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Advanced Analytics | Analytics

Mike GillilandOctober 26, 2016 0

Changing the paradigm for business forecasting (Part 11 of 12)

Aphorism 3: Organizational Policies and Politics Can Have a Significant Impact on Forecasting Effectiveness We just saw how demand volatility reduces forecastability. Yet our sales, marketing, and financial incentives are usually designed to add volatility. We reward sales spikes and record weeks, rather than smooth, stable, predictable growth. The forecast

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Advanced Analytics | Analytics

Megatrends im Analytics Bereich

Dr. Laurie MilesOctober 26, 2016 0

Results-as-a-Service - Aussagekräftige Analysen für alle!

In seinem Buch „Competing on Analytics“ benennt Tom Davenport die Analytik als Grundlage nachhaltiger Wettbewerbsvorteile. Der Grund dafür ist der prädiktive Ansatz. Heutzutage ist es nicht mehr möglich, ein Unternehmen alleine mit Blick in den Rückspiegel zum Erfolg zu führen. Und Analytik erlaubt den dringend erforderlichen Blick in die Zukunft.

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Advanced Analytics | Fraud & Security Intelligence

Stavros StavrinoudakisOctober 25, 2016 0

A practical guide to tackle auto insurance fraud - Part 3: Advanced Analytics

This is the third of the seven parts of blog post series “A practical guide to tackle auto insurance fraud”. In the first two articles of the series we drilled down to Data Management and Data Quality as the basis for insurance fraud detection analytics and also to the Business

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Advanced Analytics | Analytics

Mike GillilandOctober 25, 2016 0

Changing the Paradigm for Business Forecasting (Part 10 of 12)

The Aphorisms of the New Defensive Paradigm I want to finish this blog series with a set of 7 aphorisms – concise statements of principle – that characterize the new Defensive paradigm for business forecasting. The first is that: Aphorism 1: Forecasting is a Huge Waste of Management Time This

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Advanced Analytics | Data Management

David PopeOctober 24, 2016 0

Analytics: Four key elements for success

Analytics provides better insights into why something happened, or helps provide decision makers with information about what will happen in the future. That allows organizations to act now to improve outcomes instead of reacting to events after they happen. But it takes more than analytics alone. Achieving this level of

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Advanced Analytics | Analytics

Mike GillilandOctober 24, 2016 0

Changing the paradigm for business forecasting (Part 9 of 12)

Academic Research In an approach akin to FVA analysis, Paul Goodwin and Robert Fildes published a frequently cited study of four supply chain companies and 60,000 actual forecasts.* They found that 75% of the time an analyst adjusted the statistical forecast. They were trying to figure out, like FVA does,

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Advanced Analytics | Analytics

FVA comparisons

Mike GillilandOctober 21, 2016 0

Changing the paradigm for business forecasting (Part 8 of 12)

Typical Business Forecasting Process Let’s look at a typical business forecasting process. Historical data is fed into forecasting software which generates the "statistical" forecast. An analyst can review and override the forecast, which then goes into a more elaborate collaborative or consensus process for further adjustment. Many organizations also have

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Advanced Analytics | Analytics

Mike GillilandOctober 20, 2016 0

Changing the paradigm for business forecasting (Part 7 of 12)

The Means of the Defensive Paradigm The Defensive paradigm pursues its objective by identifying and eliminating forecasting process waste. (Waste is defined as efforts that are failing to make the forecast more accurate and less biased, or are even making the forecast worse.) In this context, it may seem ridiculous

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Advanced Analytics | Analytics

Four alternative models

Mike GillilandOctober 19, 2016 0

Changing the paradigm for business forecasting (Part 6 of 12)

Why the Attraction for the Offensive Paradigm? In addition to the reasons provided by Green and Armstrong, I'd like to add one more reason for the lure of complexity: You can always add complexity to a model to better fit the history. In fact, you can always create a model

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Advanced Analytics | Analytics

