The Analtyics Lens
August 2011 :: Volume 1 :: Issue 1
In This Issue
A Welcome from the President
A Note from The Analytics Lens Newsletter Editor
Report on the State of the Analytics Section
Analytics, O.R., and INFORMS - Where the Three Meet
Summary of INFORMS Membership Survey Results
Practice Update
Analytics Success Stories: Revenue Management Audit
UPS and Analytics; Winning the Gartner Business Intelligence Award
Section Website Now Features Analytics Process Videos
A Welcome from the President

Welcome to the INFORMS Analytics Section!

The Analytics Section is the newest section of INFORMS. I am honored to be the section's first President, and hope to get the group off to a great start. Below, I talk about the Analytics Section progress to date, objectives and future plans,

I have some great help; my fellow officers who are all top-notch: Vice President - Zahir Balaporia (Schneider National), Treasurer - Warren Lieberman (Veritec Solutions) and Secretary - Doug Mohr (UPS). We are working hard to build a first-class organization.

We are in search of volunteers for a number of positions - webmaster for our site, bloggers, and a newsletter editor. Please consider contributing!

I hope to see many of you at an upcoming conference. Until then, feel free to contact me at [email protected].

Sincerely,

Michael F. Gorman
INFORMS Analytics Section President
University of Dayton Department of MIS, OM and DSC
President, MFG Consulting, Inc.

A Note from The Analytics Lens Newsletter Editor
Michael F. Gorman

I am pleased to act as editor of The Analytics Lens, the Analytics Section's newsletter. This is the first issue of what is planned to be a "periodic" newsletter; we are shooting for quarterly, with a minimum of two newsletters per year (one before each INFORMS conference). The frequency of the newsletter issues depends in part in the interest from the membership in contributing to the content of the newsletter

In this, our first newsletter, Analytics Section members will be the first to read about the recent INFORMS survey responses about the role of analytics in INFORMS by Matt Libertore and Wenhong Luo. We also report on the state of the Analytics Section. I share my thoughts on O.R. and analytics - synergies and similarities. Warren Lieberman shares an "Analytics Success Story". Jack Levis discusses the INFORMS Practice update and recounts how UPS won the Gartner Business Intelligence Award.

As the newsletter editor, I am in search of contributors to future issues in order to increase the quantity, quality, and diversity of content. I am extremely pleased with the help I have received in this newsletter from contributors, the more the merrier! Please feel free to suggest topics you would like to read about, or to which you would like to contribute a short article.

For the fall newsletter, I plan to offer brief articles introducing some of the Annual Meeting presentations, and an Analytics Section guide to the conference - topics, sessions, and tracks of interest to members of the Analytics Section - to help you navigate the conference and get the most out of it. I am seeking volunteers to put me out of a job - that is, act as the editor of this newsletter!

Please contact me if you are interested in contributing in any way. [email protected].

Report on the State of the Analytics Section
Michael F. Gorman

In April 2011, at the INFORMS Conference on Business Analytics and Operations Research in Chicago, INFORMS announced the formation of the new Analytics Section of INFORMS. INFORMS is perfectly suited to take advantage of the growing awareness of and trend towards analytical decision making.

The Analytics Section welcomes existing INFORMS members to join, and hopes to attract non-INFORMS members who might not have otherwise considered joining INFORMS. The section is off to a quick start - we have grown to over 400 members in our first few months; see graphic below. This is astounding growth and far exceeds anyone's expectations for the section at this early date.

(If you are not yet a member, please join! It is free for 2011)

Analytics Section Membership
We have a website developed, and an active LinkedIn group. This is our first newsletter - and we plan to send a second issue in the fall. Finally, we have a 13 session Analytics track planned for the fall 2011 conference in Charlotte that will be detailed in our next newsletter.

Future plans include maintaining an active role in the spring INFORMS Analytics Conference in Huntington Beach, California, and further development of our vision for the future of the INFORMS Analytics Section.

Come join us at our business meeting at the fall conference and help us establish the future direction of our section and the broader INFORMS community. I hope many of you will speak up, volunteer, join in the conversation, and help shape our direction for years to come.

The success of this organization requires your input!

Analytics, O.R., and INFORMS - Where the Three Meet
Michael F. Gorman

A recent survey asked the question of INFORMS members - what is the relationship of operations research and analytics? (See the results of that survey in an article below.)

