Forecasting Economical and Social Impact of Non-Profit Organizations Mergers and Acquisitions

Transcription

1 Forecasting Economical and Social Impact of Non-Profit Organizations Mergers and Acquisitions Anna Svirina, Ph.D., Associate Professor Kazan State Technical University Russian Federation Kazan Adoratskogo street Tel: Elena Shurkina, Ph.D., Associate Professor Kazan State Technical University Russian Federation Kazan Amirkhana street Tel: Aleksey Chekhonadskih, Ph.D., Associate Professor Kazan State Technical University Russian Federation Chistopol Engelsa street 127a Tel: Objectives: In past five years in Russia there is a tendency towards mergers and acquisitions of government owned non-profit organizations. It can be seen mainly in medical and educational sector where according to national legislation acts companies are not supposed to have profits and if they earn any those ones are considered extra budget income which is supposed to be spend on medical treatment or education improvement purposes. As far as it seems today government is stimulating such mergers and acquisitions on the basis on lobbyists interests only when in order to receive bigger financial support from the budget influential medical and educational institutions are enforcing mergers with minor institutions without prior estimation of merger or acquisition result in terms of value added. Henceforth it seems necessary to develop a tool for mergers and acquisitions in non-profit sector results estimation which will be sensitive enough to value acquisition or merger produced synergetic effect as well as the obvious effects of non-profit companies integration. Prior Practices: The paper is based upon author s experience in educational field including their own analysis of educational institutions mergers and acquisitions results based upon author s approach towards social and economic efficiency analysis. In terms of prior practices it has to be also mentioned that the problem of mergers and acquisitions had been searched deeply in commercial sector (see for example Reed & Lajoux, 2007: Radygin, Entov & Shmeleva, 2002; Shaver, 2006; Pablo, 1994; Iyer & Miller, 2008; Andrade, Mitchell & Stafford, 2001; Haleblian, Kim & Rajagopalan, 2006; Harford, 2005; Villalonga & McGahan, 2005) including the problems of synergetic effect and organizational structure unification; but mainly the authors dealing with M&A problem were considering financial effects such as price of the shares, EVA, value of the company etc. In case of nonprofit merger or acquisition those are not the main issues since this type of organizations is judged by social outcome it produces and not by the value of the company. According to this thesis, the problem of non-profit M&A is a field where almost no research had been done which means there is an unsolved problem of measuring the efficiency of such mergers and acquisitions as well as a problem of measuring tool development for predicting the efficiency of such integration projects. Page 1 of 9

2 Approach/Methods: Within this paper we are using our own methodological approach to developing a set of criteria in measuring both social and economic effect, based upon theoretical assumption that there are 6 main productivity factors (including creativity and information on the top of 4 classical, see Svirina & Shurkina, 2009). This theoretical framework allowed us to develop an approach to measuring the quality of each productivity factor in merging non-profit organization. The framework for non-profit company readiness for M&A was developed specially for this research within the said framework which is dealing with measurement of six productivity factors and is based on their quality. Results/Insights: On the first step of the presented research the tool for measuring quality of productivity factor of merging non-profit organization was developed on the basis of authors assumptions that organizations are currently possessing 6 productivity factors (land, capital, labour, entrepreneurial activity, information and creativity which we had defined earlier), relationship between which is shown on Figure 1. Creativity Information Entrepreneurial ability Land Capital Organization s efficiency Figure 1. Relationship between productivity factors and organization s efficiency Quality of each of those factors can be estimated by means of testing 15 factors that directly or indirectly describe the quality of a certain factor. Those 15 factors were chosen out of 50 based on correlation analysis (the chosen indicators had strong positive or negative relation towards non-profit organization performance results). First 50 factors were chosen by the experts including non-profit companies owners, employees and clients as well as government officials. In order to make the process of productivity factor quality estimation quick the authors had developed a questionnaire (within which one should answer yes or no) which is based upon estimated by correlation analysis main indicators of quality. In tables 1-6 the list of such questions used for productivity factor quality estimation in non-profit organization is shown. Table 1. Questionnaire for non-profit organization s productivity factor labour quality estimation 1 Does organization achieve its goals? 2 Are employees mainly satisfied with their job? 3 Are employees mainly satisfied with working conditions? Page 2 of 9

