Thomas H. Davenport, best-selling co-author of Competing on Analytics and Analytics at Work, and President's Distinguished Professor at Babson College presented at the Premier Business Leadership Series 2010 http://www.sas.com/theserieshk
Davenport will present straightforward, practical advice from his new book Analytics at Work: Smarter Decisions, Better Results, including laying out a plan of action for deploying and succeeding with business analytics inside your company.
Learn how to:
- Use an analytics approach to run your business.
Put the right assets in place and deploy them most effectively.
- Launch an analytics initiative.
- Sustain an analytics focus over time.
- Evaluate your organisation's current analytical capabilities.
- Use analytics to make better decisions.
Thomas H. Davenport, best-selling co-author of Competing on Analytics and Analytics at Work, and President's Distinguished Professor at Babson College presented at the Premier Business Leadership Series 2010 http://www.sas.com/theserieshk
Davenport will present straightforward, practical advice from his new book Analytics at Work: Smarter Decisions, Better Results, including laying out a plan of action for deploying and succeeding with business analytics inside your company.
Learn how to:
- Use an analytics approach to run your business.
Put the right assets in place and deploy them most effectively.
- Launch an analytics initiative.
- Sustain an analytics focus over time.
- Evaluate your organisation's current analytical capabilities.
- Use analytics to make better decisions.
The New Normal: Predictive Power on the Front LinesInside Analysis
The Briefing Room with Mike Ferguson and Alteryx
Live Webcast on Feb. 12, 2013
Today's savvy organizations know that a streamlined approach to data and applications can put the power of predictive analytics right where it needs to be: in the hands of the user. Sure, training is still required, but a real revolution is underway for the graphic design of such user interfaces. Central to this overhaul of design is the concept of intelligent, simple workflow, which enables users to get things done in an orderly fashion.
Check out the slides for this episode of The Briefing Room to hear analyst Mike Ferguson of Intelligent Business Strategies as he explains why interface design and workflow must go hand-in-hand. He will be briefed by Matt Madden of Alteryx, who will tout his company’s predictive platform, a solution that leverages an array of traditional and Big Data analytics applications, designed for problem solvers and decision makers. Madden will also provide several customer use cases that demonstrate the new normal in predictive analytics.
Vilka framgångsfaktorer har allra störst inverkan på skapandet av den optimala kundupplevelsen? Utnyttja denna information för att på ett smartare sätt förstå, förutsäga och påverka kundernas beteende.
Robert Moberg, Prediktiv Analysexpert, IBM Sverige
Evaluating Big Data Predictive Analytics PlatformsTeradata Aster
Mike Gualtieri, Principal Analyst, Forrester Research, presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012
Presentation title: Evaluating Big Data Predictive Analytics Platforms
Abstract: Great. You have Big Data. Now what? You have to analyze it to find game-changing predictive models that you can use to make smart decisions, reduce risk, or deliver breakthrough customer experiences. Big Data Predictive Analytics solutions are software and/or hardware solutions that allow firms to discover, evaluate, optimize, and deploy predictive models by analyzing big data sources. In this session, Forrester Principal Analyst Mike Gualtieri will discuss the key criteria you should use to evaluate Big Data Predictive Analytics platforms to meet your specific needs.
How To Make The Most Out of Enterprise DataSnapShot
CHAT 2016 - China Hotel And Tourism Conference Presentation by Stefan Tweraser. SnapShot Hotel Analytics CEO Stefan Tweraser explains how business leaders can make the most out of the data available to them.
DAMA Webinar: What Does "Manage Data Assets" Really Mean?DATAVERSITY
For nearly a generation, managers have exhorted their organizations to “manage data as business assets.” But relatively little has happened, perhaps because the logical follow-up question, “what exactly should we do differently?” goes unanswered.
This presentation answers that question. It makes three mutually-reinforcing “prescriptions” and shows how leading companies follow them. Specifically:
1.Take care of the data: Focus on the data with the greatest market potential and improve by at least an order of magnitude.
2.Put the data to work. Use them to make data-driven decisions, to enhance existing products and services, and to find and exploit previously-hidden insights (e.g., analytics and big data).
