve employees from all departments in joint work, which will ensure one-time input of all data and significantly reduce the cost of processing it, as well as reduce the number and cost of erroneous data. management decisions.

SUMMARY

In the current environment of economic downturn, instability and limited resources, Total Cash Management is a very useful management concept, and the winners will be those companies that can make the most of its benefits.

The main one is that TCM makes it possible, with the help of coordinated and consistent procedures, to “hold in your hands” the main indicator of the business - net cash flow, and also direct all actions to ensure its positive value.

Nikolay LYSENKO, managing partner and leading consultant of System Business Consulting.

Is it possible to build a house using hand tools and a ten-year-old plan? Of course you can. However, few will agree to this, given the power tools and updated plans available today. Similarly, analysts can continue to develop analytics processes using only custom code and traditional methods. However, if you look at the opportunities available today, few people will want to do this. Today, a great home can be built with less physical effort; the same is true for analytical processes.

For many years, analysts have used tools that allow them to prepare data for analysis, run analytical algorithms, and evaluate the results. The increase in functionality of these tools is not surprising. In addition to much richer user interfaces, tools now provide the ability to automate or streamline common tasks. As a result, analysts can devote more time to analysis. Combining new tools and techniques with more mature processes and scalability will give organizations the opportunity to tame big data.

This chapter will discuss how analysts have changed the way they build analytics processes to better take advantage of the new tools and scalability available. We'll cover group modeling, product modeling, and text analytics, as well as how the analytics tool space has evolved and how these advancements will continue to change the way analysts work. We'll talk about point-and-click interfaces, open source tools, and data visualization tools.

Evolution of analytical methods

Many commonly used analysis and modeling approaches have been in use for many years. Some of them, such as linear regression or decision trees, are effective and relevant, but are greatly simplified. Simplicity used to be dictated by strict tooling and scalability constraints, but today's capabilities allow you to do so much more.

Before the advent of computers, it was impossible to make multiple iterations of a model or apply complex methods. As the scale of data processing technologies has increased, so has the scale of the tools and methods used to analyze them. Today, it is possible to apply a variety of algorithms to large data sets many times.

Often, as a result of increased scalability, specialists simply have to resort to the same established methods more often. However, many analysts are beginning to adopt new methodologies that make better use of improved tools, processes, and scalability. Many of these new methods have long been known, but until recently they were not put into practice. These are group methods, express modeling and text data analysis.

Ensemble methods

Group approaches are conceptually quite simple. Instead of building one model using one technique, multiple models are built using multiple techniques. Once the results from all models are received, they are combined to determine the final answer. You can use anything from a simple average to a much more complex formula to combine different results. It is important to note that group models go beyond selecting the best model from a set. In this case, the results of several models are combined to provide one final answer.

The power of group models is that different methods have their own advantages and disadvantages. For example, some types of clients may receive a poor rating using one technique, but a very good rating using another. Combining data from multiple models improves the scoring algorithm overall, if not literally, for each customer, product, or store location scored.

Let's say linear regression, logistic regression, decision tree and neural network. The estimates obtained from each model will be combined into one using a group approach. Often this combination provides a more reliable prediction of purchase completion.

Ensemble methods in Data Mining by John Elder and Giovanni Seni11 are the subject of an excellent book by John Elder and Giovanni Seni11. Group approaches have gained popularity due to the evolution of analytical tools. Without a good way to manage workflow and aggregate results, group modeling is a very cumbersome process. Imagine the prospect of manually running the process for each method used. After each process is completed, all results must be manually combined to evaluate how each method performed on the task. Finally, imagine that you need to decide how to combine the results into a single answer. Today, analytical tools can do most or even all hard work for you.

Wisdom of the crowd

Each individual modeling method has strengths and weaknesses. By combining different results, we will get a single answer, which may be better than the result of individual models. This is similar to how the average answer, based on the predictions of many people, can be close to the correct one. This phenomenon is often called the wisdom of the crowd.

One of the reasons for the growing popularity of group models is the simplicity of the theory behind them. The wisdom of crowds in everyday life has been studied quite widely (see James Surowiecki's book The Wisdom of Crowds). The Iowa Electronic Market at Iowa State University has demonstrated for many years that the educated guesses of many people, on average, often come close to the correct answer. In fact, the average may come closer to the correct answer than any of the individual answers.

The group method applies the concepts outlined in the book The Wisdom of Crowds to analytics. Many models that make educated guesses about the relationships being explored will, on average, come very close to the correct answer. Can group modeling solve all of an organization's analytical problems? Of course not. However, organizations should add them to their repertoire of methods.

Express models (commodity models)

One of current trends is the use of so-called express models. We define an express model as one that is created quickly and without much effort to fully realize its full predictive potential. Express models can be created, for example, automatically using a simple stepwise analytical procedure. The goal in this case is not to build the best model, but to quickly create at least some model that allows you to get an acceptable result.

When used properly, express models are very useful within an organization. Previously, building models required a lot of time and money. Analysts spent weeks or months just collecting data and then applying the models they created to that data, so models were created rarely and only to solve very important problems. If you were to send out 30-40 million sales letters, it would be worth investing in creating a model. However, if we were talking about the upcoming mailing of 30,000 offers regarding an inexpensive product, then it would not be profitable to invest in creating a model.

If analysts use modern environments, including scalable sandboxes, and modern processes, including enterprise analytics datasets, then building a model will take much less time than before. The more accessible these standard variables are, and the more computing power that can be applied to them, the easier it is to create models.

Always remember that the ease of creating a process does not mean that you can neglect the need to ensure that the process is appropriate. However, if it is managed by a good analyst, you will achieve your goal much faster.

Sometimes "good enough" actually means "enough"!

Express models are designed to improve results where you otherwise would not use any models at all. This is a lower bar than what most models have always tried to clear. The process of creating an express model stops when a sufficiently good result is achieved. This process is well suited for problems of low importance or for situations where there are so many models to be created that improving them is not pragmatically justified.

When evaluating an express model, the focus is on the benefit that comes from using it. With more effort, a lot could be improved. However, if a fast model will help in a situation in which the model would not otherwise be used, then it is used.

Let's give an analogy. If you have a house, then you will try to make some parts of it as comfortable as possible. The kitchen, for example, requires a particularly careful approach. Other times you just need to get the job done. It is possible that when remodeling a guest bathroom you are using the most ordinary materials, since there is no point in investing large amounts of money in this room. Express models help in such business situations and have a wide range of applications. Let's look at some of them.

Methods of using express models

Express models enable you to apply advanced analytical techniques to a much wider range of problems and at a larger scale within an organization than is possible when analysts have to manually create model after model.

Thus, retailers often create “purchase propensity” models for important product categories. There is no point in creating a special model for slow-growing and less frequently promoted categories. The grocery chain should create a model for products such as bath cleaners and sodas. It doesn't make sense to create a model for products that are in less demand, like shoe polish or sardines.

But what if there is a need to promote less important products? Let's say a sardine manufacturer is willing to sponsor a promotion for its products. Some retailers today have models for all of their many product categories. Many of them are express models. They are created in case they are needed, and in these situations they can provide some additional value. Important categories such as carbonated drinks or bathroom cleaners continue to receive special attention, with separate, more complex models being created for them. However, the use of express models allows for less important categories goods at least with the simplest model.

Today, analytical tools make it easier to create such models. They now have the ability to automatically execute algorithms with many combinations of indicators and several automated verification methods. This allows you to quickly create a pretty good model. Less important tasks will require a different approach. In fact, there is nothing wrong with using a good enough model instead of the best one when the situation calls for it.

Let's consider how to use express models for forecasting. Imagine a manufacturer that needs to provide as reliable forecasts as possible about demand levels, such as by quarter, by product, and by country. What if he needed to forecast demand at each store or point of sale for each week for each individual product? There simply aren't enough man-hours for high-quality forecasting. In such cases, it makes sense to create automated forecasts that are good enough. If the top-level forecasts are accurate, and the aggregate of low-level forecasts matches that accuracy, then the manufacturer will be satisfied. In this case, it will have advantages compared to the absence of any forecasts.

