Economic Analysis: Theory and Practice

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Predictive and prescriptive analysis: Theoretical aspects

Vol. 18, Iss. 7, JULY 2019

Received: 22 May 2019

Received in revised form: 4 June 2019

Accepted: 17 June 2019

Available online: 30 July 2019


JEL Classification: G30, G32

Pages: 1243–1255

Kogdenko V.G. National Research Nuclear University MEPhI, Moscow, Russian Federation

Subject The article considers theoretical issues of predictive and prescriptive analysis.
Objectives The aim is to summarize algorithms and areas of prognostic and prescriptive analysis and unveil sources of company efficiency as a result of use of digital analytics.
Methods I employ general scientific principles and methods of research, like analysis and synthesis, grouping and comparison, abstraction, and generalization.
Results The paper gives characteristics of predictive and prescriptive analysis, modeling algorithms, and identifies six areas of analysis. I consider the modeling algorithm that includes work with training and test datasets. Within each area of analysis, I highlight the main elements and sources of business efficiency improvement.
Conclusions The paper defines ways to improve business efficiency as a result of the use of digital analytics. They include adaptation of product and marketing complex to clients' needs, lowering the cost of business processes, development of effective personnel policy, preventive decision-making on fraudulent operations, business model optimization. The article may be useful for specialists of analytical services of companies.

Keywords: predictive analytics, prescriptive analytics


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