Machine Learning Archives

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Recreating the Environment in which Historical Demand Occurred

8 January 2019

At last year’s Gartner Supply Chain Executive Conference analyst Tom Enright summarized the essence of successful demand forecasting with the following statement: “Demand forecast accuracy depends on your ability to recreate the environment in which historical demand occurred.” While seemingly[...]

8 January 2019

Demand Planning is the top Machine Learning App for Supply Chain Planning

Gartner recently polled both users and vendors on which types of supply chain planning (SCP) applications were employing machine learning technology. In three different analysis, demand planning and demand forecasting came out on top of the list. With years of experience now in[...]

8 January 2019

Advanced Analytics versus Artificial Intelligence

For firms with Advanced Analytics or Artificial Intelligence (AI) in their future, Gartner has just published a useful report with three findings that clarify the difference between the two technologies and offers insight on employing them for augmenting versus automating supply chain decision making. Advanced Analytics is broader[...]

8 January 2019

How Not to use Machine Learning for Demand Forecasting

Eight years ago ToolsGroup was one of the first supply chain planning software vendors to employ machine learning to improve demand forecasting. As the tag line to a popular commercial goes, by now “we know a thing or two because[...]

8 January 2019

Trade Promotion Forecasting: the Present and the Near Future

Trade promotion forecasting is difficult: getting it right involves factoring in many variables. Marketing people, who are often responsible for it, may excel at creating and running promotions. Forecasting demand data, not so much. This can leave supply chain professionals[...]

8 January 2019

Will you be a Supply Chain Disruptor or the Disrupted?

You should be interested in applying disruptive technologies in your supply chain not only at a physical level, like in transportation and logistics, but also at a more virtual level in your supply chain planning. And you should be thinking[...]

8 January 2019

Is Your Supply Chain Planning Ready for the “Experience Economy”?

Gartner says we are entering what they call the ‘Experience Economy”, where personalization, speed, agility and the ability to predict consumer trends before they happen will separate the winners from losers (Aspire, Challenge and Transform in a Disruptive World, 27[...]

8 January 2019

Traditional Statistics versus Machine Learning. What’s the Difference?

Since machine learning is a hot topic, we thought it useful to clarify the difference between machine learning and traditional statistics as applied to supply chain planning (SCP). Both technologies help you better understand data and are classified as analytics,[...]

8 January 2019

The Power of Downstream Data for Sensing Demand

Lora Cecere, CEO of Supply Chain Insights, has released a useful new report entitled “The Power of Downstream Data” which describes previously undocumented benefits for collecting and analyzing downstream supply chain data. Downstream data is the demand data that powers a market-driven, “outside-in”[...]

8 January 2019

A Path Towards IoT Enabled Service Parts Planning

Editor's Note: This week we have a guest post from Bob Ferrari, Managing Director of the Ferrari Consulting and Research Group. This blog first appeared in Supply Chain Matters. It is the second in a series on how companies can build foundational service[...]

8 January 2019

Seven Recent Trends in Retail Demand Forecasting and Replenishment

Since most retailers are facing a shrinking operating “margin for error”, many are looking for more accurate demand forecasting and intelligent stock replenishment. Gartner analyst Mike Griswold explains how in his recent report entitled Market Guide for Retail Forecasting and Replenishment Solutions. 1/ Multichannel retailing is[...]

8 January 2019

Retailers, Is Machine Learning a Little Black Dress or an Accessory?

At first glance, a discussion about clothing and technology seems a bit incongruous, even for a retail focused blog. What could a dress possibly have to do with running your business? But they are more closely related than you may[...]

Sales & Operations Planning Software S&OP provides the critical link between inventory, customer service and business performance by enabling cross-functional planning and bridging the gap between strategic planning and operational execution.

Promotions Planning Software Promotions Planning gives cross-functional teams the visibility to synchronize demand shaping campaigns and promotions with supply chain operations ensuring that inventory is in the right place to meet demand on a daily basis, right down to the store level.

Production Planning Software Production Planning provides unparalleled visibility, insight and control of the entire production lifecycle to improve efficiency and quality control, and service demand.

Inventory Optimization Software Inventory Optimization factors in multiple planning variables and probabilities to generate an optimal multi-echelon inventory plan for every item in a portfolio to achieve target service levels.

Allocation and Replenishment Software Allocation and Replenishment automatically calculates optimal inventory levels for both existing and new items to create a phased, time-series plan that achieves target service levels even in the face of demand variability and distribution complexity.

Demand Planning & Sensing Software Demand Planning & Sensing automates the creation of demand plans using machine learning and by incorporating detailed short-term demand signals and demand collaboration, it reduces forecast error and optimally deploys inventory.

Planning as a Service Planning-as-a-Service provides business-focused, technology enabled resources to help customers quickly achieve value from their SO99+ implementation. It accelerates time-to-value over a traditional implement and learn approach.