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Dr. Kretov Kirill

Valuation and Reporting of Intangible Assets (Intellectual Capital), is standardization needed? An introduction to - “K.Chart” – the new practical approach to assessing and reporting of Intellectual Capital Structure for decision making

This paper is a practical part of a thesis submitted in part fulfilment of the degree of Doctor in Business Administration By Kretov Kirill 6/1/2011

My Concept for Reporting Capital Structure

In this paper I would like to share with you my concept of graphical reporting of capital structure that I developed through my research. I find it very applicable for the purpose of fast analysis. K.Chart may improve decision making (by reducing the error rate, maintaining attention, and simplifying analysis) and overall knowledge management within a company.

Below you can see the two traditional formats of capital structure reporting: table and hierarch-tree diagram. 1. Table (with color codes)

2. Hierarchy tree (with percent values)

Hierarchy tree is generally superior to table representation, because you can visually see the hierarchy of resources. A percent figure next to each block to signify its value within the total capital. The same capital structure in a format of K.Chart, may look like:

3. K.Chart13 (with full text comments)

Note, that comments (text blocks) can contain any information (absolute values, descriptions, etc). In the graph below full text comments were replaced with code names.

4. K.Chart13 (with codenames)

The graph becomes more compact, but information about resources is now masked and can only be decoded by someone who has a decoding table (refers to the first table in this section, column “code�).

Advantages of the “K.Chart” compared to current methods of reporting As the dissertation research theme states, current methods are more theoretical than practical. Graphical charts are generally thought to be a superior reporting technique compared to more traditional tabular representations in organizational decision making. K.Chart complements this; its slogan could be: worthy solutions make your decisions clearer – now, and in the future. A number of reasons could be attributed to the efficiency of K.Chart in decision-making processes. This proof was arrived at after a number of laboratory experiments. A series of five laboratory experiments were conducted to assess the influence of graphical and color-enhanced information presentation modes on decision quality, decision-making time, use of information, and user perceptions. The experimental design allowed for an unconfounded study of line graphs and color using a variety of information presentation designs for the same decision-making task. Based on the findings of these studies, propositions about the impact of graphics and color on individual decision makers are presented. The influence of the presentation mode on intellectual capital valuation procedures and the perceived value of information is related to how well it supports the solution approach to a particular task. The benefits of graphics are limited to reducing the decision-making time but only when the graphical report has been designed to directly assist in solving the task. Multicolor reports aid in decision making, but only in specific circumstances; that is, their benefits are not pervasive. It appears that color is more advantageous when associated with graphical reports, for certain decision-maker types, during learning periods, and in time-constrained environments. There are a number of benefits of using graphical reports when valuing or assessing intellectual capital for decision-making processes. Among the primary advantages of “K.Chart” is the reduced decision-making time by taking in data more quickly and spotting trends more easily. With the “K.Chart” intellectual capital reporting tools, a company can focus its efforts on other more important aspects (like optimizing their supply chain). A company’s intellectual capital and intangible assets incorporate lots of data which are in spreadsheets, databases, proprietary software (CMS, accounting packages, etc.), emails, remote Web sites, and probably sticky notes throughout the office. To make decisions, the company’s intangible assets accounting valuation reports – especially monthly or weekly, for appropriate decision-making processes – can be tedious and overwhelming.

“K.Chart” is intended to automate the company’s entire intellectual capital valuation and reporting process by a report-making process, from bringing the company data together, converting, checking, and reformatting the data, to tabulating and statistically analyzing the data for easy and quick decision-making processes. “K.Chart” is a practical tool to illustrate a company’s intangible assets compositions. With K.Chart, data become perspective and proper reporting gives a company more insights compared to other reporting practices. The reduced errors and hassles while valuing intellectual capital may increase the company productivity and decision-making processes. “K.Chart” is ideal to intellectual capital evaluators who want a checklist to quickly see which areas of intellectual capital contribute to company value and which do not. Another nice element of “K.Chart” is that valuation guidelines are listed next to the error; this allows the new evaluators to learn the guidelines as they read the valuation report. Worse, the tedious (expensive) process is prone to error every step of the way. Generalized, the “K.Chart” intends to make life easier and business more productive by easily identifying and valuing intellectual capital.

