Customer Profitability Analytics Tutorial NYC: Core Algorithms, Process, + Use Cases

Fitzgerald Analytics is hosting a Customer Profit Analytics Tutorial focused on how to calculate profitability at the customer level.

On April 23rd in NYC, attendees will learn to create a "customer level P&L Statement" for each of their customers, clients, households, etc. Being able to do this accurately is essential to enabling a range of high-impact analytic methods and use-cases.  For more info, and to RSVP, see full event details here. If you would like to attend, you can RSVP here

Event Agenda:

1. Introduction to Customer Profitability Analysis, including it's history, how it has been used in the past, and the role these methods play in analytic work today
2. Customer Profitability Algorithms: we will walk through the specific algorithms you need to use to turn raw data into customer profitability metrics, and share tips on how to customize them depending on your business model, data sources, and how you intend to use the metrics
3. Data Requirements: We will define the data required to implement customer profitability algorithms
4. Process: we will share an efficient process developed over 15 years to plan and execute analytic projects
5. Use Cases: 5 common use-cases of customer profitability will be illustrated to give attendees a sense of how these metrics can be used to achieve specific business objectives

Speakers will include Jaime Fitzgerald, teammates from Fitzgerald Analytics, and possibly others from the Analytics in Financial Services Group. Fitzgerald has been helping clients with Customer Profitability Analytics since the summer of 1996, and it has become an important and recurring theme in our work through the present day.

Additional Resources:  If you are interested in more content on Customer Profitability Analytics and the Fitzgerald Analytics approach to the topic, see below for a number of things we have done in the past related to Customer Analytics:

1. The FA Team put together an event an last year entitled "When Big Data Meets Customer Profit Analytics" -- here are the slides from that event:

Big Data Meets Customer Profitability Analytics from Fitzgerald Analytics, Inc.

1. Jaime Fitzgerald also wrote an article on the topic -- Customer Profitability in the Big Data Era.
2. Jaime Fitzgerald led a Webinar for Dataversity on the topic...the recording of which is available here.

Data to Dollars™ Framework + Methodology - The Book

Jaime Fitzgerald

Save space on your bookshelf, desk, and kindle for The Data to Dollars™ Value Chain:   A Practical Guide to Successful Analytics Projects

Last year Jaime Fitzgerald agreed to write a book based on the methodology used by Fitzgerald Analytics, the consultancy he founded nearly 8 years ago.  The book will be published by Elsevier, under their Morgan Kaufmann imprint.

Fitzgerald's framework (The Data to Dollars Value Chain™) and the associated methodology and toolkit brings structure and efficiency to the messy work of turning data into results, helping teams plan and execute more successful projects.   Keep reading for an introduction to the book what makes it unique.

Abstract:

For many organizations, data has become the ultimate intangible asset.  In raw form, it is useless, yet when used well it becomes priceless.   This book is about the practical, specific, step-by-step process by which data is transformed into concrete value for organizations of all sizes and types.

Unfortunately, relatively few analytics projects, teams, and technology investments achieve their full potential.  When analytics projects go well, the results are extraordinary.  Existing businesses have transformed themselves using analytics, new businesses models have been built on analytics and innovators are using analytics to achieve social goals including saving lives, improving healthcare, and empowering the poor.  Unfortunately, the “dirty secret” is that most analytics projects fail to achieve their potential.
  

This book is a practical guide to creating successful analytics projects, teams, and ongoing initiatives.  It contains all the components of the process, methods, and templates used by Fitzgerald Analytics to help dozens of clients unlock millions of dollars in results.  The benefit of the approach we share in this book is to “reduce the barrier to benefit” from analytics, enabling teams to get more from their analytics effort despite inevitable constraints in budgets, staff talent and experience, knowledge, data quality and availability, and even political barriers within organizations.

Unique Features of the Book:

1.   Unique Framework Addressing a Critical Barrier.  Unlike most books which focus on one or more parts of journey from raw data to concrete results, this book provides map to the entire trip.  What we call the Data to Dollars™ Value Chain is a complex, cross-functional process involving hundreds of steps.  Without a structured framework, roadmap, and toolkit, many analytic efforts fail.  Our framework helps executives, practitioners, and stakeholders from all departments identify opportunities, decide how to capitalize on them, plan, collaborate, execute, and repeat.

2.   Practical Knowledge You Can Use:  This book is not focused on narrative, storytelling, or inspiring case studies.  Instead, it is focused on transferring knowledge the reader can use to improve their own projects, careers, and organizations by using data, analytics, and technology to enhance results. 

3.   Practical Tools and Processes:  The books contents and associated templates will make it unusually feasible for readers to apply our framework, use the methodologies, and adopt the process we share in the book.  The book will make this easier by including illustrated processes, customizable templates, and detailed instructions, both in the book and via electronic files which will accompany the book.