O.R. and Analytics
The Encyclopedia of OR/MS (Gass and Harrs, ed.) defines OR/MS in brief as "the science of operational processes, decision making and management". The book proceeds to cover hundreds of topics, from A* Algorithms to zero sum games. Wikipedia provides the following definition of O.R.: Operations research (also referred to as decision science or management science) is an interdisciplinary mathematical science that focuses on the effective use of technology by organizations. Some of the tools used by operational researchers are statistics, optimization, probability theory, queuing theory, game theory, graph theory, decision analysis, mathematical modeling and simulation.

In his book, Competing on Analytics, Tom Davenport defines "analytical competitor" as an organization that uses analytics extensively and systematically to outthink and out execute the competition.

My read on these definitions is that there is not a big difference between analytics and OR/MS, but a difference in their relative emphases. Both areas discuss the application of advanced techniques by organizations. However, O.R. clearly emphasizes the tools and techniques; analytics emphasizes more the analytical process, the tool application and integration, and their impact on organizational competitiveness and efficiency.

Analytics Section and INFORMS
A better question for the current audience might have been what is the relationship of analytics (and this section) and INFORMS?

The INFORMS Vision Statement reads, "INFORMS is recognized as the premier organization for advancing the profession, practice, and science of operations research and management science." And its mission statement discusses dissemination of OR/MS excellence and achievements via journals, magazines and other media, and providing OR/MS education and career opportunities.

On our section website, we state that: The Analytics Section is focused on promoting the use of data-driven analytics and fact-based decision making in practice. The section recognizes that analytics is seen as both a complete business problem solving and decision making process, and a broad set of analytical methodologies that enable the creation of business value. The Analytics Section promotes the integration of a wide range of analytical techniques and the end-to-end analytics process. Analytic methodologies include descriptive techniques (what happened), predictive techniques (what will happen), and prescriptive techniques (what should happen).

The section will support activities that illuminate significant innovations and achievements in specific steps and/or in the execution of the process as a whole, where success is defined by the impact on business decision making. The Analytics Section will leverage INFORMS academic integrity to establish INFORMS as the thought leaders of the analytics movement, focusing on the predictive and prescriptive space.

In a similar way to the definitional differences of O.R. and analytics, where INFORMS focuses somewhat on advancing the tools and techniques that in many ways empowers the analytics movement, analytics is about creating a vision, selling an idea, seizing the opportunity, selecting of tools and technologies, managing the implementation process, mapping the data requirements and systems integration, and leading and sustaining the organizational change that allow O.R. to deliver on its promise. As I developed this sentence, I changed it three times; my point is that my understanding is always evolving.

In some ways, analytics is "what we have always done" at INFORMS - develop tools that enable better decisions, but in other ways, is what perhaps we could do better - advocating, explaining, demonstrating, socializing and delivering the benefits of O.R. to establish its central place in organizations efforts to make better decisions. Thus, Analytics and INFORMS go hand in glove, and both can benefit from the integration of the two - as I imagine you will agree, as a member of the Analytics Section of INFORMS!

Value Proposition for the Analytics Section
In my assessment, the Analytics Section was created for two reasons: 1) To introduce the INFORMS' membership to this very hot new wave in business, and 2) To invite analytics professionals into the INFORMS organization, whose skills sets align perfectly with the analytics movement. Thus, we have the confluence of two very different groups coming together in our section - INFORMS members wanting to learn more about analytics, and analytics professionals who want to learn more about INFORMS. We take the value proposition for each in turn.

Analytics Section for the INFORMS Member
The INFORMS member who joins the Analytics Section is taking advantage of a booming trend in business and becoming identified with practitioner terms for what INFORMS is known for. Members of the section will learn what all the analytics buzz is about -- and help to shape its evolution. The INFORMS member will broaden their understanding of implementing O.R. methodologies in practice, and will see examples of the integration of multiple tool sets for addressing practical problems. Coming to understand the process of analytics, and how O.R. methodologies fit into that process furthers the cause of seeing O.R. methodologies successfully implemented despite the organizational, financial, change management issues surrounding analytics projects. Many MIS colleagues would suggest that analytics is simply the evolution of business intelligence; the Analytics Section will help to understand the interplay of business intelligence databases and O.R. methodologies. Simply, the INFORMS member who joins the Analytics Section will help advance the awareness and use of O.R. methodologies, which is a core mission of INFORMS.