The most important thing is to make sure that you are using a process that generates good enough models. It is necessary to regularly recheck the process of developing express models and meaningfully evaluate their results. The process of creating express models should not be left to chance and allowed to work without any intervention at all.

Text analysis

One of the fastest growing techniques used by organizations today is the analysis of text and other unstructured data sources, which includes a significant portion of big data. Text mining, as the name suggests, takes some text as input. It can be a recording - an email, a transcript of a voice recording, or even scanned text converted into electronic form, such as old court transcripts. The reason for the growing popularity of text analysis is the wealth of new sources of text data.

In recent years, everything has been recorded, from Email and comments on social networks such as Facebook and Twitter, to online inquiries, text messages and conversations with call center agents. Extracting meaning from all this textual data is a challenging task. There are challenges associated with parsing, defining context, and identifying meaningful patterns. Organizations have more unstructured and text data than traditional, structured data. And these types of data cannot be ignored.

Text is a widespread type of big data, and the tools and techniques for analyzing it have come a long way. Today, there are tools that help you parse text into its constituent words and phrases, and then determine the meaning of those words and phrases. Popular commercial text analysis tools are offered by companies such as Attensity, Clarabridge, SAS, and SPSS.

By breaking down text into its components, you can determine their mood or meaning and identify existing trends. Models are often applied to summary statistics about parsed text. For example, how many of a particular client's emails are written in a positive or negative tone? How often does a given customer focus on a specific product line in their communications? This allows you to structure raw information. This method of parsing and structuring text is often called information extraction.

It is important to understand that unstructured data itself is not analyzed. First they undergo processing, as a result of which they are given some structure. These structured results are then analyzed. Remember the TV series in which detectives identify a criminal. A fingerprint is taken, then various dots are applied to it and connected to each other. Finally, detectives find a match and identify the culprit. In this case, a comparison is made not of the original unstructured print, but of the structured form created based on its pattern. This approach is typical for analyzing sources of large unstructured data.

Unstructured Data Analysis

Typically, unstructured data itself is not analyzed. First they undergo processing, as a result of which they are given some structure. The structured results are then analyzed. Very few analytics processes analyze and draw conclusions directly from data that is in unstructured form.

Applying context to text data is challenging. There are certain methods, but the process always involves some creativity. The fact is that the same words can have different meanings. If I call you crazy, it will be taken as an insult. However, if I say I just went down a crazy ski slope, what I mean is that the ski slope was amazing. Analyzing text is even more difficult because individual words alone often do not tell the whole story, and the way those words are pronounced is much more important. Intonation can completely change the meaning of a sentence.

An excellent example is given in table. 1. The meaning of the entire sentence changes when the emphasis moves. If you see and hear a person speaking, you can easily understand what he means. When you only have text, it is impossible to understand it using only a statement. The sentences that surround a particular utterance help to clarify what the speaker meant, but going to this level of analysis makes the task even more difficult. This is why text analysis will remain a challenge for some time.

Table 1. How accent can change meaning

It is absolutely necessary for most organizations to start using text mining techniques. Text mining is evolving from a technique with a limited scope to a technique that impacts a wide range of industries and tasks. This is one example of the new types of techniques that need to be developed to enable processing of unstructured big data sources.

Tracking Emerging Methods

New methods for solving new business problems are constantly emerging. You must strive to ensure that your organization uses the latest advances. If it applies to your business new method or approach, someone will need to figure it out. Let's look at several methods that were used rarely at first, but then became ubiquitous. These examples demonstrate how quickly a rarely used method can become widely used.

Collaborative filtering has similar goals to proximity analysis. Both approaches are used to identify what a particular customer might be interested in based on the interests of other, “similar” customers. Collaborative filtering is used on sites all over the world today and is a fairly fast and reliable way to get decent recommendations. In fact, it is usually implemented in the form of an express model. The basic approach is easy to deploy and quickly produces fairly good quality recommendations. With the development of the World Wide Web, collaborative filtering has become quite widespread and influential. Ten to fifteen years ago this method was not so well known.

The page ranking algorithm is the method that underlies Google's activities. Google uses it to determine the most relevant links to present to users when processing a search query. All other search engines have their own version of the page ranking algorithm. Today, most individual sites have a built-in version of this algorithm used when performing searches on the site. These methods have only recently been developed and were not used until the advent of the Internet era.

Most of the population had never heard of collaborative filtering or page ranking. A generation ago, most people might never have encountered these methods in their entire lives, but in the last few years they have become widespread. Millions of people surf the World Wide Web. use these analysis methods every day, whether they realize it or not. In the coming years, other methods that are currently virtually unknown will become widespread. Every organization should ensure that it has people to monitor the emergence of new methods. You can learn about them at analytical technology conferences, in specialized magazines, articles and blogs, or from experts from other companies.

The evolution of analytical tools

When I got into analytics in the late 1980s, the concept of “user friendly” did not exist. All analytical work was performed using mainframes. In order to carry out the analysis, not only did you have to write the program code directly, but you also had to use the terrible Job Control Language (JCL). Anyone who has ever encountered JCL knows what a headache it is!

When servers and PCs became widespread, they were basically the same old software interfaces with new platforms. Graphics and data output were in their infancy at that time. Originally, graphs were generated using text characters to create bar graphs, and dashes were used to draw grids. When outputting data, you received a huge amount of text describing what happened.

Over time, additional graphical interfaces were developed that made it possible to use point-and-click environments instead of coding. Virtually all commercial analytical tools had such interfaces by the late 1990s. Since then, user interfaces have been further enhanced to include more powerful graphics, workflow diagrams, and applications that focus on specific point solutions. Workflow diagrams are one of the most useful new features because they provide analysts with a visual map of individual work steps and related tasks. This allows you to visually track all steps of the process.

As tools evolve, so does their scope of application. Today, there are tools for managing the deployment of analytical processes, managing and administering analytical servers and software used by analysts, as well as tools for translating code from one language to another. In addition, a number of commercial analytical packages are available. Although SAS and SPSS remain the market leaders, there are many other analytics programs available. Many of them occupy a specific niche, covering specific areas. In addition, open source analytical tools have now been created.

Proliferation of graphical user interfaces

Until the mid- to late-1990s, the only option for performing statistical analysis involved writing code. Many people, especially old-school analysts, still love to write code. Meanwhile, user interfaces are becoming the norm, and analysts no longer need to spend a lot of time coding. Graphical user interfaces available today allow a lot of code to be generated "under the hood" on behalf of users.

You'll often hear heated debates about whether "real" professionals use a GUI or whether they just write code. In reality, no one should have any problems using a GUI as long as it works reliably and allows you to develop analytical processes at a pace that is equal to or faster than manual coding. True analysts do everything they can to get the job done as accurately and efficiently as possible. In addition, software today provides robust solutions that not only generate code quickly, but also guide users through a predefined process aimed at solving specific problems.

An additional benefit of the user interface is that the automatically generated code is quite optimized and error-free. This is different from manual coding, where typos are common, debugging is required, and the degree to which the code's performance is optimized depends on who wrote it. Early versions of analytical user interfaces were quite cumbersome, and if a person knew how to code well, it was faster to write the code than to use the interface. This has all changed with the advent of new user interfaces that effectively automate the generation of large amounts of code. This allows you to pay more attention to the analysis itself and the necessary methodologies and spend less time on coding.

One danger with user interfaces is also one of their key benefits: interfaces make it easy to generate code. It sounds tempting, but the ability to quickly generate code also allows you to quickly generate bad code. If the user is not a professional, then using the user interface he can accidentally create code that will do something completely different from what was intended. Without understanding the generated code, the user is unable to identify such situations, and this can lead to the developed processes being incorrect or inaccurate.

