Probabilistic Planning and Forecasting Demystified

ToolsGroup

I have been blogging and advocating for the past 15 years on probabilistic approaches to planning and forecasting, and am happy to see in the last few years it has finally started gaining traction and attention. Time is horizontal, forecast quantity vertical.

Time Series Forecasting Basics

Arkieva

In this blog we briefly cover some key insights for successful time series forecasting: (a) Profiling the Shape of the Curve is the first stage, and the first step is assessing if the time series is stationary. (b) Time Series Forecasting Basics was first posted on April 6, 2021 at 9:03 am. ©2017

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Causal Forecasting Brings Precision to your Forecasting

Logility

Causal f orecasting shines a light on , and isolates, actual demand signals from market “chatter,” thus improving forecast quality. What Exactly Is Causal Forecasting? . First, what it’s not is a replacement for demand forecasting.

Get Started Using Machine Learning for New Product Forecasting

ToolsGroup

Adding to this already uphill battle, we don’t have trustworthy new product forecasting methods because forecasting new products with no sales data is very hit-and-miss. Machine learning (ML) provides an effective weapon for your new product forecasting arsenal.

5 Perceptions on Demand Forecasting and How it's Changing

Speaker: Brian Dooley, Director SC Navigator, AIMMS

It’s no secret that demand is getting more difficult to predict. Is your demand forecasting process evolving with the times? How does your process stack up against others? Are you satisfied with your level of forecast accuracy? This webinar shares research findings from a recent survey among supply chain planning professionals to help you answer these questions.

Demand Planning: Differentiated Forecast Strategy

Arkieva

Some time ago, I had been trying to help a business improve its statistical forecasting. We tried different parameters and different forecasting algorithms but the statistical forecast for about half of the products could not be improved no matter what we tried.

Melitta: Collaborating for an Improved Forecasting Process

ToolsGroup

Melitta Sales Europe (MSE) embarked on an initiative to revamp existing planning and forecasting processes to increase efficiency and sustainability. MSE’s prioritization of its close internal collaboration strengthens the precision of its forecasts, ensuring a more robust S&OP process.

Probabilistic Forecasting - a Primer

ToolsGroup

An experienced gambler might hedge their bet on multiple outcomes, rather than just the most likely "single number forecast". At ToolsGroup we have been big advocates of probabilistic forecasting (sometimes also known as stochastic forecasting). Understanding and employing this relatively simple principle can take your forecasting and supply chain planning from ‘good to great’. In this case, forecasting 100 units is a pretty safe bet.

[PODCAST] Inventory Forecasting Lessons for Improved Supply Chain Network Optimization

GlobalTranz

Listen to “Inventory Forecasting Lessons for Improved Supply Chain Network Optimization” on Spreaker. The post [PODCAST] Inventory Forecasting Lessons for Improved Supply Chain Network Optimization appeared first on Transportation Management Company | Cerasis.

A Primer on Probabilistic Forecasting

The Smart Software

If you keep up with the news about supply chain analytics, you are more frequently encountering the phrase “probabilistic forecasting.” Probabilistic forecasts have the ability to simulate future values that aren’t anchored to the past.

The Best Sales Forecasting Models for Weathering Your Goals

Every sales forecasting model has a different strength and predictability method. It’s recommended to test out which one is best for your team. This way, you’ll be able to further enhance – and optimize – your newly-developed pipeline. Your future sales forecast? Sunny skies (and success) are just ahead!

Turn a Good Demand Forecast into the Optimum Inventory Plan

ToolsGroup

How Do You Turn a Good Demand Forecast into the Optimum Inventory Plan? Your customers don’t care if you have a great demand forecast. How do you turn a good forecast into a great inventory plan? About 15 years ago, many forecasting solutions turned to multi-echelon optimization.