4.   Useful to organizations regardless of size, sector, or geography.   The concepts, best practices, methodologies, and templates in this book can be used by organizations across society, including small and large businesses, government, health care, domestic non-profits, social-entrepreneurs, and international NGOs.  This is possible because while goals and resources vary, our structured process allows better planning and execution for any goal, as long as the organization knows what their goals are.

Neil Raden on Business Intelligence, Tony Baer on Big Data + Convergence

Business Intelligence ROI Remains Elusive; A next-generation approach to “ease of use” may hold the answer

On March 6th, 2013 the Fitzgerald Analytics team attended the quarterly symposium of the TDWI NYC Tri-State Chapter.  The keynote presenter was Neil Raden, founder of CEO of Hired Brains Research and author of a leading book on decision management: Smart Enough Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions.

For decades, Business Intelligence has been seen as both an essential and sometimes disappointing area of technology investment. Billions of dollars have been invested in presenting insights to business managers, but frequently the ROI has been soft and difficult to measure.

Neil Raden has long been concerned about the fact that usage rates for large-sale BI systems has “stalled at 10 to 20 percent of users, depending on which survey you believe.”

Of course BI will survive, but Raden said “we may not recognize it ... the need to analyze and use data will not go away, but BI will be part of a 'decision management continuum' incorporating predictive modeling, machine learning, natural language processing, business rules, traditional BI, visualization, and collaboration capabilities.”

Neil's talk focused on these questions:

∎ Why do many Business Intelligence implementations fail to achieve their potential?
∎ Will a broader definition of the concept enable better results?
∎ How can you optimize BI systems when you are not in complete control?
∎ What best practices and case studies are most instructive?

ROI on Business Intelligence - Neil Raden on Next-Generation "Ease of Use"  

Neil Raden is CEO and Principle Analyst at Hired Brains Research. He is a long-time practitioner, well-known author and consultant focused on data warehousing, Business Intelligence, analytics, big data, and decision sciences. He is the author of "Smart (Enough) Systems,” together with James Taylor. This book focuses on decision automation for optimizing practical business decisions. A favorite topic for Mr. Raden has been how to integrate strategy, planning, management and execution as the tools to achieve optimum decision making.

Neil Raden's talk was followed by a presentation by Tony Baer of Ovum Research entitled " Making Big Data Manageable: Getting Better Results by Managing Big Data Quality"

Intersecting with Neil Raden's keynote, Mr Baer asked “what does it take to turn the promise of Big Data into tangible results?”  Big opportunities to benefit from new technology have come and gone, yet the consistent challenge has been translating new potential into concrete benefits.  Mr. Baer shared a practical perspective on making big data manageable by understanding key challenges you must overcome to leverage big data, especially the unique data quality issues the Big Data sources introduce.

Mr. Baer also shared his insight that while Business Intelligence and Big Data are viewed and managed separately, in reality "Big Data and Business Intelligence must converge." Big Data needs to be approached with "less of a silo mentality," and so does Business Intelligence.

Tony Baer - Big Data and Business Intelligence Must Converge

1.  

Jaime Fitzgerald, Founder and Managing Director at Fitzgerald Analytics, served on the Board of Directors of the TDWI NYC Chapter, and helped organize the event.

Top 10 Books on Analytics -- A Data to Dollars™ Starter Library

Several years ago I created a list on Amazon called  Top 10 Books on Analytics -- A Data to Dollars™ Starter Library which listed 10 books I recommend to my teammates, my clients, and use myself.  

I'm updating the list for 2013 -- what recent books do you believe should to be added?

-Jaime Fitzgerald

Big Data Symposium from TDWI - October 3rd in NYC

Join us for the latest event of the Tri-State NY/NJ/CT Chapter of the Data Warehousing Insitute

For a Symposium Entitled: “Big Data. Social Media”

What’s Real and Worth Learning About?

October 3rd, 2012 8:30 AM – 12:00 PM

Information Builders, Two Penn Plaza, New York City

Event Description Follows:

How are companies using Big Data and Social Media to transform their industry?

Big Data.  Social Media.  What’s real and worth learning about … what is breathless hype?  What's in it for me?  What's the best way to start?  How do I start?

Join the NYC Tri-State TDWI Chapter in Midtown Manhattan on October 3rd to find out.  Register here.

Interest in Big Data has surged in recent years, as new data sources, methods, and technologies expand the frontier of how data can be used.  Yet because the topic is so new, developing a road map to unlock the benefits of Big Data can be a daunting task.

Key questions include:

•               How do we justify, and maximize ROI on our investment in Big Data initiatives?

•               What types of Big Data are most important for our business?

•               When is Social Media data valuable?  How do we decide how to use it?

•               How do we manage Big Data assets in tandem with traditional data assets?

