What is Analytics?
Business has long had a need for decision-making and structured approaches to making decisions, these may use scientific and mathematical techniques. The term Management Science (MS) refers to the application of scientific and mathematical techniques to aid management. A branch of Management Science is Operations Research (OR): this concentrates on determining the best (optimum) choice in a decision problem under the restriction of limited resources.
Good decisions require good data and business decision-making can benefit from the large amount of data captured by modern information technology, the so called data explosion. In recent years, the term (business) analytics has been used to include OR/MS as well as the analysis of data (e.g., using statistical and/or machine learning techniques to find patterns) to provide grounding for the decision(s) to be made.
(opens in a new window)Analysis is generally understood as the process of breaking something (e.g. a problem) into its component parts or modules: understanding these components may be simpler to do. The knowledge gained from the components may lead to a better understanding of the original problem by synthesis --- the bringing together of parts into a whole. In essence, analytics is ``the science of analysis''.
A narrow definition of business analytics might be “the mining and interpretation of data to aid business processes”. A broader definition , which we use in CBA, might be “how an organisation gathers, searches, models, analyses and interprets data so as to aid decision-making and improve or optimise business processes”.
Thus, we take Business Analytics to include the fields of Management Science and Operations Research, which study mathematical and scientific approaches to decision making.
One of the main characteristics of analytics is that it is logical and evidence-based. A major point in analytics is the data: the evidence. A decision based solely on experience or rule of thumb (or simply on a whim) would not be using analytics. This is not to denigrate decision-making based on intuition or experience, but rather to emphasise that it is not what we call analytics. If experience is codified into a body of knowledge, leading to replicable outcomes, then it may qualify as analytics; as happens in expert systems, for example.
We may see the terms
- Descriptive analytics: describing what the data tells us about what has happened
- Predictive analytics: predicting from the data what will happen.
The third part of the jigsaw (and most important from a business point of view) is
- Prescriptive Analytics: using knowledge gleaned from the data to decide what we should do.
It is here that we use optimisation, etc., to truly aid decision making: the extra "value-add" to the mined data.
Above all, CBA is concerned with business analytics, the value of the techniques used is assessed with respect to their contribution to business decision-making.
UCD's CBA (previously known as the Centre for Management Science and Systems) incorporates a cross-section of disciplines associated with Management Science, Operations Research, Systems Science and Decision Support Systems. Our main aim is to facilitate the development of, and provide ongoing support for, an internationally recognised, UCD-based community of researchers whose work focuses on:Decision-Making: its Structures, Modelling, and Realisation in Practice. The CBA aims to lead research in management science, decision science, decision support systems and systems science in Ireland.
The emphasis is on the practical application of technical approaches to solving problems in business, and on developing methods for management decision making. This involves a combination of decision science, modelling, algorithm development, software writing and testing, and applications of ICT (Information Communication Technologies).
Specific topics of interest include multi-criteria decision-making, decision methodologies and processes, (opens in a new window)Decision Support Systems, (opens in a new window)Geographic Information Systems, quantitative modelling for Logistics, and Technology Management. Business applications of CBA research cover a wide range from technical problems to inter-cultural differences in decision approaches. In general, the CBA will give a context for providing solutions that combine systems, mathematics and applied computer science, and for determining their appropriate usage.