Research the Mutual Influence of Indicators in Innovation Planning at Enterprises

The author analyzes the innovation development programs of 11 Russian companies with state participation and state corporations and compares the achieved results with innovation development plans. The results of the analysis show that the existing relationships between the performance indicators of the companies’ innovation activity for 2014–2016 are not considered or reflected in the programs of innovation development until 2020. This study indicates the causes of the current situation and proposes directions for improving the efficiency of innovation development planning.

Aim. The study aims to examine the mutual influence of indicators in innovation planning at enterprises.

Tasks. The author analyzes the existing innovation development programs of large state-owned companies and the correlation between the performance indicators of innovation activity, assesses the actual results of the implementation of innovation development programs for 2014–2016 and the validity of the planned indicators of innovation development until 2020.

Methods. This study uses the methods of systems and correlation-regression analysis.

Results. The analysis shows that the actual relationships between the performance indicators of the companies’ innovation activity for 2014–2016 are not considered or reflected in the programs of innovation development until 2020. This study indicates the causes of the current situation and proposes directions for improving the efficiency of innovation development planning. A matrix for determining problem situations in innovation development planning is developed.

Conclusions. The actual relationships between the indicators that characterize many aspects of innovation development at various stages of the innovation life cycle are not fully considered in the planning of innovation development. The conducted study confirms a formal approach to estimating the target values of the examined indicators, which disregards the actual relationships between them. The outcome of this can be seen in the programs of innovation development until 2020 developed by corporations. It is possible to make allowance for the actual relationships in the planning of the target values of innovation development indicators by using the methods and tools of dynamic modeling.

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