Inventory forecasting in excel can be very difficult for Shopify store owners with a large number of SKUs. Excel can seem like a cheap solution, but it isn't the best solution for making forecasts, especially if your Shopify store has a large product line. Monocle offers a tailored solution that goes beyond Excel's basic capabilities when it comes to stockouts or overstocks, ensuring that your business is never caught off guard by them. 

Why Use Excel in Basic Forecasting?

Excel is the go-to tool for many, especially for businesses with a limited range of products. Its appeal lies in its familiarity and the perception of cost savings. However, this approach is only suitable for businesses with very few SKUs. For those with a broader inventory, relying on Excel can be a gamble, often leading to stockouts or overstock situations due to its limited forecasting capabilities.

Pros of Inventory Forecasting in Excel

Excel's primary advantage is its cost-effectiveness and its relatively simple learning curve for those already acquainted with its basic functions. It's a readily available tool that can handle basic inventory forecasting needs without additional investment.

Cons of Inventory Forecasting in Excel

However, the cons of using Excel for inventory forecasting are significant, especially for businesses managing more than 50 SKUs. The risks include lost time due to manual data entry, potential for human error, limited scalability, and most critically, the financial repercussions of stockouts or overstocking due to inaccurate forecasting.

Basic Excel Forecast Functions You Need to Know

If you choose to use Excel, here are some basic functions for demand forecasting:

Simple Moving Average (SMA): Useful for smoothing out short-term fluctuations. Use the AVERAGE function, like =AVERAGE(B2:B4).

Exponential Smoothing: Ideal for data without trends or seasonal patterns. While Excel doesn’t have a direct function, FORECAST.ETS can be used in newer versions.

Linear Regression Analysis: Helps understand relationships between variables. Use =FORECAST.LINEAR(x, known_y's, known_x's).

Our Alternative To Forecasting Methods in Excel

Monocle's E-Commerce Safety Stock Feature

Keeping track of safety stock is essential for any online store utilizing Shopify for inventory management. Designed with Shopify store owners in mind, Monocle's solution streamlines this procedure. The functionality is created to address the specific issues encountered by online stores, such unexpected surges in demand, inconsistent suppliers, and the sometimes rapid changes of online consumer preferences. To make sure that online stores never run out of products when demand spikes unexpectedly, but also don't have too much on hand and end up with capital sitting idle, Monocle automates safety stock calculations for every product SKU. Stores carrying a diverse assortment of products benefit greatly from this automation because human tracking can be time-consuming and prone to mistakes.

You can test out the safety stock formula that Monocle uses here: 

Z⋅(Average LT⋅(Demand Standard Deviation)

2+(Average Sale⋅Lead Time Standard Deviation)

2

)

Monocle's ABC XYZ Analysis for E-Commerce

Online store inventory management has never been easier than using Monocle's ABC XYZ analysis tool. An all-encompassing approach for inventory categorization, this feature merges the tried-and-true ABC analysis (based on sales volume) with the more recent XYZ analysis (based on demand volatility). Since product trends and customer behaviours can change at a quick pace in the e-commerce sector, this dual analysis is particularly valuable in that context.

This feature helps store owners focus on the products that represent their biggest sales, and bring them the most profit.

You can test out the ABC XYZ Analysis formula that Monocle uses here:

=STDEVP(range) / AVERAGE(range)

Strategic Inventory Categorization:

Products are categorized into groups like AX (high sales volume, stable demand) and CZ (low sales volume, unpredictable demand), allowing e-commerce businesses to tailor their inventory strategies for each category.

Optimized Inventory Management: 

This feature helps you set accurate service levels and safety stock goals for each category so you can find a good mix between buying inventory and the product's sales potential and stable demand.

Beyond Inventory Management:

The ABC XYZ analysis in Monocle is not just a tool for managing stock; it's a strategic asset for broader business decision-making, influencing marketing, sales forecasting, and supplier relations.

E-Commerce Specific Insights

Monocle's tool is designed with the e-commerce landscape in mind, considering the unique challenges and opportunities of online retail.

Actionable Insights for E-Commerce

Monocle's ABC XYZ analysis provides actionable insights, enabling e-commerce businesses to classify products effectively, set appropriate service levels, and continuously adapt to the dynamic online market.

By integrating these features, Monocle offers a robust solution for e-commerce businesses, ensuring that they can manage their inventory efficiently and effectively, staying ahead in the competitive online retail space.

Monocle’s Alternative To Forecasting Models In Excel

Monocle's cutting-edge AutoML (Automated Machine Learning) technology, specifically created for time series data, revolutionises inventory forecasting for e-commerce. This novel method of inventory management is a game changer, especially for e-commerce enterprises with diversified and dynamic product lines.

The Power of AutoML in Forecasting

In Monocle, AutoML is more than just a tool; it's a powerful machine learning brain that examines many predicting models for each product. It evaluates each model's performance by calculating the Root Mean Square Error (RMSE), a typical statistic for quantifying a model's prediction error. This procedure ensures that the most accurate forecasting model for each product is chosen.

Diverse Range of Models

AutoML from Monocle isn't just for simple statistical models. It includes a lot of different models, from simple statistical models to more complex ones based on machine learning, such as neural networks and additive regression models. This variety is very important because predicting inventory isn't a one-size-fits-all job. Based on their past sales and how the market acts, various products need different ways of making predictions.

Catering to Different Types of Time Series Data

Monocle's AutoML is adept at handling various types of time series data, which is crucial for accurate forecasting:

Secular Trends: These are long-term movements in data over time, which the system identifies and adapts to.

Seasonal Variations: Monocle recognizes and adjusts for seasonal changes, crucial for products with sales peaks during specific times of the year.

Cyclical Fluctuations: These are patterns that occur over periods longer than a year, not necessarily tied to seasons, which Monocle's models can also detect and forecast.

Irregular Variations: These are unpredictable, non-recurring fluctuations that Monocle's system can identify, ensuring that even the most unexpected market changes are accounted for in the forecasts.

Advanced Baseline Model

The baseline model in Monocle's arsenal is an advanced additive regression model. This model is particularly adept at picking up nuances like weekend, holiday, and seasonal effects – for instance, recognizing and forecasting increased sales during Christmas or other significant shopping periods.

Seamless Integration with Shopify

One of Monolces unique strongsuits is how well it works with Shopify. Monocle starts analyzing a merchant's Shopify sales data as soon as they install it. Because of this integration, the seller doesn't have to do any manual input for the forecasting part. Monocle pulls the data and starts the forecasting process immediately, so the store owner doesn't have to do much to get accurate, data-driven insights.

To sum up, Monocle's use of AutoML for time series data is a big step forward for e-commerce businesses' ability to predict their product needs. E-commerce sellers who want to improve their inventory management and stay ahead in the competitive online market can benefit greatly from this tool because it can choose the best model for each product and work with different types of time series data.

Should You Consider Automated Inventory Forecasting?

Automated inventory forecasting with Monocle is great for Shopify brands that want to grow, handle a lot of stock, and avoid stockouts and overstock situations. Monocle's answer is made to handle the complicated needs of today's e-commerce companies. For stores with large inventory it is simply more reliable and effective than old-fashioned methods like Excel.

In conclusion, Excel may seem like a simple and inexpensive way to plan your product needs, but as your business grows and changes, its flaws become will become clear. Monocle offers a a superior option, using advanced analytics and machine learning to give you accurate, up-to-date, and useful information for your inventory forecasting needs. Are you ready to take your Shopify store to the next level? Find out more about Monocle and how it can help you forecast your inventory here.