Mike GillilandOctober 19, 2016 0

Guest blogger Len Tashman previews Fall 2016 issue of Foresight

Fresh from chairing the Foresight Practitioner Conference on “Worst Practices in Business Forecasting,” hosted two weeks ago at the Institute for Advanced Analytics at North Carolina State University, Foresight editor-in-chief Len Tashman previews the Fall 2016 issue. Preview of the Fall 2016 issue of Foresight In the provocative article, “The

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Advanced Analytics

Rick WicklinOctober 19, 2016 0

Loess regression in SAS/IML

A previous post discusses how the loess regression algorithm is implemented in SAS. The LOESS procedure in SAS/STAT software provides the data analyst with options to control the loess algorithm and fit nonparametric smoothing curves through points in a scatter plot. Although PROC LOESS satisfies 99.99% of SAS users who

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Advanced Analytics | Analytics

Mike GillilandOctober 18, 2016 0

Changing the paradigm for business forecasting (Part 5 of 12)

Implications for the Offensive Paradigm The worldview promulgated by the Offensive paradigm is that if we only had MORE – more data, more computational power, more complex models, more elaborate processes – we could eventually solve the business forecasting problem. But this just doesn’t seem to be the case. Operating

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Advanced Analytics | Analytics

Mike GillilandOctober 17, 2016 0

Changing the paradigm for business forecasting (Part 4 of 12)

Is Complexity Bad? It’s necessary to point out that Goodwin’s article is not arguing against complexity per se, and I’m not either. When you have a high value forecast, where it is critical to be as accurate as possible, of course you are going to want to try every technique

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Advanced Analytics | Analytics

Mike GillilandOctober 14, 2016 0

Changing the paradigm for business forecasting (Part 3 of 12)

Anomalies: The Beginning of a Crisis While even trained scientists can fail to see things that fall outside what they are looking for, anomalies eventually start to get noticed. But still, for a long time, anomalies within an existing paradigm are seen as mere “violations of expectation.” The response within

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Advanced Analytics | Analytics

Gorilla Experiment Video

Mike GillilandOctober 13, 2016 0

Changing the paradigm for business forecasting (Part 2 of 12)

The Current Paradigm for Business Forecasting So what is the current paradigm that we, the community of business forecasting practitioners and researchers, are operating under? I’d argue that for at least the last 60 years, since 1956 when Robert G. Brown published his short monograph Exponential Smoothing for Predicting Demand,

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Advanced Analytics | Analytics

Mike GillilandOctober 13, 2016 0

Changing the paradigm for business forecasting (Part 1 of 12)

In a February 2015 post Offensive vs. Defensive Forecasting, I sought to distinguish two very different approaches to the business forecasting problem: Offensive: The "offensive" forecaster is focused on forecast accuracy -- on extracting every last fraction of a percent of accuracy we can hope to achieve. The approach is

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Advanced Analytics | Analytics

Mike GillilandSeptember 27, 2016 0

NIJ crime forecasting challenge

NIJ's Real-Time Forecasting Challenge If you want to show off your forecasting chops, and maybe even make a little money, the National Institute of Justice has just the challenge for you. The NIJ's Real-Time Crime Forecasting Challenge: ...seeks to harness the advances in data science to address the challenges of

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Advanced Analytics | Machine Learning

Patrick KochSeptember 20, 2016 0

Local Search Optimization for HyperParameter Tuning

When shopping for a new TV, with many sets next to each other across a store wall, it is easy to compare the picture quality and brightness. What is not immediately evident and expected is the difference between how the set looked in the store and how it looks in your

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Advanced Analytics | Fraud & Security Intelligence | SAS Events

SAS PolandSeptember 15, 2016 0

SAS® Visual Investigator – nowy wymiar użycia zaawansowanej analityki SAS

W obecnych czasach temat wykrywania nadużyć w obszarach finansów, usług dla obywateli oraz bezpieczeństwa narodowego staje się coraz większym wyzwaniem dla firm prywatnych i instytucji państwowych. Powszechność dostępu do Internetu, gwałtowny rozwój handlu elektronicznego i rosnące ilości danych przetwarzanych w usługach „w chmurze” powodują konieczność zastosowania zaawansowanych narzędzi informatycznych. SAS®

