What Are the Most Important 2020 Freight Metrics to Know?

Cerasis

In early 2020, the market forecast for freight looked bright. The post What Are the Most Important 2020 Freight Metrics to Know? Data Freight 2020 freight metricsThe turmoil of the U.S.-China China trade war appeared at an end, and few disruptions were believed to cause issues in 2020. Then, coronavirus happened to spread, and now, it will impact global supply chains. It is only a matter of time. Fortunately, understanding the facts.read More.

Modern Metrics

synchrono

We use these technologies to track levels of contact engagement and conversion ratios to develop more predictable buying cycle patterns and pipeline forecasts. Given the more customer-centric demand-driven model – coupled with greater access to information – the metrics that manufacturers monitor to make improvements in operations become more focused and actionable. White Paper: Demand-Driven Manufacturing Metrics that Drive Action.

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Driving Supply Chain Analytics User Adoption with Cross-Departmental Metrics

Logility

The obvious danger of this is that business rules and data governance often don’t exist from department to department or user to user, leaving an overall picture into the health of the business that is foggy because KPIs and metrics do not correlate across the organization. Executives look at high-level company metrics, while other departments such as Finance, Sales, and Operations work at a more analytical level.

Metrics that Matter: Inventory Effectiveness

QAD

It is critical to monitor inventory effectiveness using five key metrics: Expedited orders, inventory turns, obsolete inventory, safety stock and stockouts. Using Metrics to Measure the Health of the Business. Companies use these metrics to minimize their investment in inventory without adversely affecting customer service levels. The absolute measure is less informative than the trend in the metrics. Tracking, Managing, and Choosing Metrics.

Time for a Supply Chain Metrics Cleaning

Logility

Ask yourself, “Are your supply chain metrics bogging you down?” ” To manage a supply chain containing complex dependencies between teams, departments and partner companies across international boundaries requires a rich set of metrics. However, companies often have too many independent metrics that can cause conflicts amongst competing supply chain functions. Functionally isolated metrics lead to sub-optimized supply chain performance.

Omnichannel Supply Chain Metrics: What Should Supply Chain Leaders Measure?

Cerasis

The answer lies using these omnichannel supply chain metrics to carefully track and improve operations continuously. This is a simple key performance indicator (KPI), another name for metrics, to track. The Fill Rate is a complex metric that considers the average window of delivery, percent of on-time delivery and accuracy of delivery for all products coming into your warehouse from vendors. Forecasting Accuracy KPIs.

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.

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

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

Sales Dashboards: 16 Metrics For Manufacturers

Silvon Software

The more challenging part of dashboarding, however, gets down to the actual metrics that should be included as part of a performance management strategy. As a place to start, I thought I’d provide a shortlist of both simple and more complex metrics that our manufacturing and distribution clients are using in their dashboards today. Today’s post focuses on Sales metrics only. Basic Sales Metrics. Sales to plan / forecast. More Complex Sales Metrics.

Metrics that Matter: Customer Service

QAD

Inventory accuracy and minimizing stockouts are very important to customer satisfaction, but a few other metrics also impact the ability to meet customer expectations. Forecast Accuracy. This is defined as the ratio of forecast to actual demand in a period. Companies can use these metrics to help ensure they are doing everything possible to satisfy their customers at a manageable and sustainable cost. Forecast Accuracy. Choosing Metrics.

Supply Chain Dashboards – Key Metrics For Manufacturers

Silvon Software

As I mentioned in my previous post, Sales Dashboards – 16 Metrics for Manufacturers , a strategy for measuring business performance should also incorporate metrics that focus on the supply chain and other operational areas of the enterprise. Supply chain metrics and key performance indicators (KPIs) are sometimes a bit tougher to compile than sales metrics. Sales to Forecast and Sales to Outlook.

5 Considerations When Evaluating your ERP system’s Forecasting Capabilities

The Smart Software

Consider what is meant by “demand management”, “demand planning”, and “forecasting”. The post 5 Considerations When Evaluating your ERP system’s Forecasting Capabilities appeared first on Smart Software. These terms imply certain standard functionality for collaboration, statistical analysis, and reporting to support a professional demand planning process.