No need to be old-fashioned

Many user interfaces available today can actually speed up the code generation process while ensuring error-free and optimized code. Experts should give today's interfaces a chance. The results may surprise them! This is especially true for those who have been coding for decades and are resistant to any other means. The tools will make analysts' work more efficient, freeing up time to focus on analysis techniques instead of writing code.

Point solutions include, for example, applications for price optimization, fraud detection and demand forecasting. Point solutions built on top of toolkits such as SAS use some of the common functionality of the base package, but the user interface is customized to solve specific problems. It can take a long time to develop a point solution. Organizations should consider purchasing such a solution instead of building their own. This can save both money and time.

An application for a financial institution to help detect money laundering, for example, must include a set of algorithms and business rules that find suspicious patterns in the movement of funds. The interface of such a tool will be configured to identify suspicious cases and provision as needed additional information to assist in the investigation process. Such a tool can help an organization get up and running quickly without having to develop multiple processes from scratch.

Analytics point solutions are gaining popularity as they enable different departments within an organization to incorporate more sophisticated analytics into their day-to-day business processes. Generally, a high level of knowledge is required to install, configure, and configure settings for these tools. However, their maintenance and use are within the capabilities of less trained people, which significantly expands the user base of point solutions. Note that this does not change what was said about people not using tools if they don't understand coding. Point solutions are built and configured so that the user takes the most appropriate actions.

Users of analytical point solutions tend to be more advanced than ordinary employees. However, they will not have the same skills as professional analysts. Tools that are configured and tuned by experts will automate many tasks, so that an experienced user can effectively monitor the results of the tool and make sure everything is working properly. The benefit of this approach is greater adoption of analytics across the organization and greater scale. No organization will ever have enough analysts to perform all the required analyzes manually. Analytical point solutions relieve some of this burden.

Use point solutions

Analytics point solutions are a great way to tackle specific business problems. Such tools allow more people to be involved in the analytical process. Using a ready-made commercial point solution is much faster than creating your own. However, be prepared to be shocked when you see the prices of some of the tools available.

A major disadvantage of point solutions is that they can be quite expensive. Some point solutions cost on the order of ten million dollars, or more for an enterprise-wide tool. If the ROI justifies the expense, then it's acceptable. However, the typical organization cannot spend enough money, time and effort to implement multiple point solutions, so they are often used sequentially: as one solution is completed, another is started.

In the coming years, point solutions will be developed for some aspects of big data analytics. Perhaps these are exactly what organizations will need to begin such work. As you plan your actions, you should study the market to learn about existing opportunities.

History of open source software

Open source software packages have been around for quite some time. They are available to everyone and can be downloaded for free. Additionally, the code itself is also available so users can customize and add features to the software if they wish.

Examples of widely used and highly successful open source applications include the Firefox web browser, the Linux operating system, and the Apache web server. The rise of the Internet has fueled the growth of open source software activity. Considering all the innovations that have appeared in the Internet space, it is quite natural that they are accompanied by innovations in open source applications.

There are now a wide variety of open source software packages: databases, business intelligence and reporting applications, data integration tools, office suites, etc. In some cases, such as Linux and Apache, a set of open source tools source code has become the accepted choice, if not the leader, in its field. In many other cases (office tools), open source software fills a specific niche. In general, large and/or long-established corporations are slower to adopt open source tools than new businesses or academia.

The great thing about open source tools is that thousands of people contribute to their functionality. A detected error can be quickly corrected by numerous enthusiastic developers who work in their free time. Major open source projects are supported by formal organizations. There are organizations that are made up entirely of volunteers; The non-profit enterprises established to manage the project employ full-time employees. These organizations are able to pay employees through donations, but they are not trying to make money from the software itself. The goal is to receive enough money in the form of donations and, by paying specialists, to ensure effective management of the project. In the future, open source software will continue to have an impact, including in the area of ​​analytics. This brings us to the R project.

Project R for Statistical Computing

Open source software has entered the world of advanced analytics in the form of the R Project for Statistical Computing, also known simply as R. R is a free, open-source analytics package that directly competes with, as well as complements, commercial analytics tools. R is a descendant of S, one of the first languages ​​for statistical analysis developed decades ago. Project R apparently got its name due to the fact that it was an update of S, as well as the fact that the names of its creators (Robert Gentleman and Ross Aiheka) begin with the letter R.

Project R quickly gained popularity and is currently used by numerous professional analysts. This is especially true in academic and research environments. In a corporate environment, if you have a large team of analysts, at least some of them use R in some way.

Commercial tools still dominate, but R's influence is gradually growing. Although its user base is rapidly increasing, it is not yet as well established in large enterprises as it is in academia. The R language is typically used for research and development rather than large-scale, production-critical analytical processes. This may change over time, but this is the situation at the time of writing.

The R language has a wide range of capabilities. He is in to a greater extent object-oriented than many other analytics toolkits. Can be linked to common programming platforms such as C++ and Java, allowing R code to be embedded in applications. In fact, commercial analytics packages even allow you to run code written in R as part of their toolkits. This is a very useful feature. More detailed description This topic is beyond the scope of this book.

Perhaps the greatest advantage of the R language is that whenever a new modeling or analysis method comes along, someone will implement it in the language. The functionality of R is updated much faster than the functionality of commercial tools, and if you think about it, that's how it should be. A commercial tool vendor will not rush to integrate a new algorithm until it is convinced that there is demand for its use. Once convinced of this, the vendor adds the algorithm to its release schedule, generates the code, and includes it in a new version of the tool. This may take years. In the case of R, the code for an algorithm is created as soon as several people find it useful.

The fact that R is distributed free of charge is a definite advantage for many. However, as with any open source project, there are companies that offer their own paid extensions and/or services. These companies can help you use R, develop processes in R, and in some cases provide you with extensions that improve the functionality of the base package. The downside of free software is the lack of support. You have to more or less find the answers to the questions on your own. Despite the existence large community, there is no specific person or team in charge that you can turn to.

Are you using R?

R is a rapidly growing open source set of analytical tools. In recent years it has evolved greatly and become widespread. R has its advantages and disadvantages and is not suitable for every organization or every task. However, it may have a role to play in your organization.

One of the main disadvantages of the R language is that programming with it is a fairly intensive process. Despite the existence of graphical interfaces based on the R language, many users today still prefer to write code. In addition, R interfaces are much less mature than similar interfaces for commercial tools. Of course, this may change over time.

Perhaps the biggest drawback of the R language is its poor scalability. There have been some improvements recently, but R's level of scalability does not match that of other commercial tools and databases. The R compiler processes data in memory. This means that it can only work with data sets that are the size of the computer's available memory. Even a very expensive computer has much less memory than is required to work with enterprise data sets, let alone big data. If large organization wants to tame big data, R can be part of the solution, but not the only one, at least for now.

All larger number tools, including commercial analytics packages, make it possible to use the R language. Will it become a leader like Apache or Linux? Will it remain a niche product like open source office suites? Only time will tell what role R will play in the advanced analytics space.

History of data visualization

Data visualization is as old as data itself. Recently it has become a separate industry. People like Edward Tufte make a living discussing, researching, and evaluating imaging techniques. Tufte wrote numerous books, including the classic Visual Display of Quantitative Information.

The destruction of Napoleon's troops during the campaign against Moscow in 1812, depicted by Charles Joseph Minard, is considered one of best visualizations of all times. By looking at this image, following the link in the chapter notes, you can clearly imagine what happened to these troops.

Visualization in the world of analytics refers to charts, graphs, and tables that display data. Before the advent of computers, graphics were drawn by hand. Computers have revolutionized and simplified the way we create visualizations. I remember my first color printer, a Radio Shack Color Computer. It literally had little colored ballpoint pens drawing on a piece of paper that looked like a wide check strip. I could only create some very primitive low resolution bar charts.

