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Let’s have a look at this graph which is a typical supply chain management lifecycle curve. This graph explains the inventory management system cycle for SKU ID 100324. After we consider various factors affecting inventory levels for the SKU across geographical locations, competition, feedback, promotions, Supplier time, etc they reach four critical numbers.
- Maximum Stock Level:
This is the optimum stock level for the particular SKU. In this case, it is 100.
- Reorder Point:
At this stock level, a new purchase order is generated. This number is arrived after considering the time taken by the supplier to deliver the goods in the warehouse. Here the reordering point is 42.
- Low Stock Warning Level:
This level is the warning level for the SKU going out of stock. In this case, it is 15.
- Restocking Level:
This is the level after the reordered quantity is delivered in the warehouse. In this case, the number is 90.
Now imagine doing this for all the SKUs in your catalog. In a supply chain, the above graph poses some difficult questions. The biggest dilemma that an organization faces is related to the inventory levels for its products.
Every merchandiser wonders about these questions:
How much should I order/manufacture?
When I should start the reordering process?
Inventory forecasting is the process adopted to efficiently answer these challenges.
What Is Inventory Forecasting:
Inventory estimation (forecasting) may be defined as a process of predicting inventory in future time periods. More specifically inventory forecasting is a scientific approach of predicting sales during a specified future period based on the proposed marketing plan and a set of uncontrollable and competitive forces.
All this may sound very difficult. But this becomes really straightforward if you implement the right solution. Below I will show you an example of the same.
Factors affecting inventory
There are several internal and external factors affecting sales of an organization:
- Seasonality of inventory
- Technological failures
- Labor issues
- Supply chain related factors
- Change in government laws
How to use Inventory Forecasting Software To Predict Demand Accurately
Forecasting inventory will ultimately determine the fate of your retail business as it’s a big factor in profitability figures. Any system used, needs to consider purchase or sales made in the previous month; previous season or any custom duration depending on the upcoming time period.
To illustrate this better we are going to use the examples of EasyEcom’s Inventory Forecasting software.
EasyEcom software helps to overcome hurdles involved with calculating the sales and planning inventory with ease. It helps you to plan future sales based on your previous history.
Let us look at scenarios where EasyEcom can be helpful:
Inventory Forecasting Scenarios:
Inventory planning based on previous month sale
In order to plan your inventory for next month based on previous month sale, you need to provide the number of days you want to plan the inventory for (in this case, 30 days) along with the range of days you want the inventory planning to be done based on (in this case, previous 30 days).
To be specific with a particular product or vendor, you can further apply a filter based on the brand name, SKU or vendor name.
The system will then provide you with the suggested quantities to fill your inventory with, based on the previous month average daily sale. The suggested quantity also calculates the time taken by the vendor to deliver the products.
Inventory planning based on previous season sale
Similarly, the system will provide you with the suggested quantities to plan on upcoming Christmas holidays, based on the sales made during last Christmas. For this, select the number of days you need to plan for (in this case, 60 for December and January month) and date range based on previous year custom month, December and January.
With that being done, you also have to look after the fresh stocks currently available and are moving out faster. For Christmas season inventory planning, applying a few additional factors (for holiday rush) on fresh stocks can help you avoid losing new/existing customers.
Iterative Inventory Forecasting
So, when it comes to forecasting, a lot of uncertainty is involved in any organization. In order to reduce the adverse effect of these uncertainties, an organization can take an iterative approach towards determining the inventory projected in the future.
For example, a subscription-based web business ought to be able to project website views based on its organic search placement, paid advertising, email marketing, and other alliances & promotions. Make a projection of traffic by summing up your sources, then estimate the conversion rates, and that gives you unit sales.
Now as time moves on, we need to make changes in the assumption. For example, if we predicted 10% month over month growth rate by spending $5000 per month on advertising. However, due to budget cuts, the company can only spend $3000. That will cut down the traffic by 40%.
Similarly if suddenly a competition decides to discontinue their services, suddenly the conversion rate might shoot up by 30-40% hence boosting the inventory demand. Generally quarterly or monthly revisions in predicting mechanism are recommended. This depends on the nature of the company products and time required for a feedback cycle to complete for that particular assumption.
Advantages of Inventory Forecasting:
- Happy Customers:
When a customer gets the product without a delay, they tend to trust you more for their needs. This helps in repeat purchases and loyal customer base. Consider a scenario where the customer would require a product on a regular basis which, if not procured on time may affect his business. If he is able to purchase the product and get this delivered on time, he will be a loyal customer for life.
- Reduced Stockouts:
This is one of the most talked about yet common issues among retailers for sales loss reasons. Factors need to continuously optimized to get a better estimate trend. An accurate forecasting method not only ensures lower inventory idle time in the warehouse but also the less operational cost is required.
- Efficient Production Cycle:
Forecasting involves closely monitoring present inventory to understand the future. Responding to and adapting to the changes or pattern of consumption by the consumers gives a better idea of how the future is going to be.
- Lowering Safety Stock:
When your inventory forecasting process is accurate, it increases your reorder capacity and thereby reducing the safety stock level to free up capital. If a business is using proper forecasting to plan then you don’t need to carry high safety stocks to manage your inventory.
- Reduced Idle Stock:
Obsolete inventory is a big burden on the margin of any business. To reduce the burden, it’s very essential to identify, repurpose or removal of obsolete inventory. It decreases the volume of inventory on hand and subsequently both direct and indirect costs of keeping the obsolete inventory will be reduced. Having a reliable forecasting inventory method will reduce ordering any excess stock and increases net profitability.
