In today’s era of technology and online shopping trend, businesses are looking for methods to win more customers with less investment and minimum wastage. Retail and manufacturing companies everyday face the challenge of extra and obsolete inventory in their warehouse which not only increases the business cost but also blocks storage place for more profitable product storage.
Inventory forecasting is one of the efficient methods of resolving this imbalanced stock storage issue. Let’s understand different models on Inventory forecasting and select the best suited one for our business requirement.
What is Inventory Forecasting?
As the name suggests, forecasting is making an informed futuristic plan about inventory ordering.
Inventory estimation or forecasting can be defined as a process of predicting inventory for future time periods. More specifically inventory estimation is a scientific approach of predicting revenue generation during a specified period of time based on the precisely designed proposed marketing plan.
When working with one large retailer, Harve Light, managing director at Conway MacKenzie, and team learned that a 10% increase in forecast accuracy could increase profitability by more than $10 million.
Certain information is defined to give the most accurate outcome:
- Forecast period
A forecast period is a given period of time which decides the forecast quantity.
A trend is a demand supply chain over a certain period of time. Identifying any particular product trend makes it easier to project future sales of that product.
- Base demand
The base demand is simply the current demand of a particular product.
An optimised inventory control needs a forecasting of both reorder points and order quantities to produce accurate results of this metric. Let’s understand the details of these values which are very critical while forecasting a products trend.
- Reorder Points
The reorder pints is the answer to WHEN to order your inventory. As forecasting plays a very important role in every wholesales market, we need to have a clear picture on when to order a product considering the lead time of the product procurement. Lead time is the time which suppliers takes to deliver the products to the warehouses for production.
A basic formula for the reorder point is:
Reorder level = Average daily usage rate x lead-time in days
In many cases, lead time tends to delay and product delivery gets delayed because of it, hence the concept of safety stocks are made. Safety stock is referred to keep some extra amount of stock in order to handle lead time delays in the production cycle.
Read More – 4 Reasons for Carrying Safety Stock Inventory
Once we understand when to order, we should now understand how much to order for a balanced inventory for our manufacturing cycle.
- Economic Order Quantity (EOQ)
EOQ places a very crucial part in business revenue management, by forecasting the ideal order quantity which can match the customer demand and also minimise the inventory carrying the cost for the production cycle.
In order to calculate your EOQ, you’ll need data for your annual product demand, fixed costs, and annual carrying cost per unit for your inventory. Your fixed costs are the amount spent in procuring the stocks, insurance, inspection and other process expenditures. Whereas carrying cost is the amount spent on product storage and utilities.
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Understanding your past year’s trend on the expenditure of your product procurement and maintenance will help you to calculate the EOQ metrics properly.
Once we understand the metric values needed for forecasting calculation, lets now talk about what are the forecasting methods and techniques for a successful business model.
Forecasting methods and techniques
There are many models and techniques for inventory forecasting. Some of are discussed below:
- Qualitative forecasting:
AccountingTools.com defines qualitative demand forecasting as follows: “Qualitative forecasting is an estimation methodology that uses expert judgment, rather than numerical analysis. This type of forecasting relies upon the knowledge of highly experienced employees and consultants to provide insights into future outcomes.”
Unlike the quantitative approach, rather than using historical data alone for forecasting trends,qualitative forecasting uses various current factors that will impact future demand.
“Many retailers and brands adjust stock levels and orders based on the previous year’s output and sales,” says Marc Gingras, CEO of Foko Retail. “They often focus on data that’s readily apparent while ignoring what’s less quantifiable. That’s fine if you’re a small-to-mid-sized retailers just trying to stay afloat, but not if you want to be the next big name in retail.”
Hence understanding your current trends and having a specialised team of forecasting trends experts will take your business to new heights of success.
- Time series analysis:
The time series demand forecasting is very similar to the quantitative approach. Towards Data Science says, “Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.”
“Data cannot be ignored.” – Marc Gingras, CEO, Foko Retail
Gingras adds – “Retailers should use an analytical approach, examining sales channels, suppliers and the demand placed on both, to accurately predict inventory needs.”
Hence, time series gives us an understanding of our product demand trends based on our previous collected data.
Causal forecasting is about understanding different variable or events related to your product demand cycle. The weather is a very critical example of causal forecasting. According to BusinessDictionary.com, causal forecasting definition is: “Estimating techniques based on the assumption that the variable to be forecast (dependent variable) has a cause-and-effect relationship with one or more other (independent) variables.”
Examining causal relationships helps in forecasting your product demand more accurately because you can predict and account for external factors that can affect your product demands. For example : if a branded product is on sale, other brands will have a decrease in their sales which is an external factor for those products, yet very important in their demand supply chain.
Simulation forecasting is the approach where all the above methods are mixed together. In this method of forecasting, both qualitative and quantitative insights are taken into consideration to provide a more holistic outlook.
However, because of its complicated nature, this forecasting technique is considered to be a complex way of understanding your product forecasting . Simulation forecasting also considers the external(causal forecasting) and internal factors while forecasting a product demand cycle.
Things to consider in inventory forecasting:-
- Establish a baseline for data
Understanding your product data is very important while doing demand forecasting.
“The simplest way to build a forecast is to pull in sales from the year prior and then factor in the growth rate for your business year to date to get a baseline of what to expect,” says Joanna Keating, head of marketing and e-commerce at United By Blue, which operates three brick-and-mortar locations in New York and Philadelphia. “It also helps to plan your sales by the day, which allows you to react quickly if something doesn’t meet your expectations.”
- Understand your customer and local market
“To effectively forecast demand, it’s most important to understand your customer well and their shopping tendencies,” says Castelán. Some questions to ask:
- Do my customers shop seasonally or is it consistent year round?
- What sizes and/or colors do my customers prefer?
- Are shoppers partial to certain brands?
- What do shoppers in my local area like?
- How quickly do trends catch on with consumers in my store’s area?
- Analyze your KPIs
“One of the key metrics of the forecasting process is sell-through rate, which is the percentage of non-clearance items that you will sell in relation to on-hand product for a given time period,” says Castelán.
“To identify the right sell-through rate and forecast demand, retailers often work collaboratively with suppliers to forecast demand (and their purchases) based on market information they might have along with promotional plans,” he says. “Work with suppliers to develop contingency plans [if your predictions are inaccurate].”
- Remember external factors
Causal forecasting plays a very important role in retail business model. “A big challenge is unknown events,” says Abby Perkins, director of content and communications at Glew.io. “You can have an accurate forecast that gets totally thrown off by something like a viral event in your industry, a related product launch or innovation, or even a weather event. Being nimble and able to adapt to unknown events is key.” That’s where the contingency plans come into play. Be prepared for the “If X happens, then Y product will be in demand” scenario.
Monitoring inventory levels is a big help in inventory control for the business. Regular auditing and monitoring of your inventory ensures that you never run out of popular items, as well as help you to understand the trends and demands for the current stocks in hand.
A good way to manage your inventory is to have an efficient inventory management system like SalesBabuCRM, that helps you to monitor and forecast your inventory requirement and make futuristic plans for profitable business revenue.
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