INFORMS Analytics Section for the Analytics Professional
The Analytics Section is a gateway for you to a large, diverse organization - INFORMS - that has established itself as the premier organization for the advancement of Operations Research and Management Science methodologies. As such, INFORMS brings to the Analytics professional a host of the most advanced predictive (statistical, simulation) and prescriptive (optimization) methodologies available to tackle the toughest analytical problems. These leading edge techniques are coupled with the academic integrity on which INFORMS was founded and continues to rely. While its academic base is rock solid, the analytics professional will find many interest groups, sessions and presentations that focus on the application of analytics, as well as a host of tutorials and software demonstrations to show how to put these techniques into action. The ability to meet O.R. experts and other analytics professionals and discuss analytics issues will help us forge a greater understanding of how analytics techniques are used - and overcome obstacles for why they are not used - in practice. Meeting, socializing and learning with like-minded individuals is at the heart of our section.

surveyresultsSummary of INFORMS Membership Survey Results

Matthew J. Liberatore, Ph.D., Wenhong Luo, Ph.D.

The purpose of the survey research is to assess the attitude of INFORMS members with respect to analytics and INFORMS expansion into analytics. A total of 8,335 emails were sent to INFORMS members with 8,217 delivered, 1,932 responses received, and 1,892 surveys included in the analysis for a response rate of 1,892/8,217, or 23.0%. The survey respondents represent the membership quite well in terms of age, gender, education, and region with some minor differences. A somewhat higher proportion of practitioner members and those older than 45 responded to the survey.

About 64% of the respondents indicated that they were at least somewhat familiar with analytics (a "4" or "5" rating). The mean analytics familiarity rating was 3.77. The respondents strongly agreed with both the method and process definitions of analytics. There is a small group of respondents who indicated that analytics is the same as operations research (6%) or analytics is independent of operations research (7%). However, 87% of the respondents indicated that analytics and operations research are related. Their views are evenly divided across three relationships: analytics is a subset of O.R., O.R. is a subset of analytics, and there is an intersection between the two fields.

The respondents agreed that there are significant benefits associated with expanding into analytics, and disagreed that there are significant risks (all items significant at p = 0.001). The highest rated benefit was enhancing INFORMS' ability to advance the goal of improving decision making in organizations (4.17). The responding members also significantly supported every proposed activity associated with expanding into analytics. In addition, the respondents strongly and significantly supported the overall proposal of INFORMS' expanding into analytics (mean overall support level = 4.11). Only 5% of the respondents strongly disagreed or disagreed with INFORMS overall expansion into analytics. The respondents reported that they planned to get involved in selected analytics activities, i.e., joining an online community, joining the section on analytics, subscribing to a publication, and participating in a conference (all statistically significant). On the other hand, they are less likely to participate in contributing to a forum, participating in a job fair, getting certified in analytics, participating as chair, presenting a talk, engaging in social media, and taking a course.

While younger members were less familiar with analytics, they tended to perceive more benefits and are more likely to support and get involved with analytics. There was no significant effect of age on perceived risks. No significant effects were found concerning gender on familiarity with analytics, benefits, risks, support or involvement.

Individuals holding master's and doctoral degrees reported a higher level of familiarity with analytics, but increasing education is associated with somewhat lesser support and involvement, but all levels of education offer strong support. There was no significant effect of education background on benefits. U.S./Canada members had the highest familiarity and perceived benefits, while Asia/Pacific had the highest support and involvement. Finally, while academics and practitioners showed no significant differences in their perceived benefits and risks, practitioners were more familiar with analytics and were more willing to support and get involved with analytics activities.

The results show that the INFORMS membership overall perceived great benefits and limited risks and thus offered strong support for INFORMS expansion into analytics. However, their expected involvement in INFORMS analytics-oriented activities is more selective. In addition, it is found that members' age, education level, and affiliation affect their views on the expansion.

 

Practice Update
Jack Levis, UPS

There has been a tremendous amount of activity going on at INFORMS surrounding Practice, and I'm excited to tell you about it.

Of course, the main event for practice at INFORMS is the INFORMS Conference on Business Analytics and Operations Research. This was formerly the INFORMS Practice Conference and much more was changed than just the name. Tracks were organized to be more vertical in nature and a track on the process of Analytics was created. More content was added to the executive forum, and a panel of prestigious experts was assembled to discuss how to manage an Analytics organization.

We did what we preach. We gathered data through the Capgemini study and reacted to the data. The conference changes were the result of what was learned from the study. The result was stunning. Attendance to the conference was 30% greater than our previous all-time high.