•               What technologies should we use, and how do we fit these into our existing IT stack?

Join us on October 3rd for a practical discussion of Big Data in general, and Social Media data specifically.

KEYNOTE SPEAKER

Glenn Peipert – KPMG BI Practice Director contributing to the planning, growth, leading practices, methodologies, and talent management of both the Information Management and SAP practice. Strategically focused on IT enablement and strategy, transformation, business process improvement, application development, packaged Application implementation, Business Intelligence, Data Warehousing, Information Management, Program Management and Governance. Strong focus on strategic planning through execution and oversight – current/future state, roadmap, budgeting, resourcing, and planning. Strong expertise in financial services (banking, insurance, capital markets), consumer products, pharmaceutical (Life Sciences), entertainment, and publishing.  Founder, Conversion Services International

CASE HISTORY & PRACTITIONER DISCUSSION

A discussion of practical examples, lessons learned, and key success factors will follow.  We will be joined by guests with practical experience unlocking value from Big Data assets.  Drawing from their experience, they will share use-cases, lessons learned, and best practices in areas such as:

1.     Big-data technology:  where to start?  How to setup your first Hadoop cluster?  What other technologies make the transition easier?

2.     Data Visualization:  how and when does it help increase ROI on Big Data initiatives?

3.     The Human Dimension:  what best practices improve the ability of leaders, teams, and individuals to get practical results from Big Data projects?

Confirmed case study participants will include:

Alex Hasha, Chief Data Scientist, Bundle.com (a joint venture between Citi, Microsoft, & Morningstar)

Alexander Hasha is the lead Data Scientist at Bundle.com, the definitive source for information on how people spend, save, and invest their money. Alex is responsible for everything data-related -- from data architecture to MDM to assuring the accuracy of day-to-day statistical analysis. With his team he converts data from diverse sources, including Citigroup, the US Department of Labor, and other third parties, into unique insights available nowhere else. Bundle Corporation is an innovative joint venture of Citi, Morningstar, and MSN Money, and operates the website www.bundle.com. Prior to joining Bundle, Alex worked in analytic modeling at Citigroup in the company's mortgage division, where he also wrote articles for publication. He is a graduate of M.I.T. and earned his Ph.D. in mathematics from NYU's Courant Institute. He also holds an advanced certificate in mathematics from Cambridge University.

Lee Feinberg, Founder of DecisionViz.

Lee is the Founder of DecisionViz, a management consultancy that helps companies “escape the legacy of reporting data by transforming complex data into simple pictures for making decisions.”  He is also the expert author of the BeyeNETWORK channel “HD Visualization – Driving BI & Analytics”

Ten years ago, working with companies generating large amounts of Internet data, Lee realized that visualization would be a disruptive capability. Clients have used his Decision Visualization™ business strategy and DRAW-ON™ visualization services to make data actionable. Industry leaders frequently ask Lee to address domestic and international audiences, most recently including O'Reilly Media Strata, Tableau Software European and North American Customer Conferences, CBS Interactive, and WARC.  He served on Tableau Software's customer advisory board and is the founder of the NJ and NY Tableau Software User Groups. 

Prior to founding DecisionViz, Lee joined Nokia in 2009 with the vision of “making data a part of every conversation.” His team launched data visualization services, providing 1000+ employees access to dashboards and analysis, under the credo "running business intelligence like a business." At Razorfish, Lee established an analytics management practice for the Ford Motor Company. At Digitas, Lee served on IBM’s corporate task force to define online metrics standards and introduced early interactive visualization technology.  Lee received a B.S. and M.S. from Cornell University and holds a U.S. Patent for a PC-telephone interface.  He is a member of the Cornell Entrepreneur Network and the Sandler Sales Institute.  

REGISTRATION

The seminar is open to all business, analytics and information technology managers, with an interest in Business Intelligence, Data Warehousing, Analytics and Healthcare.  There is no fee to attend our program, although pre-registration is required.  Visit the TDWI Chapter Registration Link  or the NYC Tri-State Area Chapter page to register.

We look forward to seeing you there!

Jaime Fitzgerald

Vice-President, TDWI, NY-NJ-CT Region
Member, Board of Directors

Data Discovery for Big Insights - Upcoming Webinar May 17

Jaime Fitzgerald will be the Guest Analyst on a Webinar Featuring Tableau, Focusing on the Role of Data Discovery in Transforming Data into Results.

You can register for free HERE 

May 17, 2012, 12:00PM ET / 9:00 AM PST

More and more data discovery tools are helping organizations transform the volumes of data they produce and collect into a revenue-enhancing resource. Yet many organizations are only scratching the surface when it comes to employing this form of business intelligence, missing opportunities to identify trends, surface business opportunities, reduce losses, and answer critical business questions. Too often, critical data remains locked in obscurity.