Weather-Influenced Demand Forecasting in 2020

Logistics Viewpoints

It is 2020; we now have reasonably accurate short-term weather forecasts. The post Weather-Influenced Demand Forecasting in 2020 appeared first on Logistics Viewpoints. Demand Signal Repositories Guest Commentary Retail demand forecasting weather patterns

Machine Learning and AI: Profiling Demand History – A Wiser Forecasting

Arkieva

In the simple version of supply chain management (SCM) the goal for demand forecasting in the tactical decision tier is prediction accuracy. Machine Learning and AI: Profiling Demand History – A Wiser Forecasting was first posted on August 5, 2020 at 8:11 am. ©2017

“Optimized” Inventory Forecasting a Co-Product of Optimized Central Planning

Arkieva

In a recent blog on Inventory Forecasting the core challenges and business importance of estimating inventory are outlined. Optimized” Inventory Forecasting a Co-Product of Optimized Central Planning was first posted on February 18, 2020 at 8:08 am. ©2017

Machine Learning: A Quantum Leap in Forecast Accuracy for the Modern Supply Chain

Whether you realize it or not, Machine Learning is having a profound impact on your everyday life

2021 Logistics Outlook: Truckload Freight Market Forecast

GlobalTranz

The volatility of 2020 and the uncertainties looming into 2021 make it difficult to forecast planning and budgets based on historical data. Those unexpected surges meant forecasts were worth as much as the paper they were printed on.

Improve Forecast Quality and Reliability with Value-add Forecasting (Part 1)

Logility

The ability to effectively forecast demand is essential for supply chain management decisions. In fact, demand forecasts are used throughout the supply chain including supply chain design, purchasing, operations, inventory, and sales and marketing. value-add forecasting today.

Insight from Applied Statisticians for Forecasting: Is It Worth the Effort and the Mirage of Random Variation

Arkieva

Insight from Applied Statisticians for Forecasting: Is It Worth the Effort and the Mirage of Random Variation was first posted on October 14, 2020 at 8:09 am. ©2017

Dreaming about accurate forecasts?

DELMIA Quintiq

There is a saying among forecast users: “ If you forecast, you may be wrong; but you will always be wrong if you do not forecast.”. But how much faith are companies willing to place in inaccurate forecasts? Many companies use demand forecasts that are based solely on historical data. However, these forecasts are less effective in a volatile global market facing sociopolitical challenges, such as trade wars and Brexit.

Key Questions for a Successful Distribution Network

Speaker: Irina Rosca, Director of Supply Chain Operations, Helix

As we plan for the world of eCommerce and the customer expectation of quick, free shipping, our ability to forecast is turned on its head. How many distribution centers do we even need, and is that number feasible?

Calculating Forecast Accuracy & Forecast Error

EazyStock

The Importance of Demand Forecasting Accuracy. In supply chain management it’s important to be able to measure the accuracy of your demand forecasts. Inaccurate demand forecasting can lead to the accumulation of excess stock or the reverse: issues with product availability. Ensuring demand forecasting accuracy should be a key responsibility for any conscientious inventory planner. What is Forecast Error? Forecast Accuracy/Forecast Error Calculations.

Forecasting E-Commerce Demand: Mastering Variability in Your Supply Chain Network

CHAINalytics

But the tools and processes needed to forecast e-commerce demand reliably can increase your accuracy no matter how you do business. The rise of e-commerce changes everything.

Logistics Technology Market Forecasting Under Uncertainty

Logistics Viewpoints

The current coronavirus outbreak is an example of an economic shock that elevates uncertainty and complicates forecasting. The post Logistics Technology Market Forecasting Under Uncertainty appeared first on Logistics Viewpoints. Statistics business forecasting coronavirus

Four Steps to Better Demand Forecasting

Logility

Forecasting is an “inexact science” that relies on the data available to you, the math you use, and how you implement the forecast. And your forecasting success is fundamentally impacted by your understanding of that data, its strengths and limits.