Early analytics software was quite clever at using keyboard symbols to create graphics that might not be pretty, but were very good at getting the point across. Each bar of the diagram could consist of a series of X symbols (see Fig. 1); the pie chart was made up of dots, commas and dashes, and the table frame was drawn using the symbols “” and “|”.

Rice. 1. Elementary bar chart

When office applications became widespread, almost anyone had the ability to create colorful charts or graphs with axes, labels, and legends. The graphical capabilities of analytical tools have also evolved greatly and have gone far beyond the creation of graphs consisting of text symbols.

However, until recently, visualizations were largely static. A chart in a desktop presentation application or spreadsheet remained static until it was updated, usually manually. Today, visualization tools exist that allow you to interact with graphics, exploring and analyzing data in new and more powerful ways.

Modern visualization tools

Visualization tools have evolved so much that many people don't realize all the possibilities that exist. Tools like Tableau, JMP, Advizor, and Spotfire help professional analysts and business users go beyond graphics that simply illustrate a story that's already been developed. Visualization tools allow the user to develop a new story using an interactive visual paradigm.

Today's visualization tools allow you to create multiple tabs with graphs and charts linked to your source data. More importantly, tabs, graphs, and charts can be linked to each other. If the user clicks on the bar for the Northeast region, all other charts will instantly adjust to show data related to that region.

Think of these new tools as presentation and spreadsheet software on steroids. Not only do some visualization tools have the same data manipulation capabilities as spreadsheets, but they also have graphing capabilities that rival or even exceed those of presentation applications. Now add to this the ability to connect to large databases, use visual tools and drill down into data. The result is something very powerful.

The basic premise of data visualization is that it can be very difficult to make sense of large tables or sets of numbers and identify trends. It is much easier to see trends if a suitable visual representation is used. Some visualizations, such as graphs displaying social media data, convey information that would be nearly impossible to understand or describe without the visualization.

Just imagine trying to clearly explain to a person how countries are located on a map. When you have a map in front of you, you know exactly where countries are located relative to each other. It would be very difficult to come up with even a very voluminous explanation that could compare with the map in terms of information content and clarity.

A new idea of ​​immersive intelligence has emerged, which is not yet available in commercial tools. It involves the use of 3D graphics, online worlds like Second Life, and sophisticated visual tools (such as those used in genetic research). These technologies are used to present data interactively. Will it be possible to navigate data in an interactive 3D environment to gain new insights? Time will show.

Don't talk - it's better to see once

The human brain is very good at interpreting visual information. Effective visualization can help you easily recognize a pattern or trend. When looking at traditional spreadsheets or reports, it can be difficult to see what you're looking for and easy to miss important relationships. A picture in the form of an effective data visualization can say more than a thousand words.

Visualization literally helps you see new ideas that would otherwise be impossible to discover. Professional analysts are now using these tools to develop analytical processes and data exploration; Some professionals use visualization tools solely to create graphics and presentations. These tools are much faster and more reliable than traditional graphical ones. Additionally, if someone asks a question during a presentation, you can analyze it and get the answer right during the presentation, without having to promise to create a new chart and send it the next morning. Any organization looking to tame big data should consider adding visualization tools to their toolboxes.

The Importance of Visualization for Advanced Analytics

A professional analyst constantly has to explain complex analytical findings to non-technical business people. Methods that allow this to be done more efficiently should be used. Data visualization falls into this category.

Why go into all the details of logistic regression if you don't have to? Including all the parameter estimates, deciles, and model estimation statistics is unnecessary if a simple incremental plot will tell the business sponsor all he needs to know. The details are useful as a backup, but business sponsors should not be concerned with technical details. They trust their analysts to take care of them.

Few people would prefer to see a long list of business rules instead of a visual decision tree. What if the casino or retail store need to identify the busiest areas? You can create many tables, lay them out on the table and try to find patterns in your mind. Or you can make a heat map of the floor of a casino or store, where the color indicates the level of activity. The answer to the question posed will be immediately obvious.

It's the impression that matters, not the external effects.

It is important that the visualization makes the idea immediately obvious. Too many people get caught up in fancy graphics just because they can afford it. Simplicity - best option Effectiveness or complexity must be justified.

Note that we're not talking about graphics for graphics' sake here. Many people use over-the-top or overly complex graphics simply because they are easy to create. A 3D bar chart does not add any analytical value over a 2D bar chart and may even make it more difficult to read. The focus should be on effective, compelling visualization that helps illustrate the idea more clearly. Pretty graphics that serve no purpose can distract from the main message and lead to confusion.

In some cases, a simple table is sufficient. In others, a relevant visualization can help the audience understand the idea much better. Remember the example with the map. If analysts understand how to effectively visualize data and results, it will help them become more efficient and successful in their work. Visualization tools are just beginning to make an impact. In the future, they will be used more and more often in the process of analysis and presentation of its results.

New data is more important than new tools and methods

New input data will have a greater impact on the model than a new tool or method. Adding new data to a traditional process will provide greater impact than applying new tools and techniques to old data. That's why it's important to learn how to work with big data, not just update how you work with what you have.

This chapter focused on advances in tools and techniques. However, it must be remembered that new data has a greater impact on the quality and effectiveness of analytics than the tools and methods themselves. Thus, for example, the availability of detailed web data on consumers that was not previously available will contribute more to the quality and efficiency of the propensity model than to the achievement of the logistic regression or panel method used to build the model. New tools help you get the most out of new data sources, but the data itself is the more important factor. This is why it is very important for organizations to leverage the big data sources available to them.

The most important lessons of this chapter.

• Group methods rely on the concept of the wisdom of crowds. Combining estimates from multiple approaches may provide a better answer than each individual approach on its own.
• The point of using express models is to quickly obtain a good enough model, if possible automatically. In this case, achieving maximum efficiency is not an end in itself.
• Express models allow you to use modeling to solve less important problems, as well as problems that require the creation of a very large number of models.
• In the era of big data, text analysis has become especially important. Methods for working with text data are developing rapidly and are becoming widely used.
• The difficulty with text analysis is that words alone do not tell the whole story. Accent and intonation have great importance, however, there is no information about them in the text.
• User interfaces have passed big way development and in this moment include powerful graphics tools, visual workflow diagrams, and focused point solutions.
• User interfaces should be used as productivity tools for people who know what they're doing and can make sure that the tools under the hood are doing what they're supposed to do. The user-friendly interface makes it easy for technically unskilled people to do something wrong.
• Analytics point solutions are designed to efficiently solve a narrow range of analytical problems, such as fraud detection or pricing. Such tools are becoming increasingly popular.
• R is an open source analytics tool that has gained widespread adoption in recent years. The advantage of R is the speed of adding new algorithms, but the disadvantage is that it is currently impossible to ensure scalability to the enterprise level.
• Seeing a pattern is much easier than explaining it or identifying it with a bunch of data tables. Modern visualization tools allow you to connect to a database, create interactive, interconnected graphs, and provide many more visualization options than traditional graphics tools.
• Data visualization does not mean using fancy graphics, but rather displaying data in a way that allows you to better understand the message being conveyed.

