SUMMARY OF THE LECTURE (available via YouTube link below)

With a number of recent Hollywood films representing intelligent machines as either hero or villain, the subject of Artificial Intelligence (AI) has attracted the imagination of the media and popular culture. On the practical engineering side, over the past decade humanity’s age-old dream of developing intelligent machines has experienced rapid…

Originally posted on sctr7.

Analytics professionals should keep a persistent eye open for opportunities to create cross-functional insights from data. Insights can frequently be…

The brave new world of machine managers

original blog post: http://sctr7.com/2014/10/07/manager-machine-analytics-artificial-intelligence-and-the-uncertain-future-of-management/

Advances in analytics and artificial intelligence increasingly encompass decision making traditionally associated with middle management. With…

For full blog post, click here.

In the mid-1980's I worked as an information analyst / data manager in a police station in a small town in New England (northeast U.S. - for international readers).  It was a strange but exciting experience for a young man, chosen simply as I was identified as the local ‘computer geek’ at the town high school (a small…

Original blog post on sctr7.com, by Scott Mongeau.

Executive summary

Network analysis offers a new set of techniques to tackle the persistent and growing problem of complex fraud. Network…

Original blog posted on sctr7.com.

The adage ‘garbage-in-garbage-out’ is an analytics mantra so ingrained it has its own shorthand: GIGO. Yet, in the mad, blind rush toward all things ‘big data’, there is the danger of sidelining the crucial-but-dreary topic of data quality, to which GIGO refers.

While data quality is not as ‘sexy’ as big data, anyone who wants…

Originally posted on sctr7.com. 

Network analysis is a rapidly growing analytics domain propelled by the explosion of interest in social networking. The methods rest upon much older foundations in the realms of statistics and social science. Euler’s graph theory was proposed in the early 18^th century and Moreno established the foundations for…

Original post: http://sctr7.com/2014/07/09/twelve-emerging-trends-in-data-analytics-part-1-of-4/

INTRODUCTION

Business analytics is a practitioner movement uniting several disciplines to drive value-creating decisions from data.  Central disciplines include IT / computer science, statistics, data management, decision science, and scientific research methods. …

Original post here:  http://sctr7.com/2014/06/27/the-cutting-edge-network-analytics-for-financial-fraud-detection-and-mitigation/

The application of network analysis to the growing challenge of fraud and financial crime is a fast emerging advanced data analytics frontier. As any good fraud investigation knows, fraud and financial crime are as much…

Sharing a lecture introducing business analytics to agroup of MBA and MIS students at Erasmus Rotterdam School of Management:

Summary:  https://www.youtube.com/watch?v=KmG7FJhms2Q

Part 1 of 4: https://www.youtube.com/watch?v=KFYYDrEV4wI

Part 2 of 4: …

Recent TedX talk I gave on data analytics: 
https://www.youtube.com/watch?v=q4d1DArZKgo

Blog link:

http://sctr7.com/2013/12/15/tedx-data-science-and-our-magical-minds/

Please forward if you like it!

Yours,

Scott Mongeau

For full post:  http://sctr7.com/2013/09/08/analytics-and-belief-the-struggle-for-truth/

Increasingly sophisticated analytics tools and methods are available to derive business insight from data.  However, as a discipline which drives insight from data, the crucial ‘last step’ in the analytics process is about organizational decision making.  A sophisticated, intensive analysis may all be…

A fundamental question faced by business analytics professionals and data scientists is whether they have a working correlative and causal explanatory model related to the phenomenon they are observing, be it related to reducing manufacturing error rates, determining the cause of customer abandonment, reducing fraud, targeting marketing, realizing logistics efficiencies, etc.  This is known as an experimental model in science or a conceptual model in broader research venues (i.e. social…

Improperly ‘conflating causation with correlation’ is a central but often overlooked danger in business analysis and data science initiatives. Especially with ‘big data’ sets, analysis will often reveal patterns that suggest a causal element which is only co-occurring phenomenon, or worse, ‘phantom phenomenon’ (i.e. coincidence or a happenstance of a limited dataset).

Some practical examples concerning mistaking correlation for causation:  a recent letter to the editor in the…

This is a review committee working group for practitioners and academics to establish a formal definition and set of classification criteria regarding business analytics model risk.

This group has been established based upon interest and feedback concerning a recent set of posts regarding business analytics model risk: …

PART 6 OF 7 IN A SERIES ON ADOPTING ANALYTICS CULTURE

LINK TO HEADER ARTICLE…

Seven Questions on Adopting Analytics Culture

Seven questions are posed and are addressed in serial.  The theme: ‘how can organizations adopt analytics-based decision making culture?’  

In particular, the questions address the use of change management to adopt evidence-based decision making, associated organizational challenges, and how analytics can be used to manage organizational change itself:…

Business analytics model risk (part 0 of 5): framing model risk - the complexity genie and the challenge of deciding on decision models

Introduction to a series of five articles on model risk

Here we introduce a series of five articles seeking to frame, define, and categorize business analytics model risk.  The intention is to propose processes and practices for strengthening organizational decision model risk mitigation. The series of five…

In Jorge Luis Borges’ parable “On Rigor in Science” (“Del rigor en la ciencia”), a lost empire attains such perfection in the art of cartography that a one-for-one scale map of the empire is produced, laid-out across the land.  In time, the creation is understandably deemed useless and subsequent generations ambivalently witness the decay of the map (Borges, 1975).  Borges’ critique is that of a science which seeks to perfectly validate, one-to-one, its…

For full post see:  http://sctr7.com/2013/02/24/249/

Social Network Analysis (SNA) offers a powerful, low impact method to examine the quality of organizational decision processes.  Such a tool is of interest to evidence-based managers, decision professionals, and analytics practitioners alike.  The second-part of a series on the role of organizational politics in decision making, this article goes into greater detail concerning…