Plan better with automated inventory forecasting

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Plan better with automated inventory forecasting

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Inventory forecasting isn’t easy, but Parabola makes this often-complicated process repeatable, understandable, and automate-able. Read more to learn about Inventory Forecasting, and to see a breakdown of a Parabola Flow that automates the process.

What is inventory forecasting?

Inventory forecasting, also called demand planning, helps teams predict how many months of inventory they have left before they need to restock. Teams can use inventory forecasting to ensure they don’t run out of their most popular products; they can also use it to prevent overstocking products that may not need to be frequently replaced. Forecasting takes into account not just how quickly inventory needs to be restocked, but also how quickly replacement inventory will arrive. Your team can use this analysis to ensure that you’re never caught off guard and that your customers are never left waiting due to under-stocking.

Why is inventory forecasting important?

With global supply chain issues affecting almost every industry, and with so many external factors outside of a company’s control, having a sustainable way to accurately forecast inventory is more important than ever before.

Using inventory forecasting to plan can help:

  • 💰 Maximize your team’s revenue: Know when replacement inventory will arrive so you continue to sell your products and not list them as out of stock.
  • 💳 Save money: Make sure you only order what you need by focusing on more popular items and not overstocking items that won’t sell as quickly which can lead to overcrowded storage and wasted money.
  • ✌️ Create a positive customer experience: Customers won’t be left waiting for prolonged periods of time because the item they’ve ordered is out of stock and you’re waiting for replacement inventory.
Photo by Artificial Photography on Unsplash

What makes inventory forecasting difficult?

With any type of planning, there are always difficulties that a team must tackle. Here are just a few that you may encounter while using inventory forecasting:

Multiple datapoints to manage

To make sure you’re getting the most out of your inventory forecasting, there are quite a few areas that your team will need to look into. You’ll likely want to:

  1. Understand how quickly your inventory is selling and pinpoint sales trends to have an idea of when an item will sell.
  2. Determine when to reorder items to replace the sold inventory as well as know how long it will take for that replacement inventory to arrive.
  3. Have “extra” stock to ensure items don’t sell out while waiting for replacement inventory.

Throughout the process of finding this information, your team is likely coordinating across multiple venders and 3rd party partners. The data that you’ll need to make these calculations will often live in different systems and CSV files that must then be copied and pasted into one consolidated area before your team can even begin to start working with it.

To add to that difficulty, it’s highly likely that everything is saved in different formats and data will need to be reformatted as you work with it 🥵. Surfacing all of the information that you need and then formatting it in a way that you can easily work with is a time drain for teams that need to focus on other, more important, tasks.

Miscalculations can lead to customer dissatisfaction

If products are out of stock, people can’t buy them and may go to look for them elsewhere. Even worse, they may purchase an item that you can’t fulfill. You want to ensure that your customers  receive the products they’ve ordered in a timely manner. If customers are backordering items, you want to be able to let them know an accurate wait time so they aren’t left wondering if their order has been lost.

Photo by Denny Müller on Unsplash

Different methods can be used when forecasting

Every company faces unique challenges, which means your team will have to try different methods to find the right recipe for your inventory forecasting. Finding and then calculating this data can take time so it’s not easy to add additional information or switch out methods that end up being less helpful.

Here are just a few ingredients you may want to use when building out your perfect forecast:

  • 📈 Look at sales trends for products to determine which are the most popular
  • 📐 Determine at what threshold the team needs to reorder inventory
  • ⏱️ Calculate how long it will take for a replacement order to arrive
  • 📦 Determine how many “extras” of certain products are needed to meet demands

How can Parabola help?

Inventory forecasting has many moving parts that must first be brought together and viewed holistically before a team can begin to take action. Parabola allows you to:

  • Pull information from multiple sources into a single source so you can easily decide which items need to be ordered at what frequency.
  • Make quick updates as unexpected changes pop up.
  • Send your team an alert when inventory is low or when it is time to place a restock order.
A zoomed-out view of this Parabola Flow for Inventory Forecasting

Calculating 30-Day Sales Forecast

In the below example, one of our customers is calculating their sales forecast for the next 30 days. They are able to pull in their data from various sources and use a Combine tables step to join their last 30 days of sales data with the previous order that they placed to their supplier. They then compare the numbers between the sales they made and the orders they placed:

The first card pulls in sales orders and the last order to the supplier to calculate the next 30 day sales forecast.

Consolidate inventory, POs, and past sales

Next, they pull in data from three separate sources: their available inventory, their processed purchase orders (POs), and their sales from the week before. With that data pulled in, they make sure they’re only working with the data they want by using the Filter rows and Select columns steps. From there they use Insert math column steps to make sure they are pulling in the exact numbers that they need before easily consolidating all of those results with Combine tables steps:

Data is pulled in from 3 different sources across 3 different cards to be cleaned and reformatted before it is consolidated.

Finish the forecast and send to a report

Once they’ve combined their data, they calculate their product quantity and predict how many months of inventory they have before they’ll need to replace it. The Format numbers step lets them display their data exactly how they’d like. From there, they send that information to a shared Google Sheet for other members of the team to access.

All of the data is combined and used to forecast what will be left after the next 30 days as well as how many months there are to depletion. That information is then sent to a shared Google Sheet.

Your team may benefit from using a Flow like the one above to predict how long inventory will last before it must be reordered. If you need a place to start, you can use one of our Recipes like the Shopify Inventory Forecast recipe to

If you’re interested in building similar Flows to help your team with inventory forecasting, you can start building your own Flow for free by signing up for Parabola. Email us at help@parabola.io and we can help you get started!

Blog
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Plan better with automated inventory forecasting