Based on a study of the evolution of management development in the second half of the 20th - early 21st centuries. concepts that implement a strategic approach to management have been identified. These include strategic planning (budgeting), management, marketing, as well as the concepts of strategic management accounting and strategic analysis. Of key importance in their emergence are the objective needs of intra-organizational management in the formation of the strategy of an economic entity due to the increased dynamism of environmental factors and the need to provide economic entities with sufficient competitiveness. Under these conditions, strategic management accounting is considered as an adequate tool for strategic management, which determines the relevance of identifying instrumental capabilities of an analytical nature. The starting point was the study of the concepts of “strategy” and “strategic management accounting”, which made it possible to identify a variety of characteristics that form the basis for the development of definitions. From the standpoint of establishing strategic goals (activities of an economic entity in relation to its own position in the market; profitability of products, other segments; productivity; resource provision; management of the organization and personnel, etc.), two areas of strategic assessments are defined: external strategic analysis (analysis of competitors of an economic entity) and internal analysis (analysis of the resource potential of an economic entity). Their implementation reveals the need for information and instrumental support, which determines the content of strategic management accounting. The article evaluates the information capabilities and information needs of strategic management accounting for the purpose of analyzing competitors, analytical support with strategic management accounting tools. To carry out a structural analysis of competitors among such tools - analysis of the life cycle of competitors' products; analysis of competitors' performance indicators; analysis of technologies and the experience curve of competitors. To analyze strategic positions and competitive advantages, strategic value chain analysis is considered as a tool for strategic management accounting. The presented differentiation of the structure and composition of analytical tools for strategic management accounting determines the directions of its methodological support in organizing and maintaining strategic management accounting in economic entities of various organizational and legal forms.

The concept of Strategic Management Accounting (SMA) in global accounting practice (Great Britain, USA) began to take shape as a result of the implementation of a strategic methodological approach in management science and attracting the attention of specialists to management issues based on a strategic vision of problem solving. This led from the 1970s to the 1980s. to the emergence of a new direction in the development of management - strategic management. In the 1950s - 1960s. its creation was preceded by the implementation of the concept strategic planning(budgeting) (Strategic Planning (Budgeting)). In the 1980s - 1990s. within the framework of strategic management, the concepts of strategic marketing (Strategic Marketing) and strategic cost management (Strategic Cost Management), subsequently - strategic management accounting (Strategic Management Accounting) were formed. During the same period, due to the use of analytical tools in strategic management, its associative understanding as strategic analysis (Strategy Analysis) arose. In the 2000s. The strategically oriented concept of Value Based Management was developed (Table 1).

Table 1

Concepts that implement a strategic methodological approach to management

Of key importance in the emergence of these concepts are the concept of “strategy” and the increased attention of intra-organizational management to increasing its role, which is determined by the emergence of a dynamic environment, the need for economic entities to ensure sufficient competitiveness in it based on the formation of their own competitive advantage.

Under these conditions, strategic management accounting began to be considered not only conceptually, but also from an applied perspective as an adequate tool for strategic management. To understand it as a type of practical activity and as a science, a study of the evolution and content of strategic management is required. This will ensure the identification of instrumental resources of strategic management accounting, primarily of an analytical nature.

From the standpoint of evolutionary knowledge, it is known that in the first quarter of the 20th century. classical schools management - school scientific management(F. Taylor, G. Gant, H. Emerson), the classical (administrative) school of management (A. Fayol, M. Weber, C. Bernard) - management functions were differentiated. Planning in the form of budgeting and control was recognized as the leading one among them. It was based on the recognition of the objective stability of the environment, the sustainability of the resource supply of an economic entity, which made it possible to draw up annual (short-term) budgets for the organization’s income and expenses.

In the 1950s The development of scientific and technological progress, the emergence of transnational corporations, and the saturation of the market with goods have led to the need for long-range planning as a future-oriented management tool reflecting the prospects of activity. This determined a shift in emphasis from current short-term management and planning to long-term, long-term management.

In the 1960s objectively insufficient stability of the environment, due to increased international competition, required a conceptual revision of the provisions regarding long-term planning (budgeting) of the organization. The plan (budget) began to be considered as a set of alternative actions, possible, expected due to environmental changes, and determine the strategy commercial organization in an environment of increasing environmental instability and increased competition. As a result, long-term planning has been replaced by strategic planning.

In the 1970s - 1980s. The global economic crisis has led to increased environmental dynamics and uncertainty. Further developments in the field of strategic planning led to the emergence of the concepts of corporate strategy (I. Ansoff), competitive strategy (M. Porter), corporate competitiveness (R. Waterman) and culminated in the creation of strategic management as a direction focused on the strategic goals of the organization.

In the 1980s - 1990s. strategic management, reflecting the innovative content of corporate management, was filled with new ideas thanks to the works of I. Ansoff, G. Mintzberg, and the appearance of the first works of domestic specialists in the field of strategic management. The conducted research made it possible to formulate the basic concepts of strategic management and determine the basic models and procedures for constructing strategies.

In the 2000s. researching new approaches to generating income and creating a competitive advantage in the face of constant changes in the external environment and processes of production of added value have shifted attention to the internal resources and abilities of the economic entity as sources of profit. A new strategic concept of value-based management has emerged. Its main content is to study the resource potential of an economic entity and the factors that ensure the creation and increase of its value.

During the same period in world practice, the management accounting model, focused on the control and analytical functions of intra-organizational management, ceased to meet the needs of management due to its decentralization, increased competition, and value-oriented vision. Management accounting, concentrating the attention of management subjects on internal processes (supply, production, sales, etc.) and ensuring the implementation of basic management functions (planning, accounting, analysis, control), left outside of organizational and managerial attention external processes and objects determined by factors external environment - competitors, suppliers, consumers, sales channels, as well as social, political and other conditions of the organization’s activities, i.e. strategically important factors. At the same time, intra-organizational processes of management decentralization began to provide for differentiation of activity segments. As a result, traditional organizational management structures (linear, functional, etc.) were replaced by innovative ones - divisional (product, regional), matrix, network, etc. Such changes were due to changes in the strategic goals and objectives of the organization, occurring under the influence of external environmental factors. In the development of tools, attention has increased to analytical methods for assessing counterparties, as well as the own resources of an economic entity. As a result, a strategic understanding of the content of management accounting arose, and a new direction emerged - strategic management accounting, developed as a tool for strategic management.

In understanding the content of strategic management accounting as an information resource and analytical tool of strategic management, the starting point should be considered the study of the basic concepts of strategic management. These include the concepts of “strategy”, “segmentation” (structuring) and “competitive advantage”. In the specialized literature there are several definitions of the concept “strategy” (Table 2).

table 2

Basic concepts of "strategy"

The presented definitions (see Table 2) confirm that in a generalized form the concept of “strategy” reflects the unity of the elements of the relationship “goal - directions (courses) of action - support resources.”

Strategic goals involve determining what a commercial organization should do in relation to its own position in the market, profitability (products, segments, activities, etc.), productivity and resource provision, management of the organization and personnel, its own innovations, social responsibility. To achieve strategic goals in global experience, two directions and simultaneously stages of strategic analysis are implemented:

- external strategic analysis(analysis of the external environment - competitors, suppliers, consumers and their positions). It also involves choosing your own strategic position (strategic positioning) and determining your own competitive advantages. This is the so-called competitive analysis;

- internal strategic analysis(analysis of the internal potential (resources) of the organization). Its important elements are the processes of increasing value and the development of adequate methods for their assessment, as well as segmentation and structuring, modern research of which determines the creation of strategically oriented management structures. This is the so-called resource analysis.

To carry out both types of strategic analysis, information and instrumental support is required, which determines the content of strategic management accounting. In modern domestic and foreign translated literature there are several definitions of the concept of “strategic management accounting” (Table 3).

Table 3

The main features underlying the definition of the concept of “strategic management accounting”

A generalization of the presented definitions (see Table 3) allows us to consider strategic management accounting not so much as an information source for making strategic decisions, but as an instrumental resource for ensuring strategy and strategic management. In turn, knowledge of strategic management accounting from the point of view of the tasks of strategic analysis (external and internal) involves the study of analytical tools of strategic management accounting, their composition and content.

To develop the structure and composition of analytical tools for strategic management accounting, the starting point of the study is to consider the basic models of strategic management, which determine the procedures for forming types of strategies. Among the basic models of strategic management, the strategy design model (Harvard Business School) is most widely used; model of the strategic plan for the development of an organization (I. Ansoff, G. Steiner). The objects of application of both basic strategy models are profitability (of products, segments, activities, the organization as a whole); cost (value) of the organization; finance; marketing; pricing; manufacturing process; technological capabilities; product quality; labor relations and personnel; R&D.

