The Journal of Business Forecasting Winter 2017/2018 Issue is available now for download. Below is a letter from the Editor, Professor Chaman L. Jain, revealing why this issue comes at an especially important time in the evolution of business forecasting, demand planning and analytics.

Dear Professional,

We are living in a world where market dynamics are constantly changing. Markets are exploding with new products, channels of distribution are proliferating, competition is getting more intense, and consumers are less loyal and more demanding. To survive and grow in these markets, companies must adapt, and that is exactly what they are doing. In spite of unprecedented challenges, 2/3 of companies report operating margins and revenue growth of 15% or more. The question is, what tools and methodologies are behind this remarkable growth, and how can they be translated into greater efficiency and profitability?

The answer lies in the fact that innovations like Big Data, Predictive and Cognitive Analytics, Machine Learning, Quick Response Forecasting, and Social Sensing have evolved from the conceptual to the real. Products are now “’self-aware” and Facebook data is being successfully leveraged to predict demand. The advancements we have been talking about for years are being successfully leveraged as drivers of growth. We as demand planners and S&OP professionals are no longer asking ourselves what tools of the future will be, but how we implement those tools today for superior demand planning and forecasting.

In this climate of exciting change, there remain some constants: people, process, and technology. People remain key, not least because automation in our field will, ironically, require more people to enter the field to fill a variety of new job functions. But that is not to say these elements are not evolving; software, not forecasters, will prepare forecasts based on pre-determined criteria, and information will include unstructured data gathered from social media.

Image of latest issue of The Journal of Business Forecasting and Planning

Journal of Business Forecasting and Planning

Given the advent of automated forecasting software that models, predicts, advises and learns, demand planners will not be directly involved in preparing forecasts. Soon, the responsibility of demand planners will be to build consensus around forecasts, and then communicate that to upper management for action. They must, however, know what kind of forecasts are needed and how to evaluate them. Data scientists, working under demand planners, will use their skill and technology to gather more insight from data, such as what consumers really want and why, and how they feel about our products. This insight will feed decisions that optimize revenue and profit.

Because of the increasing share of new product sales and the expanding role of e-commerce businesses, new processes must be added to manage demand because they require different approaches and strategies. Further, market dynamics are rapidly changing, and so must our plans. To detect market changes quickly and act on them, planners need to shorten their planning cycles. Strategic planners no longer have the luxury to meet just once a year – they now have to meet more frequently. Furthermore, disruptions in both supply and demand are occurring much more quickly and are costly, requiring yet more and better processes to manage them.

Tools such as data mining, artificial intelligence, predictive analytics, and Hadoop will improve market intelligence, which will help in making better decisions. Virtual assistants such as Siri, Cortana, Alexa, and Watson will help in running different scenarios and producing outputs at the click of a button to arrive at an optimal solution. Last year, H&R Block deployed Watson to assist its staff in filing tax returns. The key objectives were to reduce tax liabilities of clients and file the return correctly so that they get the refund as soon as possible. This will help the company to improve its client retention rate. To train Watson, IBM fed 74,000 pages of federal tax codes and thousands of tax-related questions pulled from the H&R Block’s 60 years of tax return data. This technology is remarkable, and is directly transferable to  both demand planning and forecasting.

Since market changes are coming thick and fast, we need to detect market signals early enough to act. Some authors in this issue are already suggesting viable and practical ways to make this happen. To speed up the process of forecasting and, consequently, decision making, Larry Lapide proposes Quick Response Forecasting, and Charles W. Chase proposes Edge Analytics. The technology required to implement these concepts is almost here.

As with all changes, there is opportunity and risk, and hope and trepidation. Yes, technology will eliminate some jobs, but it will create others. An increasingly unavoidable truth is that demand planners and forecasters will transform into data scientists, and that presents an exciting new world of opportunity. We are at a pivotal moment, let’s embrace it.

Happy Forecasting!

Chaman L. Jain, Editor

 

Featured Articles

1. Event-Driven Planning: An Inflection Point for Operations Planning
By Gregory L. Schlegel

2. Building the Link Between Data and Supply Chain Performance in the Digital Age
By Alan L. Milliken

3. Preparing for Demand Planning in 2025
By Eric Wilson, CPF

4. Digital Transformation: Three Skills Demand Managers Must Have
By Peter Chisambara

5. Quick Response Forecasting: A Blueprint for Faster and More Efficient Planning
By Larry Lapide with Eric Wilson, CPF

6. Real-Time Demand Execution Anticipating Demand at the Edge
By Charles W. Chase, Jr., CPF

7. The Move to Defensive Business Forecasting
By Michael Gilliland

8. Supply Chain Digitalization — Delivering Sustainable Cross-Functional Change
By Neil James

9. I (am) Robot—Future Proofing Your Demand Planning Career
By Andrew Schneider, ACPF

10. CAPEX Predictive Analytics Confirm Renaissance in Animal Spirits
By Evangelos Otto Simos

11. U.S. Economy Defies Conventional Wisdom, Enjoys Non-Inflationary Full Employment Growth
By Jamal Nahavandi

This special issue of the Journal of Business Forecasting is available free for members via the IBF members area. Not a member? Then get a preview of this issue of the journal or become a member today and receive all JBF issues free and a host of other benefits. 

 

 

 

Facebook Comments
Shares