Introducing parts forecaster: Pain-free inventory management

  • Last Updated: July 14, 2020
  • Lisa Huang
  • 3 min read

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We’ll get straight to the point: Managing parts inventory is a pain in the a$$.

Between just-in-time, rolling average, or sawtooth, there’s no perfect method to accurately predict what parts you’ll need on hand. It generally requires hiring an inventory manager, studying models like economic quantity order (EOQ) and lots of spreadsheets.

But there’s a better way.

Fiix just launched its parts forecaster, which automatically sorts through a bunch of data in your CMMS and helps you find trends so you can keep the right parts on hand.

What is parts forecaster and how is it different?

Parts forecaster is a tool within Fiix that predicts what parts you need to purchase for upcoming maintenance. It’s part of Fiix Foresight, the AI engine within Fiix that takes your CMMS, automatically looks for patterns within it, and offers recommendations based on the results.

Parts forecaster analyzes the way you’ve used parts in the past as well as upcoming work on your schedule. It then tells you what parts you’ll need to complete that work, which ones to order based on your inventory levels, and when you’ll need to order them based on your purchasing patterns.

The forecaster even accounts for seasonality and can quickly adapt to any changes you make to your maintenance program to keep recommendations accurate.

As with all Fiix Foresight reports, parts forecaster is available on the Fiix analytics dashboard. Instead of looking at a separate report and messing around with spreadsheets, you’ll be able to see the data, visualize trends, and drill down into results from Fiix analytics. The best part is, there’s no extra cost or coding necessary to get these forecasts—they appear automatically as long as the parts forecaster widget has been added to your dashboard.

How does it perform in comparison to traditional forecasting methods?

Here’s a burning question that all our customers have: When it comes to traditional forecasting methods, how does the parts forecaster perform?

Sawtooth or min/max

In the sawtooth method, purchase orders are made based on current inventory levels. When stock reaches a reorder point, the inventory manager orders a specific quantity to ensure stock will never dip past the minimum. This method is ideal for minimizing the risk of stockout. However, having a safety stock on hand encourages inventory managers to carry a large inventory, which ties up working capital.

With the parts forecaster, purchasing recommendations take predicted parts usage into account. We make sure you have exactly what you need, and at the right time, so you don’t have to keep a large safety stock to avoid stockouts.

Just-in-time

We typically see the just-in-time method in lean manufacturing, where inventory managers order parts just before they’re needed. This lets them reduce inventory and minimize working capital, but it’s tricky to keep the right balance. Without a safety stock in place, teams that use just-in-time are often prone to stockouts.

The parts forecaster helps by automatically analyzing all historical parts and maintenance data in the CMMS to accurately predict upcoming parts usage to avoid the risk of stockouts.

Rolling average

In a rolling average approach, inventory managers look at average parts consumption over 2-3 weeks to inform purchasing decisions, and order parts on a fixed and recurring schedule. While this is arguably an easier method to adopt, it can be highly inaccurate. For example, changes in demand based on seasonality can cause stockouts or result in overordering of parts.

The parts forecaster can spot patterns in your maintenance practices, like seasonal trends. It will leverage these insights to give you accurate parts predictions and purchasing recommendations.

Early beta customers using the parts forecaster are seeing a 50% increase in parts forecasting accuracy and up to 40% reduction in stockouts. Additionally, customers that follow the report recommendations have seen a 50% reduction in working capital reserved for parts.

And that’s just the tip of the iceberg. The magic of artificial intelligence is that the more these models are used, the more accurate they become, so as more customers start to take advantage of the parts predictor, you’ll see those numbers start to improve considerably.

How do I take advantage of it?

The parts forecaster doesn’t have to replace your existing processes. We’ve seen our customers use the report for many purposes:

  1. Inform purchasing decisions: If you don’t currently have an inventory process in place, you can skip the legwork and go straight to using the parts forecaster to determine your parts reorder quantities.
  2. Confirm and adjust purchasing quantities: If you are already using one of the inventory models we mentioned earlier, you can always cross-reference the parts forecaster with your existing purchasing plans to identify areas for improvement. We see a lot of customers adjusting their ordering quantities based on the predictions in the report.
  3. Improve processes: Since the accuracy of the report is based on parts usage data, you can also use the report to pinpoint areas of improvement in your parts tracking process. Better yet, as you continue to improve your processes, your report accuracy will improve!

How do I get started?

Having the right parts on hand is crucial for operating an efficient maintenance team. We’ve seen so many customers struggle to keep inventory under control so we built the parts forecaster to help maintenance teams easily get accurate insights.

This is where it gets really exciting: We’ve done everything in our power to make setting up our parts forecaster super straightforward. Any Fiix customer in the Professional or Enterprise tier currently using the parts and supplies module and with enough historical data will have access to the parts forecaster report through the Fiix analytics tool. All you have to do is select the report, add it to your dashboard, and you can start using parts forecaster right away.

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