I'm equally excited that INFORMS has the Analytics section as a new community. I would like to see value added content come from this section and it be the first stopping point for new practitioner members into INFORMS.

These new members will want help in navigating all facets of analytics from Descriptive, to Predictive, and Prescriptive analytics. They will want support for the entire analytics process. If done right, the support and content provided by the Analytics Section will entice professionals to join INFORMS and remain active members.

As good analysts do, we are gathering and analyzing more data. Data on how analytics practitioners view operations research and analytics. We are also doing a deeper dive into the business case for credentialing analytics. Information from these studies should be available shortly.

We would like INFORMS to be seen as the premiere association for advanced analytics professionals.

Analytics Success Stories:
Revenue Management Audit
Warren Lieberman, www.veritecsolutions.com

Overview
Veritec Solutions (www.veritecsolutions.com) was asked to conduct a technical audit of a revenue management system and an organizational and business process assessment of revenue management decision-making for a passenger railroad. We identified deficiencies that were reducing the effectiveness of revenue management decisions and made a number of recommendations to correct the problems. Our findings included:
  • Systematic inaccuracies in the demand forecasts resulted in inappropriate feeds to the optimization model, leading to poor inventory control recommendations.
  • The firm's approach to pricing was leading to poor customer service and was not well structured to support revenue management.
  • Lack of senior management support for revenue management was leading to departmental conflict, inconsistent implementation of revenue management controls, and lowered the priority of obtaining needed system maintenance and enhancements from the Information Technology Department.
  • The Revenue Management Department suffered from poor leadership, often leading to poor revenue management decisions.
  • Expanded training and educational efforts for Revenue Management and other staff was needed.
  • Current plans for reorganizing the Revenue Management Department were likely to further deteriorate the quality of revenue management decisions.
  • A lack of credible performance measures resulted in conflicting signals on the impacts of revenue management decision-making and often led to inappropriate "corrective" action.
For each of these findings, and many others, detailed recommendations for corrective action were made.

Approach
To carry out this assignment, Veritec interviewed staff in multiple departments and at multiple levels within the organization. In addition, we reviewed system documentation, training materials, performance reports, and internal correspondence and reporting. We also designed a database into which historical data was downloaded and from which we conducted a variety of data analyses. We provided interim updates to the client during the audit, obtaining feedback to determine whether and how we should shift the focus of our investigation. The following discussion provides additional detail on one of our focus areas, the demand forecasting system.

Reviewing system documentation, in conjunction with information we gathered from our staff interviews, we began to form a hypothesis that the forecasting component of the system was systematically providing estimates of demand that could undermine the validity of the system's recommendations. As we examined the situation in greater detail, including the technical specifications of the forecasting algorithms, we evaluated how the systematic bias that we suspected to be inherent in the forecast would affect the optimization module and the resulting inventory control recommendations.

The demand forecasting module combined a time-series forecast based on historical demand patterns with a booking profile based forecast to get a final forecast estimate of demand. Veritec's team found a systematic overestimation bias in the booking profile forecast. The booking profile forecast estimated the demand at departure based on the historical average of the percentage of incremental bookings received between a data reading date and departure. The functional form of the booking profile forecast is a "multiplicative" model. Our experience in several industries over the past 10 years has shown this form to be relatively unstable; for example, it tends to overforecast demand when there is a spike in demand. In addition, this forecasting method also tends to overforecast early in the booking process if only a few more reservations than average are accepted. To counteract this situation, a variety of filters and self-correction mechanisms can be implemented. As we reviewed the outputs of the forecasting system with our client staff, we determined that the forecasting system appeared to lack appropriate these checks and balances.

Using historical departure and reservations data, we then conducted a series of data analyses to see if our expectations held under a wide variety of scenarios. The results were quite conclusive. The analyses demonstrated an extremely strong bias in the forecast, a bias that our client had not previously recognized. Armed with this information, we then demonstrated how this forecasting bias would affect the results of the optimization process. Our expectations were consistent with the client's experience and led Veritec to make recommendations on how the forecasting module could be improved.