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. A recent report from Gartner agrees, focusing specifically on the challenge of building a better business case for improved forecast accuracy. Gartner says that you shouldn’t just pitch forecast accuracy to your executive management, but translate your plan into business metrics. Forecasting Demand and Analytics

Forecasting and Demand Planning for a Better, Unified Future

Logility

Year after year, survey after survey, forecast accuracy continues to be one of the top metrics for measuring supply chain performance. That is very powerful; one forecast to drive the business forward. “. Watch: When Planning for Forecast Accuracy, Visibility is in Demand.).

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. Stakeholders who care about forecasting in demand planning care about accuracy, and usually will not accept a new forecasting method unless it is rigorously validated against known forecasting benchmarks with proven accuracy.

Why You Should Embrace Uncertainty in Demand Forecasting – Part 2

ToolsGroup

Here is one straightforward opportunity to focus on in the near future: Migrate away from top-down demand forecasting. Despite the added complexities in today’s supply chains, traditional SCP systems like SAP APO typically apply the traditional "top-down" approach to forecasting based on aggregated data. When it comes to long-tail items, forecasting metrics such as WMAPE become almost meaningless or even misleading.

How to Get Started with Value-add Forecasting (Part 2)

Logility

So, the promise of using statistical algorithms, forecasting and predictive analytics is now added to the list of a company’s number one priorities. Here are a few steps that you will need to take to deploy your forecasts successfully. In far too many cases, forecasts are done as a fishing expedition where analysts run the data through predictive algorithms to see what “pops.” Evaluate the forecasting power against the risk level of the decisions that are being made.

Forecast Accuracy at the SKU Level is Achievable

Logility

Over my 25+ year supply chain career I have worked for several distribution-intensive companies and every single one of them had a focus on improving forecast accuracy. Achieving a high SKU level forecast accuracy is a top goal for supply chain planning teams regardless of industry, size, location, etc. Gartner, for example, places demand forecasts at the top of their Hierarchy of Supply Chain Metrics to highlight the impact of forecasts throughout the supply chain.

Here’s What’s Wrong with Demand Forecasting

ToolsGroup

Since there will be a week off between posts, we wanted to forgo the fluff in most year-end blogs and leave you with a deep philosophical thought to ponder while on your holiday break, and it’s this: Maybe you are doing your demand forecasting completely wrong. OK, to be more precise, there are two equally important outputs of demand forecasting and you may be focusing nearly all your energy on only one, and maybe even the wrong one. It starts with what constitutes forecast error.

The Forecasting Conundrum

Logility

I have heard a number of supply chain professionals proclaim that their companies should stop forecasting product demand due to poor forecast accuracy. However, what is often overlooked is that moving to a pull strategy does not eliminate the need for a forecast. Most likely the company will still need to forecast raw materials, purchased components, and/or sub-assemblies to be able to meet customer demand. The forecast process needs an executive champion.

DIFOT: A Metric of Supplier Performance

Unleashed

Delivery In Full On Time, or DIFOT, is a metric used to analyse how accurate and efficient your supply chain is. When it comes time to reassess the approved supplier list, then you can use these metrics to disqualify problematic suppliers and improve your own performance and supply chain. If you are measuring your own DIFOT scores as a distributor, you can use the metrics to promote your own success and ability to fulfil demand.

Overcoming Complacency: How to Drive Even More Supply Chain Metric Success

Talking Logistics

The four key methods here will help you drive more success as you bring the metrics to life on your warehouse floor: 1. Show the “story” of your metrics with quarterly and yearly growth charts; show how far you’ve come as a team over time. While most metrics stop at the output level, multiple layers of metrics in a Hoshin Plan actually determine if you’re even focusing on the right targets. A sense of complacency can lurk behind benchmarks.

