Smart Software VP of Research to Present at ISF 2018

Dr. Tom Willemain to lead ISF session on Time Series Dissaggregation

Belmont, Mass., May 14, 2018 – Smart Software, Inc., provider of industry-leading demand forecasting, planning, and inventory optimization solutions, today announced that Tom Willemain, vice president for research, will present at the International Symposium of Forecasting from June 17 – 20 in Boulder, CO.

Dr. Willemain, will present a tutorial on Time Series Dissaggregation and how the approaches he’ll outline can improve the quality of demand forecasts.  Imagine that you must provide daily forecast results but can only obtain historical demand at monthly or weekly levels.   Often times, granular demand data is not available.  How do you proceed?  Converting aggregate quarterly, monthly, or weekly data to daily data is example of the time series dissaggregation problem. Dr. Willemain will discuss current solutions to this problem and press an improved solution.

As the premier, international forecasting conference, the ISF provides the opportunity to interact with the world’s leading forecasting researchers and practitioners. The attendance is large enough so that the best in the field are attracted, yet small enough that you are able to meet and discuss one-on-one. The ISF offers a variety of networking opportunities, through keynote speaker presentations, academic sessions, workshops, meals, and social programs. In addition, representatives of leading publishing, software, and other related companies are on hand to discuss their most recent offerings.

About Dr. Thomas Willemain
Dr. Thomas Reed Willemain served as an Expert Statistical Consultant to the National Security Agency (NSA) at Ft. Meade, MD and as a member of the Adjunct Research Staff at an affiliated think-tank, the Institute for Defense Analyses Center for Computing Sciences (IDA/CCS). He is Professor Emeritus of Industrial and Systems Engineering at Rensselaer Polytechnic Institute, having previously held faculty positions at Harvard’s Kennedy School of Government and Massachusetts Institute of Technology. He is also co-founder and Senior Vice President/Research at Smart Software, Inc. He is a member of the Association of Former Intelligence Officers, the Military Operations Research Society, the American Statistical Association, and several other professional organizations. Willemain received the BSE degree (summa cum laude, Phi Beta Kappa) from Princeton University and the MS and PhD degrees from Massachusetts Institute of Technology. His other books include: Statistical Methods for Planners, Emergency Medical Systems Analysis (with R. C. Larson), and 80 articles in peer-reviewed journals on topics in statistics, operations research, health care and other topics. For more information, email: TomW@SmartCorp.com or visit www.TomWillemain.com.

About Smart Software, Inc.
Founded in 1981, Smart Software, Inc. is a leader in providing businesses with enterprise-wide demand forecasting, planning and inventory optimization solutions.  Smart Software’s demand forecasting and inventory optimization solutions have helped thousands of users worldwide, including customers at mid-market enterprises and Fortune 500 companies, such as Mitsubishi, Siemens, Disney, FedEx, MARS, and The Home Depot.  Smart Inventory Planning & Optimization gives demand planners the tools to handle sales seasonality, promotions, new and aging products, multi-dimensional hierarchies, and intermittently demanded service parts and capital goods items.  It also provides inventory managers with accurate estimates of the optimal inventory and safety stock required to meet future orders and achieve desired service levels.  Smart Software is headquartered in Belmont, Massachusetts and can be found at www.smartcorp.com

SmartForecasts is a registered trademark of Smart Software, Inc.  All other trademarks are the property of their respective owners.


For more information, please contact Smart Software, Inc., Four Hill Road, Belmont, MA 02478.
Phone: 1-800-SMART-99 (800-762-7899); FAX: 1-617-489-2748; E-mail: info@smartcorp.com

Forecasting and the Rising Tide of Big Data

The Smart Forecaster

 Pursuing best practices in demand planning,

forecasting and inventory optimization

“Trillions of records of millions of people…Finding the useful and right information, understanding its quality and producing reliable analyzed data in a timely and cost-effective manner are all critical issues.”

Smart Software Senior Vice President for Research Tom Willemain recently had the opportunity to talk with Dr. Mohsen Hamoudia, President of the International Institute of Forecasters (IIF), to discuss current issues with, and opportunities for, big data analytics. The IIF informs practitioners on trends and research developments in forecasting via print and online publications and the hosting of professional conferences.

Dr. Hamoudia begins, by way of introduction:

In all industries, data availability is exploding in volume, variety and velocity. Big data analytics is playing an important role in identifying the data that is most important to the business.

Let me take the example of the Information and Communication Technology (ICT) sector. We are seeing literally exponential growth in the amount of data available to telecoms, Over-the-top (OTT) independent content distributors, government, regulators and other organizations.

