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Pastry Chef johnw
Pastry Chef

Trunk Stock analytics - determining accurate on hand requirements

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Has anyone determined a formula to help determine the part quantity levels a Service Engineer should keep in their trunk stock?

Our current method is to let the users set a Minimum/maximum levels (in our ERP). We want to be able to let the system manage this (or our  Materials group). So the big question is if any customers are using ServiceMax data and reports to come up with a method to calculate the re-order point for specific parts.

Is it as simple as averaging the prior years usage for a specific part?

Thanks

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Re: Trunk Stock analytics - determining accurate on hand requirements

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To Colby's point this is a complex problem, but I believe the data resides in ServiceMax for you to build reports to model your business situation and potentially reach a fairly reliable answer.

I would start by averaging the rate of consumption for a part, but that you must consider the inventory cost, lead time on replenishment, and the subsequent impact these could have on your SLAs.

Determine weighting factors based for the part cost, and the lead time and track this in ServiceMax on the inventory item, generate a report with 3 columns by reporting period

Estimated level - Your calculated replenishment level based on your weighting factors * historical average consumption

Actual Stock level - Actual average stock across your technicians

Total consumption - How many of the part were consumed in that period on average

A report like this would allow to to massage the weight factors so your estimated levels matched actual consumption. You may need to get more granular by region for better quality data, but this would allow you to manage a low risk experiment based on actual data across your real business parts consumption. Creating a simple line report historically would allow you to track your assumptions vs actuals until such time as you felt confidence in the results.

The model could be more complete if you could plot part by product and map that to actual number of Installed Base for that product, but that depends on if you have this data easily accessible in the system.

The ease of being able to generate reports in ServiceMax, and analyze historical data would allow you to run a number of scenarios relatively quickly.

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Employee
Employee

Re: Trunk Stock analytics - determining accurate on hand requirements

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Hi John,

Wonderful question that took me back to a class I took at Berkeley almost a decade ago.  Determining stock levels is not as simple as an average.  Search online for the term "safety stock" and you will get a wealth of information.  Stock levels depends many factors such as the part demand, deviation of demand, cost of holding the inventory, lead time to replenish, company's goals to have part in stock (e.g. 90% of time when needed or 99.99%?), etc.  As you can see, it can get complicated quickly but I believe there are resources out there to help you answer this question.

Thanks,
Colby

Colby Lavin

Director of Product Management

ServiceMax Inc.

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Pastry Chef johnw
Pastry Chef

Re: Trunk Stock analytics - determining accurate on hand requirements

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Colby,

Thanks for the response. I know this would be more than just an average. There are so many variables that need to be added when you put Safety Stock and Field/Depot Service in the same sentence.

Thanks

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Re: Trunk Stock analytics - determining accurate on hand requirements

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To Colby's point this is a complex problem, but I believe the data resides in ServiceMax for you to build reports to model your business situation and potentially reach a fairly reliable answer.

I would start by averaging the rate of consumption for a part, but that you must consider the inventory cost, lead time on replenishment, and the subsequent impact these could have on your SLAs.

Determine weighting factors based for the part cost, and the lead time and track this in ServiceMax on the inventory item, generate a report with 3 columns by reporting period

Estimated level - Your calculated replenishment level based on your weighting factors * historical average consumption

Actual Stock level - Actual average stock across your technicians

Total consumption - How many of the part were consumed in that period on average

A report like this would allow to to massage the weight factors so your estimated levels matched actual consumption. You may need to get more granular by region for better quality data, but this would allow you to manage a low risk experiment based on actual data across your real business parts consumption. Creating a simple line report historically would allow you to track your assumptions vs actuals until such time as you felt confidence in the results.

The model could be more complete if you could plot part by product and map that to actual number of Installed Base for that product, but that depends on if you have this data easily accessible in the system.

The ease of being able to generate reports in ServiceMax, and analyze historical data would allow you to run a number of scenarios relatively quickly.

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