The Analytics Movement: Implications for Operations Research

Abstract

The movement toward the increased use of analytics in organizations has generated much discussion by academics and professionals about the impacts and opportunities that analytics offers. Although operations research (OR) has been a driving force in applying quantitative and analytical models for organizational decision making, it is less clear how we as OR practitioners can take advantage of the surging interest in analytics to promote the OR profession and expand its reach. In this paper, we discuss the drivers of the analytics movement, an example of an analytics project, and the opportunities and implications for OR, i.e., the problem scope, models and methods, implementation issues, organizational role, professional skills, and education.

Revisiting the relevance of economic theory to hotel revenue management education and practice in the era of Big Data

“…However, the academic literature supports the idea that it was Douglas Laney (2001) Irrespective of the origins or definitions of the term, the key issue here is that data and knowledge are not the same thing. Having access to huge quantities of data does not make managers instantly knowledgeable, informed decisionmakers (Lewis, 2006;Liberatore & Luo, 2010;Biran et al, 2013). Data has to be correctly interpreted and converted into knowledge for this to be the case, and for this to happen in revenue management, underpinning knowledge of economic principles is arguable needed.…”

“…As revenue and pricing data becomes increasingly unstructured as more data sources are included, such as user-generated content from social media and review sites, this challenge will only intensify. In order to increase the strategic value of knowledge, academics maintain that before any data is collected managers have to ask the right questions in order to source data that will actually provide an accurate answer to those questions, thus supporting accurate decision-making (Liberatore & Luo, 2010;Biran et al, 2013). Again, being able to ask the right questions involves a wider conceptual and theoretical understanding in order to put questions and decisions into context.…”

“…Although price and revenue management decisions made in hotels are increasingly automated, particularly within major global brands such as Intercontinental Hotel Group (Koushik et al, 2012), the need for managers to understand the driving economic forces influencing the market and pricing are still necessary as a sense-check for the decisions made by automated revenue management systems, as part of the blend of art and science of revenue management (Cross et al, 2009). Some academics would argue that relying on Big Data in decisionmaking actually removes ambiguity and leads to more accurate decision-making (Davenport & Harris, 2007;Liberatore & Luo, 2010), but possibly in hospitality where human interactions are so central to the process, experience, intuition and instinct can still play a vital part in helping managers and employees make sense of and interpret data. If this is the case, then these managers still need the underpinning of economic knowledge to help guide their intuition and instinct.…”

Data Scientists’ Skills in Detecting Archetypes in Iran

“…Research analysts develop new models or methods for their own and other organizations. Application analysts apply and customize existing models whereas user analysts verify and interpret results [3].…”

Identity Matrix

“…They are obliged, mostly under time pressure, to select the best solution. Here they can be supported with OR/MS in its modern version, given that they are aware of the powerful methods and tools that OR/MS practitioners have at hand and the impact that OR/MS has had in solving real-world problems; see (Fortuin et al 1992;Davenport 2006;Liberatore and Luo 2010).…”