Best Practice Insights
The Revenue Management Audit focused on the usefulness and accuracy of predictive and prescriptive analytics in a system that for many firms can be mission-critical. As we carried out this work, we were reminded of three items that might be reasonably characterized as best practice insights for analytical efforts:

Trust but Verify. Veritec conducted interviews with more than 25 staff. Sometimes, the information we received from staff members conflicted. Sometimes, the information we received did not turn out to be as accurate as was portrayed. In many cases, however, we were able to carry out data analyses on historical transaction data that provided the understandings we needed. When individual perceptions were far from reality, trying to understand why the perceptions might have developed often led us to insights that we could communicate and helped us gain credibility when presenting our findings.

Believe what you measure. It's not enough just to measure performance; the measures must be credible. While a variety of metrics to measure the performance of the department and their decisions existed, they didn't support what senior executives and key individuals outside the department observed. Over time, support for the department's decisions eroded; tough decisions could no longer be made. In this particular situation, the performance metrics were not designed well, and no one within the department had turned a critical eye towards correcting the situation. Proposing new performance metrics that were credible indicators of the impact of departmental decisions was critical for helping the department overcome high level corporate directives that were producing lower revenues and profits than might otherwise have been achieved.

It all starts with the data. Decision support systems need care and maintenance. System parameters need to be updated. Over time, staff turnover led to a loss of institutional knowledge. Required maintenance and updates were forgotten. Decision support models no longer performed as well as they could.

Warren Lieberman is President of Veritec Solutions. Veritec is a consulting and software firm with a focus on price optimization and revenue management analytics. For more information, please contact [email protected].
UPS and Analytics; Winning the Gartner Business Intelligence Award
Jack Levis, UPS

INFORMS has described three categories of analytics; Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. The prerequisite, of course is data gathering. As organizations grow in analytical maturity, they move up the analytics ladder and reap the increased reward of advanced analytics.

A little over ten years ago, I was named the project manager for a large "game changing" program at UPS. I didn't know it at the time, but this was an analytics program. We grew from descriptive analytics, to predictive analytics, to prescriptive analytics. On a whim, I decided to enter UPS into the Gartner Business Intelligence Excellence Award competition to tell of our journey through analytics.

We already had a strong engineering method for running our business. We employ thousands of engineers and for over 60 years have been refining methods, measurement, and procedures. We needed to look ahead however, as we had exhausted the efficiencies of traditional methods. Our CEO had three goals for the endeavor. Reduce cost, improve service, and offer new first of their kind products. His goal was to be a "one to one" business. Where we could treat every customer, every package as if it were the only one we had. To do this we would need a data architecture and model that knows where every package is every minute, where it needs to go, and why.

This was a data project. We had to unite data from around the enterprise into a consolidated architecture that modeled the business. Much of the data was informal, residing in spreadsheets or just in peoples' heads. We were building a real time system, and for the first time in our history, if a system failed or data was incorrect packages would not get delivered.

My experience with projects and operations research taught me to never underestimate the complications in getting sound data and that was the case here. Economically solving the data problem was the biggest hurdle to overcome. This meant not only gathering the data, but providing systems and processes to keep it maintained and accurate each and every day. With the data problems resolved, Business Intelligence (analytics) could proliferate throughout every part of the operation. The key was making information available to employees so that they could make better decisions. The drivers' handheld computers (DIAD) that used to be a data acquisition device changed to an information assistant.

Information on every package and customer is sent to the DIAD with the unique demands and characteristics. Drivers now can see electronically all the work they need to complete and plan their day accordingly through their DIAD device. The DIAD know the time every package needs to be delivered, what services were promised (COD, Signature required, etc.), and where inside the vehicle the package is loaded. It also knows many of the individual desires of our customers (where to deliver, which neighbor to give to if not home, where to park, phone number, etc.).

The itinerary can be viewed multiple ways and the DIAD is smart enough to double check that all requests are properly met. It ensures that our promises are kept, and even has functionality that checks if a package is delivered to the wrong location. All through the use of data.

Admittedly, it's hard to tell if this portion of the system is analytics or just plain software engineering. But, O.R. and Analytics are about making better decisions, and the information provided to drivers allows them to make better decisions and better serve our customers. Helping drivers make better decisions through information is one piece of the puzzle, but planners must decide what territory goes on each route and the general order drivers will follow to serve their customers. This is where some advanced analytics comes into play.

Through EDI, even before a package is picked up forecasts are sent to the destination alerting them of future deliveries. The information is updated throughout the package's lifecycle within the UPS system. Statistical forecasting systems merge historical information, pending pickups, and ones already in our system to create a nice forecast of the future.