3 4 Are employees mainly satisfied with the compensation? 5 Is justice principle performed within organization? 6 Is product/service quality level acceptable? 7 Are employees actually working over ½ of their working hours? 8 Resources are used by employees mainly according to the plan? 9 Are employees disciplined enough? 10 Are cases of absence from work without a satisfactory reasons rare? 11 Do employees rarely explain their faults as the result of some external reasons? 12 Do employees trust each other and management? 13 Communication noises do not influence the quality of information passed? 14 Managers are stating problems only to their direct subordinates? 15 Is span of control being carefully observed? For every yes answer a non-profit organization in its pre-merger state gets 1 point. Overall quality of labour productivity factor is defined as the ratio of points earned to 15 maximum points. The close the received ratio is to 1 the better the quality of labour productivity factor is. The same procedure takes place with land productivity factor (see Table 2). Table 2. Questionnaire for non-profit organization s productivity factor land quality estimation 1 The company is getting quality products and raw material from the suppliers? 2 The company is getting quality services from the suppliers? 3 The company owns (or rents) enough space to carry out its activity? 4 Products and raw materials are coming to the non-profit company on time? 5 Services are coming to the non-profit company on time? 6 The company is receiving the requested products and services? 7 Is the company using its space properly? 8 The company is not short on products and raw materials needed? 9 The company is not short on services needed? 10 The company is not exceeding planned use of products and raw materials? 11 The company is not exceeding planned use of services? 12 The company is able to use its land and space according to decisions made by management? 13 The company is able to use its products and raw materials according to decisions made by management? 14 The company is able to use supplied services according to decisions made by management? 15 The company has no problems with access to the resources. The quality of land is defined according to the algorithm described above for labour productivity factor. The same procedure takes place with capital productivity factor (see Table 3). Table 3. Questionnaire for non-profit organization s productivity factor capital quality estimation 1 Equipment used by the company is of necessary quality? 2 Software used by the company is of necessary quality? 3 Equipment does not need to be repaired often? Page 3 of 9

4 4 The company has an access to necessary financial resources and can easily get extra? 5 The company has an access to necessary equipment and software? 6 Company does not need loans to survive? 7 Company is not spending over 5% of resources for achieving goals which stand out of company s mission? 8 Does company value human resources higher than other? 9 Is the company uses its resources to the high extend? 10 Company s services are of high quality? 11 The company is receiving enough resources to achieve main goals? 12 The company is receiving enough resources to achieve main and side goals? 13 The company is receiving enough resources to achieve also extra goals? 14 The company is receiving enough resources to achieve all stated goals? 15 Company s indirect expenses are less than 40% of direct expenses? The quality of capital is defined according to the algorithm described above for labour productivity factor. The same procedure takes place with entrepreneurial ability productivity factor (see Table 4). Table 4. Questionnaire for non-profit organization s productivity factor entrepreneurial ability quality estimation 1 Are company s clients mainly loyal? 2 Is the company competitive on the market? 3 Is company stably attracting new clients? 4 Does company management understand main clients requirements? 5 Is company service in demand? 6 Are company markets the subject of clear segmentation? 7 Can one say company is good at attracting necessary personnel? 8 Can one say company is good at attracting necessary financial resources? 9 Can one say company is good at using proper technology and technics? 10 Can one say company is good at presenting its service in the market? 11 Can one say company is good at using land properly? 12 Is the company dealing well with unsatisfied clients? 13 Does the company have wide range of clients and is not depending on any of them? 14 The company is never paying bribe? 15 Can one say company is good at services distribution? The quality of entrepreneurial ability is defined according to the algorithm described above for labour productivity factor. The same procedure takes place with information productivity factor (see Table 5). Page 4 of 9