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Advanced Analytics | Machine Learning | SAS Events

Polly Mitchell-GuthrieSeptember 13, 2016 0

Machine learning fun at KDD

Who says machine learning can't be fun? A crew of us from SAS went to San Francisco for the recent KDD conference, which bills itself as "a premier interdisciplinary conference, [which]brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data." We brought

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Advanced Analytics | SAS Events | Students & Educators

Elaine KearneySeptember 9, 2016 0

The Internet of medical things and of intern things

The internet of medical things, spurred by the advent of wearable sensors, has dramatic consequences in industry, healthcare, and analytics, just as the advent of the internet of things and analytics has consequences in education. When I began my internship at SAS in May, I knew little about the internet of

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Advanced Analytics | Analytics

Mike GillilandSeptember 8, 2016 0

New course on Next Generation Demand Management

My friend and colleague Charlie Chase, author of the new book Next Generation Demand Management, has developed a 2-day course to go along with the book. The course is part of the SAS Business Knowledge Series, and is being offered in Chicago, October 19-20. Here are the details: Next Generation

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Advanced Analytics | Machine Learning | SAS Events

Namita LokareSeptember 8, 2016 0

Time series machine learning techniques in healthcare

Time series machine learning techniques show great promise for the analysis of health care wearable data. As our busy lifestyles render continuous monitoring more and more essential, the need to analyze data to find correlations between these data streams becomes even more important, because they can provide important cues to

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Advanced Analytics | Analytics | Data Visualization

Andreas BecksSeptember 8, 2016 0

Ohne Kompromisse: 9 Tipps für Analytics

Data Science, Self-Service, Machine Learning, Internet of Things … All diese Begriffe rund um die Digitalisierung geistern schon seit einiger Zeit durch die IT-Welt – und nicht nur durch diese. Spätestens die letzte Fußball-EM hat mit dem Phänomen „Packing“ auch dem Nicht-ITler unter den Fans des Breitensports die Augen geöffnet,

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Advanced Analytics

Ed HughesSeptember 7, 2016 0

Operations Research Talks at Analytics Experience 2016

Analytics Experience 2016 will be held on Sept. 12-14, 2016 at the Bellagio in Las Vegas, NV. There will be a great number of excellent talks and demonstrations at the conference, covering many aspects of SAS analytics and many practical applications. Several of these sessions deal directly with the use

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Advanced Analytics | Fraud & Security Intelligence

Stavros StavrinoudakisAugust 31, 2016 0

Procurement fraud: your hidden enemy

All global researches and surveys show that all kind of fraud, like procurement fraud, is rising and empowered by new dimensions in matter of vulnerabilities and attack methods. From traditional check tampering and skimming methods to cyber crime attacks, fraudsters become more sophisticated, with a powerful arsenal of technology in

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Advanced Analytics | SAS Events

Bobby GutierrezAugust 29, 2016 0

Is Poker a Skill Game? A Panel Data Analysis

The annual SAS Analytics Conference is upon us again. This year it is known by a different name, Analytics Experience 2016, but the location, Las Vegas, is the same as it has been the previous two years. Just like last year, I will be attending and presenting on analytics for panel

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Advanced Analytics | SAS Events

Guohui WuAugust 23, 2016 0

Spatial econometric modeling using PROC SPATIALREG

In our previous post, Econometric and statistical methods for spatial data analysis, we discussed the importance of spatial data. For most people, understanding that importance is relatively easy because spatial data are often found in our daily lives and we are all accustomed to analyzing them. We can all relate to

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Advanced Analytics

Simran BaggaAugust 22, 2016 0

3 Steps to big data success with text analytics

A huge proportion of big data is unstructured text (such as client interactions, product reviews, call center logs, emails, blogs and tweets). Organizations starting to invest in advanced analytics often overlook the value text analytics could add to the process. But when data scientists or analysts get to work exploring

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