The implementation of any of the basic strategy models ensures the formation corporate strategy. It is specified according to the “product/market” characteristic (these are objects of external strategic analysis). However, the main content of corporate strategy is not so much in assessing the profitability of products, segments, activities, etc., but in assessing the cost (value) of a commercial organization due to the presence of a main strategic goal - increasing its value as a factor in profit growth.

As part of the corporate strategy, we are developing functional strategies. They specify the corporate strategy in accordance with the areas of activity. The functional ones include strategies that provide a balanced approach in assessing the main aspects of activity: financial, marketing, production/product, research (innovation) strategy, strategy of organizational change. Functional strategies are implemented according to the “resources/capabilities” characteristic (these are objects of internal strategic analysis).

To implement differentiated types of strategies, external and internal strategic analysis is required. Let us consider which analytical tools of strategic management accounting are adequate for use for external strategic analysis.

External strategic analysis (analysis of the external environment, or analysis of competitors - competitive analysis) involves: assessment of the structure of competitors and assessment of strategic competitive positions (analysis of competitors' strategic positions).

Assessing the structure of competitors (structural analysis of competitors), according to M. Porter, involves researching the composition (list) of existing competitors; threats (ease or difficulty) of the emergence of new competitors within existing ones; replacing own-produced products with competitors' products; the ability of competitors to provide lower prices to customers; the ability of a commercial organization to compete among existing competitors. According to R. Grant, this list can be supplemented by studying the ability of competitors to complementarity (the desire to accompany the main product with additional ones).

In world practice, traditional analytical tools strategic management accounting for carrying out are: analysis of strengths and weaknesses (SWOT analysis) of competitors, analysis of the life cycle of competitors’ products; analysis financial indicators activities of competitors; analysis of competitors' expenses. Let's look at these tools in more detail.

Analysis of strengths and weaknesses (SWOT analysis) of competitors, life cycle analysis of competitors' products. These types of analyzes are conducted based on external information about competitors. Such information provides knowledge about competitors in terms of prices, sales volumes, market shares, cash flows, and other available resources. It also helps to determine what the current strategy of competitors is, their goals and intentions, what their resources and capabilities (strengths and weaknesses) are. From the point of view of information support for strategic management accounting, this kind of information can be obtained from the most general (formal) sources about competitors: annual accounting (financial) statements, press materials, analysis of the results of sociological research on the industry, market segment. The required information can also be obtained from informal sources: from sales representatives, common suppliers, based on product analysis, competitor technologies, and communication with industry experts. On the basis of this kind of collectively collected information, strategic management accounting ensures that the specified types of analysis are carried out.

The life cycle analysis of a competitor's product is carried out based on the developments of the Boston consulting group, which differentiated four stages (phases) of the product life cycle - market introduction, growth, maturity, decline ( Boston Matrix 2x2). Each stage of the product life cycle is characterized by levels of business and financial risks, and the dynamics of cash flows. Assessing business and financial risks involves studying the dynamics of costs (variable and fixed) of a competitor. Thus, a high level of fixed costs reflects a competitor’s high financial risk strategy, but at the same time determines a high level of marginal income in the break-even analysis. A low level of fixed costs, on the contrary, indicates a strategy of low financial risk and a low level of marginal income for a competitor.

In addition, analysis of the life cycle of a competitor’s product allows you to estimate costs and financial results, characterize cash flows for each stage of the life cycle of its product. Thus, at the “introduction” stage, a competitor’s product will have:

High values ​​of variables, as well as fixed costs, until the level of production efficiency increases and stabilizes (competitor's experience curve);

Low, sometimes minimal, income;

Small profit figures, even if revenues increase.

At the “growth” stage of a competitor’s product, one should expect changes in the cost structure due to their increase in market research - marketing costs. Marketing costs are divided into development costs and costs of maintaining the achieved level. Increased investment in marketing development costs should be considered a competitor's long-term investment. The law of diminishing returns generally applies to marketing costs, i.e. increasing market share beyond certain limits may not be justifiable for competitors. In addition, at this stage, you should expect an increase in sales revenue from competitors, as well as an increase in the level of profit from sales by product. As a result, measuring profitability, profitability, profitability by product and sales markets becomes the main element of the structural analysis of competitors. The elasticity of demand for competitors' products, the impact of price reductions on their sales volumes, and, as a consequence, production volumes are analyzed. Competitors' net cash flows may not be positive. But their neutral meanings are quite likely.

At the “maturity” stage, one should expect the stability of the process of profit making by competitors. During this period, competitors will objectively reduce investments, reduce variable costs, and the need to expand production capacity. The main focus of competitors will be on the problem of minimizing costs, the likelihood of realizing the strategic position of “cost advantage,” and the desire to improve production technologies and product quality. As a result, an increase in quality costs among competitors, a decrease in the experience curve, and an increase in economies of scale should be expected.

The "decline" stage for a competitor's product will mean, as a strategic goal of the competitor, the release of costs in those business segments that, according to the competitor, do not create added value. The main task of the competitor is the general trend of cost reduction while controlling the decline in sales volumes.

In general, analysis of the life cycle of a competitor’s product allows you to coordinate your own actions based on knowledge of competitors’ orientation in managing costs, income, cash flows and risks at each stage of the product life cycle.

Analysis of financial performance indicators of competitors. This analysis is carried out on the basis of published accounting (financial) statements; allows for a numerical analysis of its indicators on the financial aspect of activity. In particular, the following are analyzed:

Indicators for assessing financial results and operating efficiency (absolute indicators of gross profit, sales profit, profit before tax, net profit);

Indicators of profitability of financial and economic activities (profitability of sales, expenses for ordinary activities, expenses for products sold, profitability of commercial and administrative expenses);

Indicators of return on assets (total, non-current, current);

Indicators of return on capital (invested, own (shareholder), borrowed, net assets, own working capital, net working capital);

Indicators of cash and liquidity (absolute indicator of net cash flow, relative indicators (coefficients) of absolute, critical, current liquidity);

Indicators of business activity (turnover and duration of turnover of total, non-current, current assets; turnover of total, long-term, short-term receivables; average period for repayment of receivables; share of accounts receivable in the total value of current assets; accounts payable turnover, average period for repayment of accounts payable; inventory turnover);

Indicators of financial stability (absolute - own working capital, net working capital; relative (coefficients) - financial independence, financial dependence, financial stability, financing (financial leverage), financial activity (financial leverage), maneuverability of own capital, provision of own working capital , provision of net working capital).

Such analysis in assessing one's own financial condition and financial performance of an economic entity traditionally constitutes the subject area of ​​comprehensive economic analysis ( financial analysis activities of the organization). It includes well-known formulas for calculating relevant indicators. From the point of view of assessing competitors, it determines the instrumental content of strategic management accounting.

Analysis of competitors' expenses. Since cost information is a trade secret, such an assessment is possible based on an analysis of technologies, production products, experience curves, and economies of scale among competitors. Its sources are direct observation, interaction with common suppliers, surveys of retired personnel, knowledge of competitors' production patents, their production capacities, and technological innovations. This information is also necessary when analyzing a competitor’s break-even.

Thus, analysis of a competitor’s experience curve allows one to evaluate changes in labor productivity due to a better understanding by employees of the content of the production operation they perform (activity function). In view of this, the labor (time) costs for manufacturing, for example, units of production are objectively reduced, which leads to lower costs. This phenomenon is also known as the learning effect. Analysis of a competitor's experience curve is based on tracking increases in labor productivity and reductions in labor costs per unit of output due to repetition of operations (production actions, activity functions). This process continues only for a certain time, when it is possible to set a cost reduction rate per unit of output. The learning process begins at the point when the first unit of production leaves production. When output doubles, then the average time taken to produce a unit of that doubled output will be some percentage of the average time taken to produce the first unit of output about which the doubling then occurs.

