Analysing Analytics:Evolution or Emperor's New Clothes?
YoungOR 18, April 2013Michael J. Mortenson, Neil F. Doherty & Stewart Robinson
In association with:
What is Analytics?What is the difference between business analytics and business intelligence?
1 Analysing Analytics: Evolution or Emperor’s New Clothes?
Analytics is a subset of business intelligence
Davenport & Harris (2007, p 7)
Business intelligenceis a subset of analytics
Vesset et al (2012); SAP (2012)
Business intelligence &analytics are a combined discipline
Chen et al (2012); Lim et al (2012)
Analytics is a ‘rebranding’of business intelligence
Eckerson (2011); Elliot (2011)
What’s the difference between …?
Analytics is ...delivering the right decision support to the
right people at the right time.Laursen & Thorlund, 2010, p XII
Decision Support Systems are ...technology solutions that can be used to
support complex decision making.Shim et al, 2002
Analytics is ...[the] technologies, systems, practices, and
applications to analyze critical business data so as to gain new insights
Lim et al, 2012
Management Information Systems are …an arrangement of equipment and procedures, […]
designed to provide managers with informationCollins English Dictionary
Analytics is ...the scientific process of transforming data
into insight for making better decisionsINFORMS
Operational Research is ...The application of advanced analytical
methods to make better decisions.INFORMS
2 Analysing Analytics: Evolution or Emperor’s New Clothes?
Presentation Structure
3 Analysing Analytics: Evolution or Emperor’s New Clothes?
1. Historical Analysis of Analytics
2. The 1st Era: The Scientific Method
3. The 2nd Era: Management Information Systems
4. The 3rd Era: Decision Support Systems
5. The 4th Era: Business Intelligence
6. The 5th Era: Business Analytics
7. What is an Era?
8. Analytics and Operational Research
Historical Analysis of Analytics
4 Analysing Analytics: Evolution or Emperor’s New Clothes?
1. Where to start?
2. What to include?
The 1st Era: The Scientific Method
5 Analysing Analytics: Evolution or Emperor’s New Clothes?
o The end of WW2 to the mid-1960s.
o Characterised by attempts to apply the ‘scientific method’ to decision making.
o Key developments include:― The von Neumann architecture― Behavioural science― FORTRAN programming language
Aspect The First Era
CatalystsSuccess of OR methods in WW2 & developments in computing technologies.
Data Mostly ad-hoc. Often difficult to obtain and manage.
Technology Early computers & digital calculators.
Quantitative Methods
OR, statistics, mathematics and econometrics.
Decision Making
Limited. Mostly reports created ad-hoc.
The 2nd Era: Management Information Systems
6 Analysing Analytics: Evolution or Emperor’s New Clothes?
o Mid-1960s to late-1970s.
o Characterised by the widespread adoption of business computing.
o Key developments include:― Development of microchips― Release of the IBM
System/360― First MSc in OR introduced
Aspect The Second Era
Catalysts Rapid spread of computers such as IBM System/360.
Data Increased amount of data, mostly through manual input.
Technology First MIS & relational database management systems (RDBMS).
Quantitative Methods
OR, statistics, mathematics and econometrics.
Decision Making
Mostly ad-hoc though with some report automation.
The 3rd Era: Decision Support Systems
7 Analysing Analytics: Evolution or Emperor’s New Clothes?
o Describes a period from the late-1970s to the late-1980s.
o Combines information systems with OR & behavioural science.
o Key developments include:― Personal/desktop computers ― The ID3 decision tree algorithm― The ‘Soft OR’ methodology
Aspect The Third Era
Catalysts Making information systems more focused on end-users.
Data Mostly structured, but in increased amounts.
Technology DSS, RDBMS, PCs, LANs & statistical software.
Quantitative Methods
OR, statistics, mathematics and econometrics.
Decision Making
DSS user interfaces (GUIs) designed to suit users.
The 4th Era: Business Intelligence
8 Analysing Analytics: Evolution or Emperor’s New Clothes?
o The late-1980s to the around 2000.
o The term describes tools such as data-marts, data-warehouses & OLAP cubes.
o Other key developments include:― Increased retail & operational data― Balanced scorecards & dashboards― Data mining
Aspect The Fourth Era
Catalysts Increased data available. New architecture & technology.
Data Point of sale data. Combining datasets into warehouses.
Technology Data-marts, warehouses, RDBMS, laptops & PCs.
Quantitative Methods
Traditional methods plus the popularisation of data mining.
Decision Making
GUIs, balanced scorecards & dashboards.
The 5th Era: Business Analytics
9 Analysing Analytics: Evolution or Emperor’s New Clothes?
o The early-2000s to present day.
o ‘Big Data’ sources: social networks, RFID & the ‘Internet of Things’.
o Desire to make more analytically-informed decisions in management.
o Other key developments include:― Smartphones, tablets, etc.― Text mining― Data visualisation
Aspect The Fifth Era
Catalysts ‘Big Data’ & associated architecture.
Data Significant amounts of structured & unstructured data.
Technology NoSQL, MPP, software-as-a-service & real-time analytics.
Quantitative Methods
Tools integrated into product ‘suites’. Text mining.
Decision Making
Recommendation agents, data visualization & integrated
insights in operating systems.
What is an Era?
Analysing Analytics: Evolution or Emperor’s New Clothes?
o Is an era a paradigm?o Is an era just hype?o Shares many of the purposes
& practices of previous era(s).o However, introduces new
challenges, innovations, characteristics & perspectives.
10
Analytics and Operational Research
11 Analysing Analytics: Evolution or Emperor’s New Clothes?
Surface Level
Discipline Level
The most visible level.
The most era-specific part. Concerns general discussions (or hype).
Describes the underlying disciplines.
Includes technological, quantitative methods & decision making disciplines.
Summary
12 Analysing Analytics: Evolution or Emperor’s New Clothes?
• Each era has unique concerns but is closely related to the last.
• For OR ‘rebranding’ as analytics has problems: Instability Lose the core of the “OR brand”.
• Ignore analytics? Miss opportunity Ignore the concerns of the “ecosystem” Opportunities to innovate
o Real-time ORo Distributed File Systems & ORo OR & data mining ‘Big Data’
Contact Details and Questions
Analysing Analytics: Evolution or Emperor’s New Clothes?
Email: [email protected]
Website: www.whatisanalytics.co.uk
Mobile: 07833 -------
LinkedIn: http://www.linkedin.com/profile/view?id=114000243&trk=tab_pro (or search Michael Mortenson)
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