Modeling and Estimation of the Risk When Choosing a Provider

The factors of the enterprise's economic stability are its competitive ability, quick response to the changes of external conditions, implementation of the new technologies, increase of the manufactured products quality and efficiency of the industrial enterprise activity. One of the methods of competitive ability increase for an enterprise is the use of outsourcing [1 -4]. However, upon outsourcing implementation in the enterprise, it shall be accounted that snap decision about transition to outsourcing, not supported by a deep analysis of all potential risks [5 -11] and advantages can have a negative effect on the enterprise activity. This is connected with the fact that the outsourcing market in our country is not yet developed to such a degree as to offer large suppliers to the enterprises, suppliers, who would be able to provide high-level services.

Transition of the enterprise’s operation functions to outsourcing requires that corporate decision support systems (DSS) shall assess options of orders placement for outsourcing with account of risk factors [12,13].

In this work, the algorithm is suggested for calculation of risk integral estimate upon selection of an outsourcing provider, a numerical example is provided. Variety of risks accounted in different economy braches, is quite large [8 -10].

In respect of the influence degree, the risks are divided into external (uncontrolled) and internal (controlled). External risks include:

 economic (price risk, exchange rate, currency and market risks);  administrative (modification of the statutory documents, payments accompanying risks);  risks associated with outsource services provider (breach of contract terms, information leak, growth of prices). Internal risks are usually represented by information risk (untimely receipt of information), personal risk (associated with the low professional level of the decision-makers), financial risk (lack of funding).

Diversity of possible sources of information about risks complicates their comprehensive and complete accounting. Therefore, in practice, experts are frequently involved for the assessment of poorly formalized and hardly-measurable factors. In this work, expert evaluation tools are also applied for risk assessment of each provider. The suggested technology includes two groups of expert evaluations:

1. The first group includes estimates of relevance of each factor according to the customers’ opinionand separately according to the provider’s opinion. The result is the balanced weights of each risk factor according to the opinion of such services market participants. This group can be formed by specialized consulting companies with the use of expert evaluation methods for different types of businesses used in the outsourcing (transport, legal, customs services, provision of constituent components and ingredients for different manufactures, etc.)

2. The second type is formed by the company selecting provider itself. Evaluations here are represented by the scores assigned by the experts for one or another risk factor, applicably to a certain provider from the portfolio of potential outsourcing services providers. For instance, even with a high risk of unreliable supply, a minimum score can be assigned, in case the company receives the commodities in form of customer’s pick-up.

Algorithm of provider’s risk evaluation is demonstrated by the model data provided in the Table 1.

Thick frame contains portions 𝑞 𝑖𝑗 of the respondents (interviewed customers and providers), whose 0-10 evaluations lie within the “-score” ranges [0; 1], [1; 3], [3; 5], [5; 7.5], [7.5; 10], right borders of which (pockets) are specified as 𝑎 𝑖 . These values can be calculated separately for the customers and providers, but here their average values are presented, i.e. the correlation ratio for these groups amounts to 0.94, which allows to consider their opinions about risk factors as consistent. Portions of respondents are obviously can be interpreted as probabilities of the corresponding scores 𝑎 𝑖 . Then it is possible to estimate average risk 𝑐 𝑖 as an average score of each risk factor:

where 𝑛number of score estimates’ ranges; 𝑚number of risk factors .

For estimation convenience, it is necessary to perform normalizing of average risks (1), which will allow to operate them (𝛼 𝑖 ) as probabilities:

The second group of estimates reveals opinion of the customer’s experts about each k th provider from the providers group 𝐾, considered as potential service providers. For each provider, experts assign a score according to the discrete scale from 1 to 5 (see column bi in the Table 1). Then integral risk 𝑟 𝑘 for the k th provider is determined as follows:

For data provided in the table 1, the integral risk value is 𝑟 𝑘 = 0.71, which can be interpreted as a minor risk, since it can lie within the range from1 to 5. However, in case the purpose of estimates calculation is the selection of an alternative provider, then the absolut

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