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.

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).

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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

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

Cerasis

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.

How is Demand Forecasting changing? How do you compare to your peers?

AIMMS conducted research to assess how supply chain teams perceive the accuracy of their forecast and discover the tools and techniques they are using to upgrade the forecasting process. In this report, you will find helpful benchmarks and insights offered by your peers on the latest demand forecasting techniques, forecast granularity and periodicity, and expectations for the future.

Machine Learning: Optimization and Community Intelligence – A Wiser Forecasting

Arkieva

Machine Learning: Optimization and Community Intelligence – A Wiser Forecasting was first posted on August 12, 2020 at 7:41 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? This ultimately improves the quality of the forecasts.

How do supply chain professionals rate their demand forecast’s accuracy?

AIMMS

Part I in our series on assessing your Demand Forecasting process. Is your demand forecasting process evolving with the times? Are you satisfied with your level of forecast accuracy? How do professionals rate their demand forecast’s accuracy? .

Demand Planning & Forecasting During COVID-19 [Webinar]

CHAINalytics

Last month, Chainalytics’ Neelesh Asati moderated a panel discussion on demand planning and forecasting during COVID-19 hosted by Logistics Insider.

Probabilistic Forecasting: Right Fit for Your Business?

Supply Chain Shaman

A Closer Look at Forecasting. Traditionally companies forecast using history (shipments or orders) and applying linear regression to understand the patterns of historical demand using these to estimate future requirements in a time-series format. Understanding Probabilistic Forecasting.

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.

Inventory Forecasting Overview Part 1

Valogix

This blog post provides some basic information about viable inventory forecasting techniques. Forecasting is one of the key steps in inventory planning but not the only one. inventory forecasting

“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

Probabilistic Forecasting and Confidence Intervals

Arkieva

Probabilistic Forecasting and Confidence Intervals was first posted on September 27, 2019 at 11:18 am. ©2017

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.

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!

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.

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.

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. How much can you realistically expect to improve your forecast accuracy each year? Forecasting Demand and Analytics

Business Forecasting Lessons From Hurricanes

Arkieva

With each storm, there comes a bevy of forecasts put out by different computer models. These forecasts begin about 10 days out and change as the storm gets closer and closer. This blog tries to extract some learnings from this process of forecasting.

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

Common Forecasting Myths Debunked – Part 1 – One Forecast is Enough

Logility

This is the first of a series of four posts that will explore common forecasting myths. In supply chain the impact of a single error can quickly derail an entire forecast. Many companies believe that once a forecast is created success will follow throughout the product life cycle.

How Not to use Machine Learning for Demand Forecasting

ToolsGroup

Eight years ago ToolsGroup was one of the first supply chain planning software vendors to employ machine learning to improve demand forecasting. Statistical forecasting approaches have others. Forecasting Demand and Analytics Machine Learning

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.

Differences Between Demand Forecasting Yesterday vs. Tomorrow

Blue Ridge

There are some distinct differences between demand forecasting, which operates on historical sales data alone, and predictive analytics, where decisions are science-driven. The post Differences Between Demand Forecasting Yesterday vs. Tomorrow appeared first on Blue Ridge.

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?

Why probabilistic forecasting is better for inventory optimization

ToolsGroup

Last month we published a primer on probabilistic forecasting , an alternative to deterministic or ‘single number’ forecasting. Spreadsheets and legacy suites like SAP APO produce top-down aggregated forecasts using a deterministic approach.

Forecasting: Let’s Start by Asking the Right Questions

Supply Chain Shaman

This is especially true for forecasting. I find that too many companies try to buy forecasting software through a Request For Proposal (RFP). How forecastable is your product set? What is your Forecast Value Add (FVA) by product segment? Ten calls.

Why SAP APO Can’t Forecast Demand in Complex Environments

ToolsGroup

SAP APO is not equipped to address today’s supply chain challenges and that makes demand forecasting and supply chain planning more cumbersome and off target with APO or similar tools. APO’s“Top-Down” Demand Forecasting. Finally, ‘noise’ is not forecastable.

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

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.

Using Weather and Climate Data to Improve Demand Forecasting

ToolsGroup

Editor's Note: This is the second in a three part series on advanced demand analytics to improve demand forecasting. Demand forecasting software can usually factor in climate and seasonality , like more ice cream being sold during summer months or in warmer climates.

Building a Business Case for Improved Demand Forecasting

ToolsGroup

I’ve always maintained that improving demand forecast accuracy, as helpful as it can be, shouldn’t be the end goal itself, but simply a means to the end. Gartner says that you shouldn’t just pitch forecast accuracy to your executive management, but translate your plan into business metrics.

Trade promotion forecasting: the present and the near future

ToolsGroup

Trade promotion forecasting is difficult: getting it right involves factoring in many variables. Forecasting demand data, not so much. To do this, the first hurdle is creating a good statistical baseline forecast.

Why You Should Embrace Uncertainty in Demand Forecasting

ToolsGroup

This explains also why supply chain planners struggle to improve their forecasts and end up hitting a ceiling. The increase of demand volatility in today’s markets explains why supply chain leaders tend to believe that their primary supply chain problem is forecast accuracy.

Probabilistic Forecasting Can Extend the Life of SAP APO

ToolsGroup

Since the beginning of time – OK, since the beginning of demand forecasting the standard approach has been a single number forecast that works relatively well with stable high volume demand. Machine learning can refine the forecast by crunching external data.