Forecast Using Leading Indicators – Regression Analysis:

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Improve Forecast Accuracy, Eliminate Excess Inventory, & Maximize Service Levels

In this video tutorial Dr. Thomas Willemain, co–Founder and SVP Research at Smart Software, presents Regression Analysis, a specialized statistical modeling technique to identify and harness leading indicators to achieve more accurate forecasts.  Regression analysis is a statistical procedure to estimate the relationship between a response variable and one or more predictor variables. Housing starts, for example, might be a good leading indicator of vinyl siding demand.  Tom explains how and when to use regression analysis and works through a practical example.

Forecasting Techniques for a more profitable business
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Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

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Share, develop, and manage consensus demand plans

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Share, develop, and manage consensus demand plans to ensure inventory policy matches business strategy.

Smart Inventory Optimization (SIO) creates planning scenarios. SIO starts with a “Live” scenario that shows where you are now. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan that becomes the “Goal” scenario, which drives the ERP system’s replenishment planning.

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Related Posts

Share, develop, and manage consensus demand plans

Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

Pulling all the data together on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics to calculate multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Gaming Out Your Logistical Response to the Corona Virus

Gaming Out Your Logistical Response to the Corona Virus

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

Recent Posts

  • Research Vice President Forecasting Guru Tom WillemainForecast Using Leading Indicators – Regression Analysis:
    In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice. […]
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Forecasting Techniques for a more profitable business

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Improve Forecast Accuracy, Eliminate Excess Inventory, & Maximize Service Levels

 

In this Video Dr. Thomas Willemain, co–Founder and SVP Research, defines and compares the most useful Forecasting Techniques: Exponential Smoothing, Single Exponential Smoothing, Holt’s Method and Winter’s Method.  These videos explain the basic thinking under each technique as well as the math behind them, how they are used in practice and the tradeoff of each method.

Forecasting Techniques for a more profitable business
Leave a Comment

RECENT POSTS

Share, develop, and manage consensus demand plans

Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

Pulling all the data together on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics to calculate multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Gaming Out Your Logistical Response to the Corona Virus

Gaming Out Your Logistical Response to the Corona Virus

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

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  • Research Vice President Forecasting Guru Tom WillemainForecast Using Leading Indicators – Regression Analysis:
    In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice. […]
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    Smart Software, Inc. announced  today that the company completed its SOC 2 Type II Audit, delivering the highest level of data security and availability for customers and partners. . […]

Clean, accessible and actionable data under one roof

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Is your data isolated in Excel Silos? Do you have data in many disparate systems? Smart IP&O Solution brings clean, accessible and actionable data under one roof.

Scattering all your data across multiple spreadsheets gets in your way. Pulling all the data together in the Smart Platform on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics in the Smart Inventory Optimization app to see how you’re doing in terms of multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Leave a Comment

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Share, develop, and manage consensus demand plans

Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

Pulling all the data together on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics to calculate multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Gaming Out Your Logistical Response to the Corona Virus

Gaming Out Your Logistical Response to the Corona Virus

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

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  • Research Vice President Forecasting Guru Tom WillemainForecast Using Leading Indicators – Regression Analysis:
    In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice. […]
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Gaming Out Your Logistical Response to the Corona Virus

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

​As the world holds its breathe to see how the new corona virus (2019-nCOV) will play out, we cross our fingers for all those currently in quarantine or under treatment and pray that health authorities around the world will soon get the upper hand.

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

Reacting to Longer Lead Times

This is a problem that can be solved using advanced supply chain analytics. Presumably, you may have already used this technology to make good choices for the control parameters used in managing all your inventory items, e.g., values for Min and Max or Reorder Point and Order Quantity. The specific technical question addressed here is how to convert an increase in replenishment lead time to changes in those control parameters.

In general, longer lead times require fatter inventories if you want to maintain a high level of customer service. This general rule translates into larger values of Min and/or Max. How much larger depends critically on what new, longer lead time values will appear and their probabilities of occurring.

While many planning software systems assume a fixed lead time, the reality is that almost all lead times have some degree of randomness. Typically, ignoring that randomness increases stockout risk, so having a good estimate of the probability distribution of lead times is important. In normal times, your transactional data can be used to estimate that relationship. But sudden disruptions like 2019-nCOV create unprecedented situations in which you have to make educated guesses about what new delays you will see and how likely they are. We will assume here that you can imagine some such scenarios and want to figure out how to best respond to them.