5 Table 5. Questionnaire for non-profit organization s productivity factor information quality estimation 1 Does the company use wide range of information resources on internal and external environment? 2 The time between the moment information is received and used is relatively short? 3 Is the company good at dealing with informational asymmetry? 4 Is the system of reverse connection used by the company good? 5 Does the one who needs information receive relevant information mainly? 6 Does the company know enough about its services from both internal and external clients perspective? 7 The information company needs for efficient performance is getting easier to get as time passes? 8 The quality of information processing is high? 9 The noise in informational communications is low? 10 The company is using mainly formal channels for information transfer? 11 Does the company receive enough information on its competitors? 12 Does the company receive enough information on its markets? 13 Is information processed with a relatively high speed? 14 Is information processing efficient? 15 Is company reacting to major changes in external and internal environment adequate? The quality of information is defined according to the algorithm described above for labour productivity factor. The same procedure takes place with creativity productivity factor (see Table 6). Table 6. Questionnaire for non-profit organization s productivity factor creativity quality estimation 1 The company takes into consideration new ideas regardless of source they are coming from? 2 The company implements new ideas regardless of source they are coming from? 3 An idea can come from any employee of the company? 4 Ideas are processed adequately? 5 Suggested ideas if proved interesting are rewarded? 6 Is there the atmosphere of trust in the company? 7 Company s organizational structure can be considered flat? 8 Are company employees mainly loyal? 9 Company s employees are satisfied with their home/work balance? 10 The level of bureaucracy in the company is relatively low? 11 Company employees are able to manage their worktime by themselves? 12 Personnel is familiar with the set of goals company has? 13 The company had developed and is keeping in working conditions total quality management system? Page 5 of 9

6 14 The services suggested by the company are competitive in the area of its inhabitancy? 15 Services and ideas produced by the company nearly always find its internal or external customer? The quality of creativity is defined according to the algorithm described above for labour productivity factor. After that primary estimation of productivity factors quality of both non-profit organizations which are planning to merge, the level of merger or acquisition readiness should be estimated. This procedure has two steps. On the first stage quality indexes for all six productivity factors are compared. In case they differ less than 10% in merging non-profit organization one can consider that productivity factors in both of them is of close quality which is a preposition for successful merger or acquisition. If the difference even for one factor is somewhere between 10% and 30% merger or acquisition is to be considered risky and in case merger happen main problems would be coming from the factor which quality is highly different. Finally if the difference for even one factor exceeds 30% the merger or acquisition would probably be unsuccessful and should lead to negative synergetic effect creation if it happens. Henceforth if possible such merger or acquisition should be postponed to the time when productivity factor quality would become more equal since in the opposite case integrated structure would be unable to produce necessary social value and would come out of the merger almost without clients. On the second stage complex estimation of productivity factors quality for both merging nonprofit organization should be taking place. Integrated indicator of such quality can be estimated according to the following formula: I q = 0.1Q lab +0.1Q land +0.1Q cap +0.2Q ea +0.2Q inf +0.3Q cr, Q lab index which describes the quality of labour used by merging companies, ratio of points received to maximum; Q land index which describes the quality of land used by merging companies, ratio of points received to maximum; Q cap index which describes the quality of capital used by merging companies, ratio of points received to maximum; Q ea index which describes the quality of entrepreneurial activity in merging companies, ratio of points received to maximum. This indicator has higher share in complex indicator due to the fact of its higher importance estimated by the experts; Q inf index which describes the quality of information used by merging companies, ratio of points received to maximum. This indicator has higher share in complex indicator due to the fact of its higher importance estimated by the experts; Q cr index which describes the quality of creativity in merging companies, ratio of points received to maximum. This indicator has maximum share in complex indicator due to the fact of its higher importance estimated by the experts. Complex indicators are indicated for both companies and than compared. In case they differ less than 10% in merging non-profit organization one can consider that productivity factors in both of them is of close quality which is a preposition for successful merger or acquisition. If the difference even for one factor is somewhere between 10% and 30% merger or acquisition is to be considered risky and in case merger happen main problems would be coming from the factor which quality is highly different. Finally if the difference for even one factor exceeds 30% the merger or acquisition would probably be unsuccessful and should lead to negative synergetic effect creation if it happens. To make a conclusion on this research we would like to provide the results of two comparative studies performed for two non-profit companies merger. In first case two medical services centres located in Kazan where merging (see Figure 2) in Page 6 of 9