Simple steps can amplify the results of organizations’ data discovery efforts, empowering executives, business managers, front-line personnel, and other employees to make informed decisions. By visually exploring data with modern tools, users can compare different scenarios, test assumptions, and get to answers quickly and confidently.

Attend this webinar and learn how to:

• Overcome key challenge, including ever-growing data volumes with shrinking decisions windows
• Foster a culture of data-driven decision making
• Maximize the value of the investment in business intelligence and reporting
• Track and measure success on an ongoing basis

Register to hear BI Consultant Jaime Fitzgerald offer insights for encouraging data discovery in your organization. Fitzgerald will explain best practices for fostering an analytical atmosphere that creates a culture of insightful thinking.

Big Data Meets Customer Profitability Analytics

We are expecting more than 100 attendees at our latest NYC meetup tomorrow, for an event focused on the intersection between Big Data and Customer Profitability analysis.

Customer Profitability Analytics remains a "must have capability" in Financial Services and Beyond, and for many companies there is still a gap in their ability to "know where their profit comes from" at the customer level, client level, and household level.  Customer profitability analysis--and related methodologies--are key enablers of improving KPIs including:

1. Customer Lifetime Value ("CLV")
2. Customer loyalty and retention
3. Share of wallet maximization
4. Marketing ROI
5. Impact of Customer Service, Customer Experience, and Customer Satisfaction on Profit
6. Product design, pricing, promotion, and positioning
7. Allocation of resources (capital, budget, HR, etc)

While "Big Data" is arguably the biggest buzzword in data science today, you "can't deposit data in the bank" no matter how big it is!

This event will focus on a key question:   how does big data and related technology enhance the potential of customer analytics?  In what ways have best practices in Customer Profit analytics stayed the same, and in what ways does Big Data create new potential in this domain?

The discussion will be moderated by Jaime Fitzgerald, founder of consulting firm Fitzgerald Analytics.  The firm helps clients improve results through better use of data, technology, and analytics, and was named a “Best Small Consulting Firm to Work For” two years in a row.  Jaime has extensive experience in Customer Profitability Analysis, Data Management, and Big Data and is a frequent speaker on these topics. 

Jaime will be joined by co-presenters with first-hand experience in various dimensions of the problem, including current and former analysts at Deutsche Bank, Credit Suisse, Citi, and the credit card division of Bridgestone Firestone.  The presentation and Q&A will be highly interactive, and focused on practical insights that can be applied to improve results.

Live Radio Today - The Art of Harnessing Unwieldy Data

I’ll be doing a live panel interview today @ 3PM with DM Radio. on The Art of Harnessing Unwieldy Data Big & Small.  Easy to register, and will be a fun conversation.

The show is moderated by Eric Kavanagh & Jim Ericson of InformationWeek Magazine.

On the show, I'll frame the discussion from a Analytics and Data to Dollars™ point of view, then participate in a round-table discussion with subject matter experts and cutting-edge technology innovators including:

1. Suresh Chandrasekaran of Denodo, 
2. Sean Martin of Cambridge Semantics, and 
3. Grant Ingersoll of Lucid Imagination.

 Join if you can!

"Beginning with the End in Mind" - Habits of Highly Effective Data Professionals

What if Steven Covey was a technologist, data professional, or data scientist? Would the best-selling author–best known for promoting his ”Seven Habits of Highly Effective People“–have thrived in today’s data-driven world?

We explore this question in Habits of Highly Effective Data Professionals , our latest post on DATAVERSITY.

We believe he could have thrived, if he adapted to the complexity and practical realities of working with data and technology. Like today’s best data pros, he would have succeeded by combining technical skills with the principle of “Beginning with the End in Mind” (Habit #2). He would also have needed to take the next step, rolling his sleeves up and figuring out HOW to achieve his most essential goals.

We call this key next step ”Causal Clarity™,” by which we mean achieving a clear vision for HOW a goal will be achieved. What will cause the desired result? What are the preconditions? What are the sequence of steps–sometimes thousands of them–that lie between the current state and the desired state?

Read the Entire Article Here...

Data Management & the Netflix Qwikster Stumble

After decades building his reputation as one of the most data-savvy, customer centric, and innovative corporate leaders of our generation, the Netflix CEO stumbled badly when he announced plans to split Netflix operations into two separate businesses. After a barrage of criticism from customers, stockholders and analysts, Netflix announced Monday that it will abandon the ill-fated plan.

In our Latest Post at DATAVERSITY, we comment on the data management implications of the much-debated Qwikster debacle. Surprisingly, the same company that sponsored the pioneering Netflix Challenge—effectively crowd-sourcing the optimization of their movie recommendation model–was planning to intentionally create a less integrated, less customer-friendly version of itself.

Read the whole article here...