3.Advance the management system. Today’s organizations can only be described as “unfit for data.” Getting the right people in the right jobs and having all who touch data contribute is essential.
Lecture notes on being Data-Driven and doing Data Science Johan Himberg
Visiting lecture held at Aalto University School of Business on prof. Pekka Malo's course "Data Science for Business". Lecture given by Johan Himberg and Jaakko Särelä (@ReaktorNow)
MeshLabs is a pure-play developer of text analytics software. Our core product is a hybrid text analytics engine, that combines linguistic (NLP), statistic, and semantic approaches to process large volumes of unstructured and structured content. Built to enterprise performance standards, the engine offers flexible integration capabilities including content connectors and APIs. We are a team of information retrieval professionals who are passionate about solving complex unstructured data processing problems for a variety of industries. Our product is deployed at large enterprises globally. We specialize in developing products using emerging content processing technologies to solve complex customer experience management problems. I can discuss with you specific ideas, best practices, and case studies.
The New Normal: Predictive Power on the Front LinesInside Analysis
The Briefing Room with Mike Ferguson and Alteryx
Live Webcast on Feb. 12, 2013
Today's savvy organizations know that a streamlined approach to data and applications can put the power of predictive analytics right where it needs to be: in the hands of the user. Sure, training is still required, but a real revolution is underway for the graphic design of such user interfaces. Central to this overhaul of design is the concept of intelligent, simple workflow, which enables users to get things done in an orderly fashion.
Check out the slides for this episode of The Briefing Room to hear analyst Mike Ferguson of Intelligent Business Strategies as he explains why interface design and workflow must go hand-in-hand. He will be briefed by Matt Madden of Alteryx, who will tout his company’s predictive platform, a solution that leverages an array of traditional and Big Data analytics applications, designed for problem solvers and decision makers. Madden will also provide several customer use cases that demonstrate the new normal in predictive analytics.
Vilka framgångsfaktorer har allra störst inverkan på skapandet av den optimala kundupplevelsen? Utnyttja denna information för att på ett smartare sätt förstå, förutsäga och påverka kundernas beteende.
Robert Moberg, Prediktiv Analysexpert, IBM Sverige
Evaluating Big Data Predictive Analytics PlatformsTeradata Aster
Mike Gualtieri, Principal Analyst, Forrester Research, presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012
Presentation title: Evaluating Big Data Predictive Analytics Platforms
Abstract: Great. You have Big Data. Now what? You have to analyze it to find game-changing predictive models that you can use to make smart decisions, reduce risk, or deliver breakthrough customer experiences. Big Data Predictive Analytics solutions are software and/or hardware solutions that allow firms to discover, evaluate, optimize, and deploy predictive models by analyzing big data sources. In this session, Forrester Principal Analyst Mike Gualtieri will discuss the key criteria you should use to evaluate Big Data Predictive Analytics platforms to meet your specific needs.
How To Make The Most Out of Enterprise DataSnapShot
CHAT 2016 - China Hotel And Tourism Conference Presentation by Stefan Tweraser. SnapShot Hotel Analytics CEO Stefan Tweraser explains how business leaders can make the most out of the data available to them.
DAMA Webinar: What Does "Manage Data Assets" Really Mean?DATAVERSITY
For nearly a generation, managers have exhorted their organizations to “manage data as business assets.” But relatively little has happened, perhaps because the logical follow-up question, “what exactly should we do differently?” goes unanswered.
This presentation answers that question. It makes three mutually-reinforcing “prescriptions” and shows how leading companies follow them. Specifically:
1.Take care of the data: Focus on the data with the greatest market potential and improve by at least an order of magnitude.
2.Put the data to work. Use them to make data-driven decisions, to enhance existing products and services, and to find and exploit previously-hidden insights (e.g., analytics and big data).
3.Advance the management system. Today’s organizations can only be described as “unfit for data.” Getting the right people in the right jobs and having all who touch data contribute is essential.