Around the world, we are witnessing petabytes of data: trillions of records of millions of people—all coming from multiple sources. Among these sources: internet connections, sales, customer contact centers, social media, mobile and land lines data. Finding the useful and right information, understanding its quality and producing reliable analyzed data in a timely and cost-effective manner are all critical issues. ICT companies are increasingly looking to find actionable insights in their data. How they can increase their customer base and loyalty programs? How can they improve the quality of service (QoS) and reduce customer turnover? With the right big data analytics platforms in place, they can be more competitive and efficient, improving operations, customer service and risk management. Forecasting and predicting customer trends and directions are key for telecoms.

Forecasting skills, including mathematics, statistics and econometrics, form one of the most important “blocks” of required skills in managing Big Data. Some forecasting activities naturally form part of the big data debate.

In retail industries, forecasting addresses daily demand across thousands of products. Financial forecasting, whether considering customer behavior or financial data series, generates massive on-line data sets. As pointed out by Robert Fildes, Distinguished Professor at Lancaster University, as yet the academic forecasting community is not thoroughly engaged—with only a few exceptions. Hal Varian of Google has looked at some of the work that David Hendry and Jennifer Castle, at Oxford University, have undertaken on searching large data sets for data congruent meaningful models. Stock and Watson have also developed their own approaches to large macro data sets. But despite the attempt, at last year’s symposium on forecasting in Seoul, to explore the theme of big data and its forecasting applications, there remain few convincing applications of using on-line data on real forecasting problems.

Q. One hears a great deal about “predictive analytics” these days, yet the phrase rarely is linked with forecasting. Do you agree that forecasting lies at the heart of predictive analytics? Have you an explanation for why the link has been broken? Have you ideas about how to re-inject forecasting into the conversation?

The results of forecasting (the “what”) are perhaps now perceived as less important than the “how”. Consequently, the trust that users give to traditional forecasting has declined. Who indeed is challenging the accuracy or relevance of forecasting by comparing, a posteriori, the reality vs. forecast—making a case for metholodiges’ effectiveness and therefor building credibility?

With the current perception of “predictive analytics”, there is probably more space in the public imagination allocated to the “how” side of things, and therefor a more credible story to tell to partners, investors or customers.

Q. It appears that there is almost no link between traditional forecasting and mobile technology (smart phones, tablet computers). Is this true, or are some companies migrating forecasting to mobile devices? Do you see a path forward in which traditional forecasting algorithms would routinely reside on mobile devices?

First of all, I am really delighted to invite your readers to have a look at our latest issue of Foresight. An excellent paper on the subject, “Forecasting In the Pocket: Mobile Devices Can Improve Collaboration”, explains that “the increasing popularity of PDAs, smartphones, tablet computers and other mobile devices opens up new opportunities for communication and collaboration on business forecasts.” The authors tell us “mobile forecasting (m-forecasting) applications may streamline approaches to collaboration between retailers and suppliers, thus contributing to the provision and exchange of product information, especially since forecasts are strongly tied to local context knowledge.”

For example, on the ICT & OTT side, a large number of predictive projects, such as those of Google+ and Facebook, are happening thanks to the inclusion of the “user location” data in the OTT IT systems. In my opinion, and what I see in some sectors like retail and logistics, is that traditional forecasting and mobile forecasting (m-forecasting) are complementary. This latter could be seen as a bottom-up forecasting approach that will or will not confirm the top-down forecasting results.

Q. Some people argue that big data will facilitate the replacement of forecasting with “sense and react” systems. Practically speaking, how would you explain “sense and react”, and are there application areas where you think it is or is not likely to take hold?

It seems to me that “sense and react” is fully oriented to the short-term perspective. Forecasting extends this by addressing needs for a variable horizon: short-term and medium-term.

As a side effect of ATAWAD (Anytime, Anywhere, Any Device), the decision-making criteria are, more than ever, “short term”. Big data is a “weak signals” sensing system, which enable the near-real-time detection of business opportunities that would go unnoticed with traditional IT systems. There are not really preferred or non-priority applications for this, the question is more on the “when” side.

Big data is relevant when looking below the surface in difficult economic times, but I am less sure whether it is worth the effort in “normal” economic period. To conclude on this point: I will be happy to see an example on how accurate are forecasts which are based on “sense and react” versus forecast based on traditional models.

Q. I’m asking some big questions. To what extent do you see the IIF community shaping these discussions and outcomes? How can readers join in the dialogue?

We are expecting an increasing availability, and increasing usage, of huge amount of data in many industries—such as energy, transportation, health care, finance, telecommunications and tourism.

Many of the IIF’s members are engaged in different aspects of the big data “movement.” The IIF is doing some work in the forecasting activities that naturally form part of the big data debate. More generally, the IIF is actively participating in, and providing a forum for, the discussion of forecasting in the wider world.