A couple of days before the actual delivery day, planning systems analyze the forecast, and point out routes that have too much work, too little work, or inefficient work. The forecasts are updated in real time all the way up to a driver leaving the building with that day's packages. Planners can then move appropriate work between drivers to ensure the right packages are on the right route each day. Through the use of integrated data, predictions, and systems, planning is now done with a scalpel instead of an ax.

Once the drivers leave the building, the systems continue to monitor and control the operation. GPS in the DIAD tells a central monitoring station the location of each driver is in near real time. Operators can see what work has been completed and what work is remaining for each driver. If a customer needs an on demand pickup or to meet a driver, planners can see which driver will be closest to the customer at the time the customer needs to be served.

Of course there are a tremendous amount of descriptive analytical tools available. The DIAD records events every second of the day along with GPS readings. If a package is delivered even one minute late, systems report on the failure and even pinpoint the event that caused the problem. Tools exist that analyze problems in plans and execution with appropriate metrics to report on efficiency.

The results from this suite of tools have been tremendous. Through the integration of processes, information technology, and analytics, UPS cut 30 million miles driven per year. This equates to 3 million gallons of fuel and 30,000 metric tons of CO2 not going into the atmosphere. In addition, due to the integration of systems, drivers make 8 billion fewer manual entries per year which improves visibility for our customers. All this happened while introducing new service offerings for our customers.

Up to this point, the majority of the tools have used descriptive and predictive analytics combined with integrated information technology. We are not done yet however. Moving to prescriptive analytics requires not only that optimizations be developed, but it also requires even more accurate data than before. We have been working on this for a while and are testing the crowning jewel on our suite of tools.

It takes all recorded customer demands, business rules, and constraints and optimizes the plan meeting all conditions. Rather than giving a driver a general plan for the day, the system prescribes the lowest cost route that fulfills all service commitments.

Data issues have to be addressed again, including the accuracy of off the shelf maps. If anyone has used a navigation system that didn't efficiently route between two points you know what I mean. For a UPS driver making 130 deliveries, small inaccuracies add up to a large issue. Using analytics, we compared our historical geographic data (gathered from the GPS unit in the DIAD) with map data to point out where inaccuracies exist in commercial maps. Tools are provided to allow the planner to customize maps for the optimizations, making our maps the most accurate in the world.

Testing so far has shown significant savings. The optimizations have shown seasoned drivers new ways to run their areas. Ways that even these professionals did not think about which still meet service commitments while reducing cost. We are excited about this next phase of our analytics journey and so were the people at Gartner.

I'm proud and honored that UPS won the Gartner competition and it's hard to tell the story here, without the visuals used at the competition. I learned a lot and the experience opened my eyes and solidified my thoughts on analytics.

There were 1,500 people at the Gartner event and the majority were busy getting data in order so that they could do descriptive analytics. Most had a goal of someday doing predictive analytics and the concept of optimization seemed like Star Wars to most. Their focus was data. At INFORMS, it seems we focus on optimizations and predictions, but worry less about the data issues that come along with that territory.

It sure seems to me that merging the two points of view could be a good thing.

 

Section Website Now Features Analytics Process Videos

Organizations want to take advantage of analytical tools and techniques to improve their decision making but don't always how or where to start. View these on-demand videos filmed at the 2011 INFORMS Conference on Business Analytics and Operations Research from top-notch analytics experts to improve your analytics maturity.

Click here to watch featured videos which include:

Christer Johnson, IBM
What Impact will Watson have on the Use of Analytics in Business? An Overview of Deep Q&A Technology
Christer Johnson, MBA, North American BAO Advanced Analytics Leader, IBM Global Services, IBM Corporation

Will OR/MS Professionals Help Put Analytics to Work?
Jeanne G. Harris, MS, Director of Research, Accenture Institute for High Performance, Co-Author, Competing on Analytics and Analytics at Work

How to Win with Analytics...vidi, vici
Nathaniel Lin, PhD, Founder, Analytics Executive Network, and Adjunct Professor, Georgia Tech College of Management

Data-Driven Decisions: The Role of Operations Research in Business Analytics
Radhika Kulkarni, PhD, Vice President, Advanced Analytics R&D, SAS Institute Inc.

Analytic Principles and the "Enabling Stack": The Why and How of Applied Analytics at Best Buy's Consumer Insights Unit
Scott Friesen, MBA, Sr. Director of Analytics for the Consumer Insights Unit, Best Buy

 

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