Lecture notes on being Data-Driven and doing Data Science Johan Himberg
Visiting lecture held at Aalto University School of Business on prof. Pekka Malo's course "Data Science for Business". Lecture given by Johan Himberg and Jaakko Särelä (@ReaktorNow)
MeshLabs is a pure-play developer of text analytics software. Our core product is a hybrid text analytics engine, that combines linguistic (NLP), statistic, and semantic approaches to process large volumes of unstructured and structured content. Built to enterprise performance standards, the engine offers flexible integration capabilities including content connectors and APIs. We are a team of information retrieval professionals who are passionate about solving complex unstructured data processing problems for a variety of industries. Our product is deployed at large enterprises globally. We specialize in developing products using emerging content processing technologies to solve complex customer experience management problems. I can discuss with you specific ideas, best practices, and case studies.
Similar to 1. thurs 930 1030 davenport - keynote (20)
5. What Are Analytics?
Optimization “What’s the best that can happen?”
Predictive Modeling/ “What will happen next?” Predictive and
Forecasting
Prescriptive
Randomized Testing “What happens if we try this?”
Analytics
Degree Statistical analysis “Why is this happening?”
(the “so what”)
of Intelligence
Alerts “What actions are needed?”
Query/drill down “What exactly is the problem?” Descriptive
Analytics
Ad hoc reports “How many, how often, where?”
(the “what”)
Standard Reports “What happened?”
5 Thomas H. Davenport – Analytics at Work 5
6. Levels of Analytical Capability
Stage 5
Analytical
Competitors
Stage 4
Analytical Companies
Stage 3
Analytical Aspirations
Stage 2
Localized Analytics
Stage 1
Analytically Impaired
Thomas H. Davenport – Analytics at Work
6
7. Analytical Competitors
Old Hands, Turnarounds, Born Analytical
Marriott — Revenue management
UPS — Operations and logistics, then customer
Progressive— risk, pricing
• Harrah’s — Loyalty and service
• Tesco — Loyalty and internet groceries
• MCI/Worldcom— Cost identification and reduction
• Capital One— “information-based strategy”
• Google — page rank, advertising, HR
• Netflix— customer preference algorithms
7 Thomas H. Davenport – Analytics at Work
8. Analytical Competitors or Companies
Across Industries
Financial Services Consumer Products Hospitality/ Entertainment
• Wellpoint • E&J Gallo • Harrah’s Entertainment
• Progressive Insurance • Mars • Marriott International
• Barclays Bank • Procter & Gamble • New England Patriots
• Capital One • Boston Red Sox
• Royal Bank of Canada • AC Milan
Industrial Products Pharmaceuticals
• Astra Zeneca Retail
• CEMEX • Amazon
• Merck
• John Deere & Company • Tesco
• Vertex
• Wal-Mart
Telecommunications Transport • JCPenney
• O2 • FedEx eCommerce
• Rogers Telecom • Schneider National • Yahoo
• Cablecom • United Parcel Service • Ebay
• Expedia
8 Thomas H. Davenport – Analytics at Work 8
17. The Context: Analytical Culture
• Facts, evidence, analysis as the primary
way of deciding
• Pervasive “test and learn” emphasis where
there aren’t facts
• Free pass for pushbacks—”Where’s your
data?”
• Still room for intuition based on experience
• A focus on action after analysis
• Never resting on your analytical laurels
17 | Thomas H. Davenport – Analytics at Work
18. The Context: Analytical Processes
Defection Risk
Creation
Purchase Order “What is the customer status?”
Creation
Request Global ATP Inventory Forecast
Sales Order “Will this be back in inventory?”
Global ATP Check
Fulfillment Request
Creation &
Release Delivery
Request
Returns per Customer
“What is the customer history?”
CLTV
Delivery “Does this order justify extra efforts?”
Execution
Update Update
Releases ASN
Inventory Accounting Inventory
Delivery Performance
Receives ASN “How effective is our fulfillment
process?”
Source: SAP AG 2006
18 Thomas H. Davenport – Analytics at Work
23. Multiple Interventions:
Better Pricing Decisions at Stanley
Pricing identified as one of four key decision domains by CIO
Pricing Center of Excellence established in 2003
Adopted several difference pricing methodologies
Implemented new pricing optimization software
Regular “Gross Margin Calls” for senior managers
Offshore capability gathers competitive pricing data
Some automated pricing systems, e.g., for promotions
Center spreads innovations across Stanley
Result: gross margin from 34% to over 40% in six years
23 Thomas H. Davenport – Analytics at Work