The theme of our last International Symposium on Forecasting (ISF) held in Seoul was “Forecasting with Big Data” and a few presentations were related to health care and telecommunications. A relevant workshop has just been run by the European Central Bank (ECB). If these models are capitalized on, they have the potential to impact the economic policy of Europe quite quickly.

Readers can join in the dialogue by contributing papers to the IIF’s publications (The International Journal of Forecasting, Foresight and The Oracle). Foresight, for one, is an invaluable voice in bringing academics and practitioners together in an ongoing discussion.

Readers also can present papers at the annual conference (the aforementioned ISF). They also can suggest and organize specific workshops for specific applications of big data, like the one that was just organized by the ECB in Frankfurt. Another opportunity is to invite IIF’s members to attend any meeting related to forecasting with big data. All these opportunities form good platforms for networking and working together.

Mohsen Hamoudia, PhD, is the President of the International Institute of Forecasters. He also serves as Head of Strategy for Large Projects (Paris) for Orange Business Services (the former France Telecom).

Thomas Willemain, PhD, co-founded Smart Software and currently serves as Senior Vice President for Research. Dr. Willemain also serves as Professor Emeritus of Industrial and Systems Engineering at Rensselear Polytechnic Institute, and as a member of the research staff at the Center for Computing Sciences, Institute for Defense Analyses.

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      Recommended Resource: The IIF

      The Smart Forecaster

      Pursuing best practices in demand planning,

      forecasting and inventory optimization

      A go-to source for info on cutting-edge forecasting research, the International Institute of Forecasters (IIF) publishes journals and hosts conferences that we have relied on for decades. In this introduction, IIF Business Manager Pam Stroud gives an overview of the organization’s offerings. (Smart Software Senior Vice President for Research Tom Willemain serves on the Editorial Board of the IIF’s practitioner-oriented publication, Foresight.)

      When founded in 1981, the IIF set as its goal: “Bridge the gap between theory and practice, with practice helping to set the research agenda and research providing useful results”. The IIF keeps its members abreast of the latest trends and research in forecasting through its publications, events and website. Its members are drawn from corporations and institutes of higher learning in more than one hundred countries, and form a vibrant community for networking and professional development.

      The IIF’s practitioner journal, Foresight, is dedicated to improving the practice of business forecasting, enhancing the professional development of business forecasters, and bringing forecasting know-how to those entering the profession. Because forecasting knowledge and wisdom are not concentrated in one segment of forecasters, we publish valuable ideas from across the discipline—from forecasting teachers and scholars, forecasting analysts and managers, and forecasting consultants and vendors. And we strive to ensure that these ideas are presented clearly, are supported by evidence and are free of bias.

      In addition to our publications, the IIF sponsors an annual conference, the International Symposium on Forecasting (ISF). The ISF is an opportunity for researchers and practitioners to come together to share experiences and cutting edge research, and to network among their peers. The Foresight Practitioner conference extends this opportunity to practitioners, delivering practical professional development for business forecasters.

      Another example of ‘bridging the gap,’ between research and practice, is the annual research grant, offered in partnership with SAS, which supports research on how to improve forecasting methods and business forecasting practice.

      IIF Membership benefits include:

      The International Journal of Forecasting – The IJF is the leading scholarly journal in the field of forecasting. With an outstanding editorial board of 44 internationally known forecasting experts, it is a highly readable, widely used and often-cited research journal.

      Foresight: The International Journal of Applied Forecasting – Foresight publishes concise, readable and timely articles on forecasting processes, methods and solutions. It is the essential read for business forecasters and an invaluable aid for forecasting educators and students.

      The International Symposium on Forecasting – Members receive discounted registration to the premier international forecasting conference. This annual IIF event attracts the world’s leading researchers, practitioners, and students. Each symposium offers more than 250 research presentations in a setting which emphasizes social interaction, and networking opportunities.

      The Foresight Practitioner Conference – Members receive discounted admission to this professional development event for business forecasters, where they learn from practitioners who have earned their expertise in the field at top companies, and from forecasting researchers sharing the business implications of their work.

      Recent topics from The International Journal of Forecasting:
      • Economic Time Series: Modeling and Seasonality
      • On the use of cross-sectional measures of forecast uncertainty
      • Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts
      Recent topics from Foresight: The International Journal of Applied Forecasting
      • How Good Is a “Good” Forecast?: Forecast Errors and Their Avoidability
      • Forecast Methods Tutorial: ARIMA: The Models of Box and Jenkins
      • Improve Forecasting of Consumer Purchases Using Google Trends

      “Since 1981, the IIF has been central to my career. Why? Because it’s a diverse and clever group of people focused on pragmatic, evidence-based research. The annual symposium is a great place to exchange ideas about forecasting.” – J. Scott Armstrong, Professor of Marketing, The Wharton School

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