Wyniki wyszukiwania - BazTech

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The concept of diagnostic analytics

Wolniak Radosław, Grebski Wes

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2023

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z. 175

651--670

EN

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the diagnostic analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The paper discusses the concept of diagnostic analytics, which is a powerful tool for organizations to understand the underlying factors and reasons behind specific outcomes or events. By analyzing historical data and applying statistical techniques, organizations can identify root causes, patterns, and correlations that explain past events. This understanding enables informed decision-making, performance improvement, risk mitigation, enhanced customer insights, process optimization, resource allocation, and continuous improvement. Nevertheless, there are several challenges associated with diagnostic analytics. Firstly, the analysis process can be time-consuming due to the need for thorough examination and interpretation of data. Additionally, real-time insights may be limited as diagnostic analytics primarily focuses on historical data. Issues related to data quality and availability may also arise, impacting the accuracy and reliability of the analysis. Furthermore, diagnostic analytics lacks predictive capabilities, making it more challenging to anticipate future outcomes. The complexity of analysis, data privacy and security concerns, risks of bias and misinterpretation, and difficulties in identifying causal relationships further add to the challenges organizations face. Originality/value: Detailed analysis of all subjects related to the problems connected with the diagnostic analytics.

2

The basis of prospective analytics in business

Wolniak Radosław, Grebski Wies

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2023

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z. 176

771--789

EN

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the prospective analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: Prescriptive analytics aims to assist businesses in making informed decisions that optimize desired outcomes or minimize undesired ones. It goes beyond predicting future outcomes and provides recommendations on the best actions to achieve desired goals while considering potential risks and uncertainties. Prescriptive analytics finds applications in various domains such as supply chain management, financial planning, healthcare, marketing, and operations management. It empowers businesses to make data-driven decisions, optimize resource allocation, enhance efficiency, and gain a competitive advantage. Considered the highest level of analytics, prescriptive analytics combines historical data, real-time information, optimization techniques, and decision models to generate actionable recommendations. Originality/value: Detailed analysis of all subjects related to the problems connected with the prospective analytics.

3

Functioning of predictive analytics in business

Wolniak Radosław, Grebski Wes

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2023

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z. 175

631--650

EN

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the predictive analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: Predictive analytics is a powerful tool that leverages historical data and statistical models to forecast future outcomes and behaviors. It enables organizations to gain valuable insights, make informed decisions, and drive business growth. By analyzing patterns, correlations, and trends in data, predictive analytics can uncover hidden relationships and provide a deeper understanding of business processes, customer behavior, market trends, and other important factors. The benefits of predictive analytics are numerous. It enables organizations to forecast and predict future events, leading to proactive decision-making and the ability to anticipate trends and outcomes. It enhances decision-making processes, improves resource allocation, and provides enhanced customer insights. Predictive analytics also helps in risk mitigation, fraud detection, optimization of operations and pricing, product development, and marketing effectiveness. By leveraging these benefits, organizations can gain a competitive advantage and achieve sustainable success. Originality/value: Detailed analysis of all subjects related to the problems connected with the predictive analytics.