For example, a 70% learning curve is applied relative to a competitor. It shows the number of hours of labor required to produce sequentially, say, five batches of product, when the total (cumulative) volume of production doubles after each batch. It is assumed that, according to a known technology used by a competitor, the release of the first batch consisting of one unit of product requires 72 hours. Each subsequent batch leads to an overall doubling of the number of units of product. Calculation of labor time with a set percentage of the learning effect from a competitor is presented in Table. 4.

Table 4

Effect of 70% learning effect from a competitor

Graphically, the 70% effect of competitor experience will show that the average time per unit of production decreases quite quickly at first, then more slowly, and finally becomes so small that it can be ignored in changes. This means that the competitor’s production has reached a stable level and the subsequent effect of changes from labor improvement should not be expected. Experience effect analysis is used in assessing a competitor's production strategy.

Break-even analysis is also an important information source for developing a marketing and product strategy. Its implementation in competitor assessments is limited by the availability (inaccessibility) of information on variable costs, which are present in the calculations of break-even production and sales values, critical sales revenue; production and sales volumes, revenue, but taking into account projected profits; marginal income, marginal safety margin, as well as relative indicators of the norm (level) and marginal income coefficient. In an economic entity's assessment of its own competitive positions, the calculation of these indicators does not cause difficulties.

The study of competitor analysis tools allows us to develop composition of analytical tools strategic management accounting when conducting structural analysis of competitors. Such analytical tools include SWOT analysis of competitors, life cycle analysis of competitors’ products, analysis of financial performance indicators of competitors (analysis of accounting (financial) statements of competitors), analysis of technologies and the experience curve of competitors, analysis of expenses (costs) of competitors, break-even analysis of competitors.

Assessing strategic competitive positions (analysis of competitors' strategic positions) involves identifying the level of product diversity (assortment) of competitors, the level of geographic coverage and market shares of competitors; quality of competitors' goods and services; competitors' positions in technology and capacity utilization, pricing and research and development; ownership structures and organizational structure competitors.

In international practice, the analytical tools of strategic management accounting when analyzing the strategic positions of competitors are portfolio (assortment) analysis of competitors and monitoring of the strategic position and analysis of the strategic positioning of competitors.

Portfolio (assortment) analysis is carried out on competitors in one industry. Involves tracking trends in assortment, sales and production volumes, market shares, product costs, and sales revenue. The information obtained is used for evaluation market strategy competitors.

Monitoring the strategic position and analyzing the strategic positioning of competitors are based on the concept of strategic positioning developed by M. Porter. It is used in assessing three strategic positions embodied in a business:

Cost advantages (resulting in low costs);

Advantages of differentiation (differences);

Advantages by segment (focusing on a narrow segment).

These positions are implemented not only by competitors, but also by the organization itself, which acts as a counterparty and competitor in the external environment. Therefore, this area of ​​strategic analysis focuses not only on analyzing the advantages of competitors, but also on assessing one’s own competitive advantage, as well as assessing the degree of sustainability of one’s own competitive advantage.

Sources of cost advantage are traditionally the learning effect (cost savings due to increased operational experience, training, qualifications); economies of scale (economies due to production volume); improvement of processing technology, improvement of production processes, product design. As a result, the main analytical tools of strategic management accounting are the analysis of the experience curve and the assessment of economies of scale.

However, the cost advantage is achieved primarily through radical cost reduction. In this regard, strategic management accounting uses an effective tool to establish the conditionality of cost reduction. In world experience this is analysis of radical (cardinal) cost reduction. Its implementation is based on the differentiation of activities, within which those in which the most significant cost reductions are possible are identified. For example, consolidation of orders for the supply of inventories provides an increase in supplier discounts and, consequently, a reduction in costs for the activity “purchase logistics”. For this type of activity, cost reduction is also achieved by reducing the number of suppliers (maximizing savings on purchases) and rationalizing logistics processes. The use of high-quality inventories reduces defects in the production process, and the use of identical components for different models of production products reduces general production costs, which together reduces costs for the “main production” activity. By specified type activities, cost reduction is also achieved through the transfer of part of production functions to outsourcing, fuller utilization of production capacity, closing part of production also to improve the utilization of production capacity, rationalization of production processes, reduction of jobs, use of cheap labor, abandonment of outdated technologies, etc. . Reducing the percentage of manufacturing defects reduces the costs of warranty obligations, thereby reducing the costs of the type of activity “after-sales warranty and service maintenance”. For the R&D and design activities, costs are reduced due to changes in the frequency of model changes.

The sources of differences (differentiation or focus) advantages are different from the sources of cost advantages. This is because differentiation adds value, thereby increasing costs, which is a key focus of management accounting. In strategic management accounting, it is important to consider that the variable costs of differentiation or focus include the costs of higher-performing resources, including more qualified personnel, better after-sales service, better quality and targeted distribution. Fixed costs of differentiation and focus increase as the segment the organization covers narrows. In addition, fixed costs increase due to the need for continuous product innovation. This limits the ability to use the experience curve and economies of scale in competitor analysis. These circumstances make competitor cost analysis a key analytical tool for strategic management accounting when analyzing the strategic positions of competitors through differentiation or focusing.

The search for sources of competitive advantages in terms of costs and differences (differentiation or focusing) in global experience also led to vertically oriented integration and diversification of the activities of economic entities. This led to the creation of alliances due to the abandonment of the strategy of rivalry (competition) in favor of a strategy of cooperation between counterparties in the formation of unique value (added value). This orientation is associated with the concept of a value chain, the elements of which, in particular, are various economic entities - competitors. It determines the differentiation of the value chain between competitors, conditioning their access to sources of profit within the chain. At the same time, the level of competition decreases or increases only due to the concentration of elements of the value chain in the hands of one or several counterparties. Therefore, in practice, economic entities - counterparties are interested in receiving and measuring profits at all levels of the value chain. The main analytical tool of strategic management accounting used for such assessment is considered strategic value chain analysis.

It involves assessing the competitive advantage of various economic entities - competitors, considered in the general chain of activities that create value. In this context, a value chain is a coherent set of strategically important activities provided by competing economic entities. The strategic question is whether an economic entity can maintain its competitive advantage based on cost or differentiation or focus, manage the elements of the value chain in comparison with the elements of the value chain of its competitors.

Since the value chain provides not only for the economic entity’s own presence in it as a link(s) of the chain, but also for the presence of its competitors, strategic analysis of the value chain determines the possibility of assessing costs and financial results for each element (links of the chain - types of activities) represented one or another economic entity - a competitor.

Conventionally, if the value chain consists of successive activities "production" - "packaging" - "transportation" - " retail", each of which is represented by a competing economic entity, then strategic analysis of the value chain allows us to identify costs and financial results for each element of the value chain, namely in the context of the types of activities of economic entities - competitors (Table 5).

Table 5

Strategic value chain analysis

The total profit along the value chain is RUB 1,430,220. (39,720 + 360,000 + 94,500 + 936,000). The percentage of total profit belonging to competitors by elements of the value chain has the following values: packaging - 2.78%, production - 25.17%, transportation - 6.61%, retail sales - 65.44%. Given that manufacturing non-current assets are significant in quantity and value in the packaging, production and transportation elements of the value chain, we should also expect the highest return on assets, calculated as the ratio of profit to non-current assets, in the retail element.

The conducted study of tools for analyzing the strategic positions of competitors allows us to develop a set of analytical tools for strategic management accounting when analyzing strategic competitive positions. These include:

Portfolio (assortment) analysis of competitors;

Monitoring the strategic position of competitors;

Analysis of strategic positioning of competitors;

Analysis of the learning effect and the scale of competitors;

Analysis of radical (cardinal) cost reduction;

Strategic value chain analysis.

In a generalized form, the structure and composition of the analytical tools of strategic management accounting used in conducting external strategic analysis are presented in Table. 6.