7 1 0, ,8 0, ,6 0, ,4 0, ,2 0,1 0 labour land capital entreprenuerial activity information creativity medical care centre #5 0,81 0,74 0,86 0,67 0,92 0,88 medical care centre #12 0,78 0,71 0,87 0,65 0,87 0, medical care centre #5 medical care centre #12 patients before merger (per year) patients after merger (per year) Figure 2. Medical care merging companies profiles and future performance As it can be clearly seen from the figure provided, as the result of the merger both medical care centres had started to have more satisfied patients than prior to the merger (for medical care centre #5 growth rate is 3%, for medical care centre #12 8%) which is in our opinion due to two main reasons. First of all the profiles of companies productivity factors quality in the studied case are pretty close which makes prepositions for successful merger. Second, medical care centre #12 was able to improve quality of service highly since it got access to some rare specialists after merger while increase in medical care centre #5 satisfied patients is only due to the fact that some of the former dissatisfied clients where able to change their doctors 1 which led to improve in medical services quality. The second merger analyzed in this study was a merger of Zelenodolsk city campus of Kazan State Technical University with professional college #51 situated in this city. Educational institutions profiles and results of the merger are shown on Figure 3. 1 In Russia people s mobility in choosing doctor suggested by government funded medical services is restricted. A person can go only to doctors from the medical care centre he belongs to by place he or she lives Page 7 of 9

8 1 0,9 0, ,7 0,6 0, ,4 0,3 0, ,1 0 labour land capital entreprenuerial activity information creativity KSTU 0,92 0,86 0,82 0,89 0,72 0,81 College 0,61 0,84 0,77 0,43 0,78 0, KSTU students before merger (per year) College students after merger (per year) Figure 3. Educational companies merging companies profiles and future performance This merger took part in 2008 and was involving two educational institutions with very different productivity factors quality profiles. The results of this merger were as well predictable: Kazan State Technical University campus with better quality profile had lost students (19% in two past years) who were moving to different educational institutions while college was growing in terms of students attracted, but by relatively low rate on 2.3%. That means that overall merged structure had lost 12.2% of students who become dissatisfied with the quality of education. Those results show that prior estimation of conditions should be as well performed in case of non-profit companies mergers and acquisitions. Implications to Community/Industry: Non-profit organizations are provided with forecasting tool measuring economic and social value added in case of merger or acquisition. Educational institutions and consultants are provided with a tool of measuring possible results of M&A in the non-profit sector. Value to the Theme: a forecasting model for non-profit organization s economic and social value added measurement, based upon 6 productivity factor methodological approach. Keywords: productivity factors, non-profit organizations, mergers and acquisitions, economic value added, social value added. Page 8 of 9

9 References Andrade G., Mitchell M., Stafford E. (2001), New evidence and perspectives of mergers, Journal of Economic perspectives 15(2), pp Haleblian J., Kim J., Rajagopalan N. (2006), The influence of organizational acquisition experience on acquisition performance: a behavioural learning perspective, Administrative Science Quarterly, 44, pp Harford J. (2005), What drives merger waves?, Journal of Financial Economics, 77, pp Iyer D., Miller K. (2008), Performance feedback, slack, and the timing of acquisitions, Academy of Management Journal, 51, pp Pablo A. (1994), Determinants of acquisition integration level: a decision-making perspective Academy of Management Journal, 37, pp Radygin A., Entov R., Shmeleva N. (2002), Problems of mergers and acquisitions in corporate sector, IEPP institution, (in Russian) Reed S., Lajoux R. (2007), The art of mergers and acquisitions, Alpina Business Books, (in Russian) Shaver M. (2006), The paradox of synergy: contagion and capacity effects in mergers and acquisitions, Academy of Management Review, 31, pp Villalonga B., McGahan A. (2005), The choice among acquisitions, alliances and divestitures, Strategic Management Journal, 26, pp Page 9 of 9