Five Elements of Successful Sales Forecasting

Logility

While extremely valuable, any reputation forecasting has can quickly be tarnished by bad experiences. A more fundamental issue is knowing what business problems forecasting can address. The statistical forecast is generated to make adjustments to sales and production planning.

Top 10 Demand Planning Metrics You Should Have on Your Dashboard [Infographic]

Arkieva

To stay ahead of the curve, effective demand planners must track the right metrics that can help curtail possible demand planning issues ahead of time. Top 10 Demand Planning Metrics You Should Have on Your Dashboard [Infographic] was first posted on January 29, 2019 at 2:07 pm. ©2017 ©2017 " Supply Chain Link Blog - Arkieva " Use of this feed is for personal non-commercial use only.

Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics

ThroughPut

ELI enables manufacturers to meet and beat their Supply Chain Forecasting Goals by nailing-down bottlenecks & eliminating waste to achieve end-to-end efficiencies. The post Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics appeared first on ThroughPut. What is Manufacturing Throughput?

Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics

ThroughPut

ELI enables manufacturers to meet and beat their Supply Chain Forecasting Goals by nailing-down bottlenecks & eliminating waste to achieve end-to-end efficiencies. The post Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics appeared first on ThroughPut. What is Manufacturing Throughput?

Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics

ThroughPut

ELI enables manufacturers to meet and beat their Supply Chain Forecasting Goals by nailing-down bottlenecks & eliminating waste to achieve end-to-end efficiencies. The post Manufacturing Throughput – A Comprehensive Guide on Key Manufacturing Metrics appeared first on ThroughPut. What is Manufacturing Throughput?

Forecast Accuracy: Why It Matters and How to Improve It

E2open

Demand forecasts underpin essentially every major business decision, but discussions about forecast accuracy rarely get visibility outside of supply chain organizations, let alone at the board level.

Adventures in Forecasting in the Supply Chain

Supply Chain Opz

And no function is more at the forefront of that endeavor than demand forecasting. In order to do that, forward planning is key, and accurate forecasts are a critical input. The quest then lies within forecasting, which seeks to provide the best possible estimate of future sales to enable the organization to effectively plan to meet that future requirement. Given that demand can change every day, forecasting becomes the ultimate adventure.

Riding the Tradeoff Curve

The Smart Software

Blog Business Policy Demand Planning Excellence in Forecasting Inventory Optimization Operational Analytics demand forecast demand planning implementations efficient stocking ERP forecasting forecasting software inventory modeling inventory optimization kpi metrics overstock overstocking probabilistic modeling statistical forecasting stockouts supply chain analytics understock

FORECAST DRIVEN INVENTORY MANAGEMENT

The Smart Software

The post FORECAST DRIVEN INVENTORY MANAGEMENT appeared first on Smart Software. Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory.

A Zen Master’s Guide to a Good Forecasting System

Halo

Five Koan of A Good Forecasting System. Having a hard time figuring out how to use forecasting when the results never seem good enough? For many of us, forecasting seems like either too much work, or too complicated to get right. With deep apologies to philosophers and history, here are five Koan that may help you in your quest to improve your forecasting. Amid this change, a good sales forecasting model won’t last. Forecastability’, not accuracy.

The Right Forecast Accuracy Metric for Inventory Planning

The Smart Software

Traditional forecasting accuracy metrics aren't applicable when the goal is to optimize inventory. This blog explains why and details how to calculate the metric. The post The Right Forecast Accuracy Metric for Inventory Planning appeared first on Smart Software. Blog Demand Planning Excellence in Forecasting Inventory Optimization demand planning forecast forecast accuracy inventory planning

Demand Forecasting Mistakes in the Retail Industry

Alloy

Consumer goods companies rely on forecasts to support inventory planning and distribution across their sales channels. Building accurate demand forecasts requires more than just an understanding of the latest machine learning techniques; it also requires the right data and an understanding of the potential costs of incorrect estimates. Below, we’ll explore two of the top forecasting errors consumer brands commit, along with suggestions for how to avoid these pitfalls.