Table 6

The structure and composition of analytical tools for strategic management accounting when conducting

external strategic analysis of competitors

Internal strategic analysis (analysis of the resources of an economic entity, or resource analysis) involves assessing the internal potential of an economic entity - production, labor, financial. Such analysis traditionally constitutes the subject area of ​​a comprehensive economic analysis of the activities of an economic entity. At the same time, the strategic orientation of an economic entity determines its attention to the study of factors that increase its value, as well as the creation of strategically oriented management structures. These issues require a separate study of the relevant analytical tools of strategic management accounting.

Differentiation of the structure and composition of analytical tools of strategic management accounting used in analyzing competitors determines the capabilities of an economic entity not only in assessing its counterparties, but also in analyzing its own competitive advantages. In addition, it determines the directions of methodological support for strategic management accounting. As a result, the structuring of analytical tools for strategic management accounting is an integral part of its organization and maintenance in an economic entity, being a relevant resource for conducting external economic analysis.

Bibliography

1. Ansoff I. New corporate strategy. St. Petersburg: Peter, 1999. 416 p.

2. Ansoff I. Strategic management: Classic edition. St. Petersburg: Peter, 2009. 344 p.

3. Ansoff I. Strategic management. M.: Economics, 1989. 519 p.

4. Bogataya I.N. Strategic accounting of enterprise property. Rostov n/d: Phoenix, 2001. 320 p.

5. Vakhrushina M.A., Sidorova M.I., Borisova L.I. Strategic management accounting. M.: Reed Group, 2011. 192 p.

6. Drury K. Management and production accounting. M.: Unity-Dana, 2012. 1423 p.

7. Grant R.M. Modern strategic analysis. St. Petersburg: Peter, 2008. 560 p.

8. Katkalo V.S. The evolution of strategic management theory. St. Petersburg: St. Petersburg State University, 2006. 548 p.

9. Mintzberg G. Structure in the fist: creation effective organization. St. Petersburg: Peter, 2004. 512 p.

10. Mintzberg G., Ahlstrand B., Lampel J. Schools of strategy. Strategic safari: excursions through the wilds of management strategies. St. Petersburg: Peter, 2000. 330 p.

11. Mintzberg G., Queen J., Ghoshal S. Strategic process. St. Petersburg: Peter, 2001. 688 p.

12. Nikolaeva O.E., Alekseeva O.V. Strategic management accounting. M.: LKI, 2008. 304 p.

13. Porter M. Competitive advantage. M.: Alpina Business Books, 2005. 715 p.

14. Porter M. Competitive strategy: Methodology for analyzing industries and competitors. M.: Alpina Business Books, 2005. 454 p.

15. Porter M. International competition and competitive advantages of countries. M.: International relationships, 1995. 895 p.

16. Siegel J., Shim J. Dictionary of accounting terms. M.: INFRA-M, 2001. 408 p.

17. Strategic management / Ed. A.N. Petrova. St. Petersburg: Peter, 2012. 400 p.

18. Ward K. Strategic management accounting. M.: Olimp-Business, 2002. 448 p.

19. Waterman R. The renewal factor: how the best companies remain competitive. M.: Progress, 1988. 362 p.

20. Shank J.K., Govindarajan V. Strategic cost management: New methods for increasing competitiveness. St. Petersburg: Business Micro, 1999. 278 p.

21. Shim J., Siegel J. Methods of cost management and cost analysis. M.: Filin, 1996. 344 p.

Operational management is the management of internal production processes at the department level. It comes down to making decisions and taking actions in a specific situation and includes: operational (schedule) planning; organization of technological preparation and equipment maintenance; determining the volume of a batch of manufactured products; placing orders for materials; distribution of work (it is established by whom, where and when certain operations should be carried out); coordination of the current activities of departments to ensure its clear rhythm and compliance with the schedule; Chapter 26. Strategic and operational management of an organization 357 control, identification of deviations, determination of their causes, adjustment of the progress of technological processes; inventory maneuvering; dispatching.

One of the main objects of operational management is inventories. Their presence provides flexibility in logistics, production and sales. There are three types of stocks: the first is raw materials, materials, semi-finished products, which form the starting point of the production process. They are intended to mitigate the negative consequences of uneven supply; the second is the backlog of work in progress between technological operations. The need for them arises due to the irregularity of production processes in various departments; the third is finished products, the surplus of which is needed to cover an unexpected increase in market demand.

MRP reduces costs by reducing inventories of finished products. This is achieved by optimizing the total production volume, sequence of operations and product batch sizes.

MAP involves minimizing investments in inventories based on determining the optimal size of batches of material resources, taking into account the constantly changing flow of orders.

Kanban is a system for operational planning and management of orders and material flows between individual operations. Unlike the previous ones, such a system is “pull” and not “push”. It allows us to produce and supply the necessary parts and semi-finished products for assembly or further processing precisely when consumers' stocks are exhausted.

The conditions for the normal functioning of the system are considered to be the stability of the enterprise’s production program and minor deviations in equipment loading; eliminating the formation of inventories and backlogs of work in progress for reasons not related to technology (for example, to ensure financial stability). “Just in time” is a system for planning and managing material and technical supplies, providing for its complete synchronization with production processes.

48. Control in management, its types and functions.

Management is based on a clear system control, without which it has a fictitious and demonstrative character.

In a management system, control performs the following main functions: functions: verification (establishing the feasibility, validity, legality of decisions; checking their implementation, compliance with technical, environmental, legal and other norms and regulations; identifying errors and violations); informational (collection, transmission, processing of information about the state of the object); diagnostic (study and assessment of the real state of affairs in the organization and its environment; identifying the main trends in its change, threats and opportunities, hidden reserves); prognostic, creating a basis for assumptions about the future state of the object and possible deviations from the specified parameters; communication, ensuring the establishment and maintenance of feedback; orienting, suggesting what you need to pay special attention to; stimulating (based on the results of control, personnel are assessed, rewarded or punished); corrective (based on the results obtained, the state and behavior of the object (its part) are changed in such a way as to ensure the necessary values ​​of its characteristics or stability of functioning when deviating from them); protective (promotes the preservation of resources)

Kinds

The following main types of control are distinguished:

1. By type: traditional control records deviations from planned targets and standards; forward control monitors the gap between the actual state of affairs of the organization and its goals; based on the results, measures are taken aimed at achieving them, and not at correcting past mistakes; entrepreneurial control is exercised over the external situation and internal processes, factors influencing them; As a result, the goals themselves are adjusted.

2. By type (financial, marketing, quality control, production, etc.).

3. By objects, which are: the state of production, technical, personnel potential, the volume of financial resources, material reserves, the feasibility of their use; efficiency of production activities; intermediate and final results; costs, losses and their culprits; reliability, quality, accessibility, completeness of information; deadlines for the implementation of decisions made; image of the organization; maintaining trade secrets, etc.

4. By subjects that carry out the control process (administration, functional services, special units, employees themselves).

5. By intensity (normal or enhanced).

6. At the place of implementation.

7. By purpose (filtering control is designed to separate the good from the bad, and corrective control is to correct the situation).

8. By methods: actual control is carried out through questioning, inventory, inspection, and destruction of the object; documentary occurs on the basis of reconciliations and checks of documents; evaluative control is based on examination, analysis, and comparison with a standard.

9. By stages of implementation.

In accordance with this characteristic, three main types of control are distinguished: preliminary, current and final.

Preliminary, as is clear from the term itself, precedes active activity, and even more so any specific results. Its task is mainly to check the readiness of the organization, its personnel, production apparatus, management system, etc. for work. It is carried out by analyzing the presence and condition of resources, comparing them with the tasks at hand.

Current control (strategic and operational) evaluates the implementation of the organization’s internal and external capabilities

The third type of control is final. It usually involves assessing the organization's implementation of its decisions and the results of its actions, as well as the organization's strengths and weaknesses. Final control data is used to draw up regular plans.