Automated Order Processing and Proactive Inventory Management

Speaker: Irina Rosca, Director of Supply Chain Operations, Helix

Organizations need to focus on demand driven supply planning, utilizing real time information on customer orders from all marketplaces (e-commence, Amazon - or other online retailers, and point of sale data from brick and mortar). Focusing on this information once per month during the S&OP meeting is too late for all business units to align. Companies should have seamless integration between order entry, inventory management, forecasting and supply planning models and purchase order status to sense risk, pull levers to mitigate potential risk, and communicate within and outside the organization. This is especially important for new product releases, in store programs or promotions (sales, end caps, PDQ. etc) or online promotions (company run or 3rd party). Depending on total supply chain lead time, not having real time visibility and analysis of this information can significantly affect sales and the bottom line.

How Does Demand Sensing Differ from Forecasting for Demand Planning?

Logility

For today’s supply chain planner, the art and especially the science of forecasting demand have evolved. Traditionally, forecasting models were based on time series techniques that create a forecast based on prior sales history. The limitations of time-series forecasting.

Probabilistic Forecasting and Confidence Intervals

Arkieva

Probabilistic Forecasting and Confidence Intervals was first posted on September 27, 2019 at 11:18 am. ©2017 Historically, most of the key planning and computational activities (models, time series, machine learning, and other analytics) that support extended supply chain management (SCM) are “deterministic models”. ©2017 " Supply Chain Link Blog - Arkieva " Use of this feed is for personal non-commercial use only.

What’s Your Forecast Accuracy Target for 2019?

ToolsGroup

Editor’s Note: Two years ago we posted a blog about how to set an annual forecast accuracy target and it was one of our most popular topics. Many companies have already started their 2019 planning and budgeting cycles, so if you are in charge of demand forecasting for your company, it’s about time to thinking about your organization's 2019 goals. It seems as if everyone is looking to improve their forecasting performance. Forecasting Demand and Analytics

Untangling the Complexities of Demand Forecasting

ModusLink Corporation

Whether facing a major product launch or compiling standard monthly forecasts, the accuracy of demand forecasts is crucial. The post Untangling the Complexities of Demand Forecasting appeared first on ModusLink Global Solutions. Manufacturing to Market logistics manufacturing supply chain forecasting Demand Planning Demand ForcastNo one understands this as intimately as Apple, who is fresh off of its much-anticipated iPhone X, 8 and 8 Plus product announcements.

Overcoming the Accuracy vs Agility Trade-Off in Demand Planning & Forecasting

Agility and accuracy don’t necessarily need to be at logger heads. In-fact, anticipatory agility enabled by AI and Machine Learning can move the accuracy frontier forward in terms of validity and consistency driving significant business value.

What’s Your Forecast Accuracy Target for 2017?

ToolsGroup

In 2016, it seemed as if everyone in supply chain was looking to improve their forecasting performance. Unsurprisingly, the highest percentage of respondents in a recent Gartner/Supply Chain Digest survey selected forecast accuracy and demand variability as the top barriers preventing them from reaching their broader supply chain goals. How much can you realistically expect to improve your forecast accuracy each year? Forecasting Demand and Analytics

Multiple View Forecasting

Operations and Supply Chain Management

Multiple View Forecasting. Using a Multiple View Approach to forecasting has become an imperative. This market perspective is used as one input to the company’s volumetric forecast. A technique called “Focus Forecasting” (fitted forecast) is typically used.

How to Measure Forecast Errors in Intermittent Demand Forecasting

Arkieva

Stop using traditional forecast accuracy metrics to measure forecast for sporadic demand patterns. How to Measure Forecast Errors in Intermittent Demand Forecasting was first posted on March 19, 2019 at 12:19 pm. ©2017 Use this method instead. ©2017 " Supply Chain Link Blog - Arkieva " Use of this feed is for personal non-commercial use only. If you are not reading this article in your feed reader, then the site is guilty of copyright infringement.

Promotion Forecasting

Cognira

Brochure: Promotion Forecasting. With decades of retail and data science experience, intelligent retail forecasting is Cognira’s core expertise. Our highly accurate, quality omnichannel forecasts represent true customer demand – not just sales history.

The Top Five Benefits of Using Machine Learning for Demand Forecasting

Logility

Machine Learning for demand forecasting has matured to a level of accuracy, transparency and replicability that translates into transformative results, including in these five areas: Accuracy, transparency, thoroughness of analytical options and results.