Since the start of the recovery, the U.S. economy continues to show modest resiliency in light of uneventful shocks. The market has come to accept that the level of economic activities will keep pace with relatively robust consumer confidence and spending as the primary engine of growth. Unexpected August lackluster employment figures, followed by back to trend new jobs, has provided impetus to the debate regarding the timing of the Fed’s interest rate hikes in 2016 and 2017.
According to the fi ndings of the World Economic Survey (WES) conducted in the third quarter of 2016, about 1,100 executives from 115 countries have assessed worldwide capital expenditures—the engine to future economic growth and jobs—to be substantially below satisfactory levels and also below the levels of investment activity that the world economy experienced in the third quarter of 2015. Looking forward, business experts are pessimistic over the path of capital expenditures in the next two quarters.
Time series forecasting has evolved in a big way since 1822, when Joseph Fourier fi rst conceived of the mathematical analysis of historic time series data. Today, more complex time series models and forecasting tools continue to fuel the pursuit of improving forecast accuracy. Despite all the advancements in time series models, forecast accuracy remains a challenge.
Forecasting and demand planning are the backbone of any organization, and are key to operational efficiency and vitality. Accurate forecasts lead to lower inventory levels, fewer lost sales, and higher profitability. Demand for technology products is impacted far more heavily by economic swings than by any other specific sector of economy.
Jawad Hussein, Thom J. Hodgson, Russell E. King, Steven D. Jackson, and Kristin A. Thoney-Barletta
It is a mystery to me why anyone would manually cleanse the actual demand history given all the advancements in data collection, storage, processing, and predicative analytics. In my experience, whenever a company separated historical baseline volume from the promoted volume, and then added them back together using judgment (also known as layering), 1 + 1 tended to equal 5, instead of 2.
More than 20 years ago, during my tenure as a consultant with Accenture, I worked on an eye-opening engagement with Limited Brands, a private label apparel retailer. The company engaged us to improve its forecasting capabilities. An executive there believed that its internally developed legacy forecasting computer systems were no longer responsive to changing demand patterns. He wanted us to research what changes needed to be made to the forecasting algorithms it used.
Having your company’s money invested in the right inventory is critical. Modern supply chains are much more complex, product life cycles are shrinking, and “Risk Management” is the new buzzword. There are too many opportunities for things to go wrong. No one can afford to have money tied up in the wrong product mix or in excess inventory; it’s the kiss of death and everyone knows that, right?
S&OP has served business leaders over the past 20 years to make timely decisions about balancing sales (demand) with supply (manufacturing capacity and inventory) with the focus primarily on plan, source, make, and deliver a product or service to consumers. In the next 10 years, how consumers shop and receive goods will transform endto- end supply planning, the decisions business leaders will need to make, and how those decisions are made.
[ Q ] What are the pros and cons of forecasting at an aggregate level (total U.S.) versus DC level? Which is more common and does forecasting at a DC level require additional headcount? [ A ] At which level we should forecast depends on the objective
May’s job growth of 38 thousand compared with the monthly average of 177.5 thousand from January to April has left many observers wondering whether job growth has peaked. Although May’s figure was lower than expected, it should not be surprising, given the 2016 first quarter new job growth was the weakest in three years. Despite dismal new jobs numbers, the unemployment rate dropped to 4.7 percent in part due to a combination of a lower labor participation rate and an increase in involuntary part-time employment. The Conference Board Employment Trend Index (ETI), which considers eight labor-market indicators, revised the downward rate from 128.53 in April to 126.81 in May.
The outlook for global economic growth in 2016 has weakened further in the recent months. Worldwide output is estimated to continue to grow modestly by an average annual rate of 2.5% in 2016 and is now forecast to slightly accelerate to 3.4% in 2017 and 3.3% in 2018. Monthly predictive analytics from around the globe show a slowdown in the growth rates of emerging markets, and a loss of momentum in the growth of industrial countries.
What will be the FOMC rate decision? Every six weeks the financial markets consider this critical question. The FOMC sets the stance of the U.S. monetary policy, and provides a target for the federal funds rate. This article presents an ordered probit approach that estimates the sixmonth- ahead probability of three distinct scenarios of the FOMC decision: raise the fed funds target rate, reduce the rate, or keep the rate unchanged.
The digital revolution has affected all aspects of business, including supply chains. The Internet of Things (IoT), with its network of devices embedded with sensors is now connecting the consumer to the factory. Technologies such as RFID, GPS, event stream processing (ESP), and analytics are combining to help companies to transform their existing supply chain networks into more flexible, open, agile, and collaborative digital-driven models. Digital supply chains enable business process automation, organizational flexibility, and digital management of corporate assets.
My last column in the Journal of Business Forecasting (Spring 2016), titled “Execution Needs the S&OP Plans,” discussed the need to synchronize supply-demand execution operational plans with the tactically based Sales & Operations Planning (S&OP) process plans. The main purpose of this is to help align daily operations—such as those that take place on the plant floors and within the distribution centers—with the plans that have been developed to meet the operational performance goals that drove the S&OP plans. This helps operations managers to act in accordance with financial and various operational objectives.
Nearly every S&OP success story speaks of engagement by the executive team as a core element of the implementation. It is universally accepted as one of the most important precursors of positive results. “Lead from the top” is a common S&OP axiom, yet the expression “executive engagement” is often nothing more than a vague utterance—offered like a solution unto itself. It assumes the listener already knows the meaning of the expression. And in my experience, the one guaranteed way to make something utterly useless is to leave it painfully vague.