The practical importance of work  To increase the validity of management decisions at the expense of use of the offered organizationaleconomic (knowledge management) tool “K.Chart” for IA identification and evaluation. 

Can also be practical in managing formation and development of IA including other activities of knowledge management.

To perform selection of the best alternative solution variant while investing financial resources in IA formation (including in-house development or acquisitions).

To reduce terms of creation and to increase intellectual product quality at the expense of informationanalytical provision developed by the author.

Benefits of using K.Chart ‘K.Chart” presents a class of graphs that give a lot more possibilities for capital structure representation than any other type of graphs, because it simply allows more informational dimensions (graphical methods of data representation): 1. 2. 3. 4. 5.

Layers that represent hierarchy (normally, during analysis one doesn’t go below the 4 th) Sub-elements for each layer – located just above their parent. Size of area of each sector – volume (relative value). Principle is similar to pie charts. Color code (Currently not in use, except it clearly separates one resource from another). Graphical Comments (Can be of any complexity, but recommended is between 3 and 30 characters)

I believe it might be useful for reporting of total capital structures. And there are many other practical applications of K.Chart including trend analysis, data comparison, on the spot analysis, etc.

Another example (Mega Case) Below you can see an example of some hypothetic company with almost 200 groups of resources identified on the graph. There you can see different scales, use of full text comments and of code names. Charts that are not marked with “complete” have a size constraint – the total value of group of resources should be minimum 1% of total capital.

Alternative 1200x 1200px 3966x 3968px 3966x 3968px 2794x 2796px 2794x 2796px Complete Complete Note that the final picture only represents a structure of the sub-sub-element ("Organizational Resources" within "Intangible Assets"). For the total capital structure reporting there should be about 5 graphs like this one. The complete capital structure in a format of opimized hierachy tree can be found here (currently only available on request to participants of my survey) In my experience we have built the capital structure of more than 30000 (thirty thousands) entries, the printed graph was about 16 square meters.

Survey Research Objectives Originally (in 2010-2011) Kretov Kirill conducted a targeted survey in order to obtain information about current best practices in the field of IA evaluation and reporting, plus to collect feedback regarding his capital structure reporting concept - the K. Chart. The primary purpose of conducting the survey was to: 1. Establish relations with field practitioners (those deeply involved in the management of IA, including identification, evaluation, and reporting); 2. Collect feedback regarding my graphical concept of total capital structure reporting.

The secondary purpose of conducting the survey is to complement the findings of the deskresearch, thus to: 1. Develop a complete list of the intangible assets valuable to a software company (i.e., everything that may have a value and can be identified); 2. Prepare a list of possible approaches to the valuation of each element on this list (if possible); 3. Classify the list of assets according to the level of certainty in the valuation results (i.e., the degree to which the results are widely acceptable to the participants); 4. Identify those assets that may be critically important to software companies; 5. Identify the assets that are easiest to evaluate and those with unquestionable value; 6. Identify the assets that cannot be valued and those for which an evaluation is impractical (i.e., when the cost of valuation may exceed the asset’s value); 7. Find out which models of classification (taxonomy) are most practically applicable.

At present time the simplified version of original survey is available at author’s web-site on (mirror domain

About the author Present article is a part of Doctorate Thesis written by Dr. Kretov Kirill (Master of Arts in Human Resource Management and Doctor of Business Administration) December 2009, Geneva, Switzerland. The author invites everyone to participate in his ongoing survey on the site All copyrights reserved by Kretov Kirill.

Dr.Kretov Kirill Introduction to K.Chart  

Present article is an extract from the Doctorate Thesis written by Dr. Kretov Kirill (Doctor of Business Administration and Master of Arts i...