An Example using Advanced Software

To illustrate this type of prospective planning, consider a hypothetical example. One item, a spare part, has an established pattern of replenishment lead times, with delays of 5, 10 and 15 days occurring with 15%, 70% and 15% probabilities, respectively. Given this distribution and a random demand averaging one unit every 5 days, values of Min = 5 and Max = 10 do a good job. Figure 1 shows a simulation of 10 years of daily operation under this scenario. Fill rate and service level are high, and stockouts are infrequent.

Now suppose that disruptions in the supply chain create a less favorable distribution of lead time, with a 50:50 mix of 15 and 30 days. Figure 2 shows how badly the current values of Min and Max perform in this new scenario. Fill rate and service level plummet due to frequent stockouts. Operating costs more than triple due to penalties for backorders. Only inventory investment (the average dollar value of stock on the shelf) seems to get better, but this happens only because so often there are backorders with nothing left on the shelf. The shift to longer lead times clearly requires new higher values of Min and Max.

Figure 3 shows how the system performs when the Min is increased from 5 to 10 and the Max from 10 to 15. This change compensates for the longer lead times, restoring the previous high levels of fill rate and service level. Inventory investment is necessarily greater, but operating costs are actually lower than before.

Summary

Changes in normal operating conditions require adjustments in the way inventory items are managed. One such change looming large on this date is the potential impact of the 2019-nCOV Corona virus on supply chains, with anticipated increases in replenishment lead times.

Changes in lead times require changes in inventory control parameters such as Min’s and Max’s. These changes are difficult to make with any confidence using pure guesswork. But with some estimate of the increase in lead times, you can use advanced software to learn how to make these adjustments with some confidence.

This note illustrates this point using simulations of the daily operation of an inventory control system.

Figure 1 Simulation of normal operations using current replenishment lead times, Min and Max

Figure 2 Simulation of abnormal operations using longer lead times and current Min and Max

Figure 3 Simulation of abnormal operations using longer lead times and revised Min and Max

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Related Posts

Share, develop, and manage consensus demand plans

Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

Pulling all the data together on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics to calculate multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Gaming Out Your Logistical Response to the Corona Virus

Gaming Out Your Logistical Response to the Corona Virus

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

Recent Posts

  • Research Vice President Forecasting Guru Tom WillemainForecast Using Leading Indicators – Regression Analysis:
    In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice. […]
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    Smart Software, Inc. announced  today that the company completed its SOC 2 Type II Audit, delivering the highest level of data security and availability for customers and partners. . […]

TOP 3 COMMON INVENTORY POLICIES

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Inventory control policies and strategies for a more profitable business

In this Video Dr. Thomas Willemain, co–Founder and SVP Research, defines and compares the three most used inventory control policies. These policies are divided into two groups, periodic review and continuous review. There is also a fourth policy called MRP logic or forecast based inventory planning which is the subject of a separate video blog that you can see here. These videos explain each policy, how they are used in practice and the pros and cons of each approach.

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RECENT POSTS

Share, develop, and manage consensus demand plans

Share, develop, and manage consensus demand plans

Ensure inventory policy matches business strategy. Various team members can create their own scenarios, perhaps dividing the work by product line or sales territory. One decision maker can then merge these scenarios into a consensus plan.

Clean, accessible and actionable data under one roof

Clean, accessible and actionable data under one roof

Pulling all the data together on the cloud lets you automatically refresh the data every day and always see the full picture. Then you can run analytics to calculate multiple cost and performance metrics and how those metrics would change if you changed key drivers, such as supplier lead times.

Gaming Out Your Logistical Response to the Corona Virus

Gaming Out Your Logistical Response to the Corona Virus

This short note is about one way your business can develop a plan to adjust to one of the likely fallouts from the virus: sudden increases in the time it takes to get inventory replenishment from suppliers. Supply chains around the world are being disrupted. If this happens to you, how can you react in a systematic way?

Recent Posts

  • Research Vice President Forecasting Guru Tom WillemainForecast Using Leading Indicators – Regression Analysis:
    In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice. […]
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