- Managing Manpower Better:
When a business suddenly starts to grow, manpower requirement is also increased to handle the operations. So an inventory forecasting report helps the organization be better prepared for a sudden growth in future inventory with a proper manpower planning in place. For example in the case of a subscription business, if the inventory is going to shoot up in few weeks’ time, the recruitment effort has to start immediately in order to be able to fulfill the inventory.
- Better Pricing and Promotion Strategy:
With a better co-ordinated and planned promotion strategy always yields better results. With integrated distributor-level promotions and related forecasts helps to improve the flow of goods. It also achieves better results in terms of availability and stock fill rates.
- Better Supplier Negotiation:
When you know exactly when and how much you are required to order; the negotiation becomes easier for you. The supplier is also aware of the kind of business he can expect from you and hence gives you a better price. By having a negotiation based on logic and research you are positioning yourself as a credible customer who wants to have a long-term relationship rather than one-off spot buy.
- Plan Sales Strategies:
Forecasting is very helpful with Product Management, Marketing and Product Design planning. Decisions on promotions, pricing and purchasing are made with data derived from inventory forecasting. This has a positive impact on the sales and profit margin.
Benefits of using Inventory Forecasting with software like EasyEcom:
- With inventory aging report, we can identify stale inventory. End of season sales offers can be created for such inventory to free up the working capital
- Plan inventory based on multiple sales channels and offline sale combined together
- Flexibility in planning inventory based on different time frames (sales velocity during holidays vs regular time)
- Receive automated alerts at inventory reorder point
- Ability to accept backorders in case demand goes over the board. New purchase orders can be created for respective vendors for the backorders.
How to Measure Inventory Forecasting:
When you have data available, anything can be measured but to accurately forecast inventory, the focus should be on those data points which are relevant. Before we jump into how to do inventory forecasting, we need to consider a few crucial points.
A Forecast Accuracy Metric That Is Objective, Quantitative, And Manageable.
Deciding what to forecast?
Level of aggregation: Individual products or product groups? Weekly, monthly, or quarterly inventory? Units of measurement: units or dollars?
Determine How Often It Should Be Measured
Feedback cycles of each assumption used in forecasting
But one thing the management needs to understand that no matter how sophisticated the forecasting techniques you use, forecasts will never be 100% as it involves factors that are not controlled by you and a lot of uncertainty involved in it.
Techniques Used To Measure:
While forecasting inventory, there will be two sets of products. First is for the products that has stable inventory and has past data available. It can be forecasted more accurately. The second type of products are items that are new, low volume and innovative products. It is very hard to predict an accurate forecast with considerable uncertainty involved. And to make the problem more complex, there are zero historical data and some assumptions have to be made to calculate inventory.
The techniques used can be broadly divided into 4 different categories.
- Trend forecasting:
These are forecasting methods. When a particular type of upward or downward trend for a particular product is involved, this method is used for forecasting. The double exponential smoothing, regression, triple smoothing etc are few techniques popular in this category.
- Graphical forecasting:
When you have data and you convert them into a graphical representation, it conveys the pattern visually. Visual representation of data is easier to comprehend. This technique can give you a general trend without getting too much into understanding the data. Previous inventory exploration, trends and patterns help you forecast easily.
- Qualitative forecasting
When historical data is unavailable or irrelevant or are scarce, the forecasting is done based on an intuitive or judgmental evaluation. When a new product or a new innovation is launched, this scenario arises. Some typical qualitative techniques are based on personal insight, sales force feedback, panel consensus, market research, visionary forecasting, and the Delphi method.
- Quantitative forecasting
When a historical inventory data is used to project future inventory, it becomes more accurate and relevant. The available data and the other relevant factors are taken into account while forecasting the future inventory in these methods. The popular methods adopted by organizations are the Extrinsic and intrinsic techniques, time series forecasting methods, exponential smoothing (relying on past data) supplemented by qualitative judgements.
Inventory Forecasting Methods
- Delphi Method:
This method is widely used to predict the future demand when historical data is not available. Moderator sends the questionnaire to each expert and prepares a statistical summary based on their answers. The summary report is shared with the panel again to further modify their responses. This process continues till a common consensus is achieved.
- Time Series Method:
As the name suggests, past sales data is used to predict future demand.
- Exponential Smoothing:
In this method also past data is used to forecast inventory. However, recent sales data are given more weightage while forecasting. For example, if you are using past data of last 2 years (2020 and 2021). Previous year data will be given more weightage the data of 2020. This further improves the accuracy of inventory forecasts.
- Trend Analysis:
Trend analysis evaluates whether a product has growing demand or decreasing demand. In case of increasing product demand, you can forecast to purchase a higher volume of units. Similarly, in case of decreasing demand you can decide to purchase less units of the product.
- Market Research:
This method is generally used when historical sales data is not available. Customer surveys and questionnaires are used to predict demand, and in turn, inventory forecasts.
Inventory Forecasting Best Practices:
Keeping a few very crucial points in mind while calculating inventory forecasting gives maximum output.
- Get input from various stakeholders. Take input from Sales, Marketing, and Finance.
- Competitors sales data
- POS data
- Amount of obsolete stock
- Frequency of stockouts
- Measure Forecast Accuracy at the SKU, Location, and Customer Planning Level
- Adjustments Based on Feedback of Current Cycle & Focus on exceptions
- Talk with customers
- Review the data for trends
It is always very beneficial to have a great inventory forecasting team who work on a regular interval to understand the trend and derive accurate inventory forecasting method.
It is important to understand what kind of data is more important with respect to forecast accuracy. Is it the external data like competitor sales, POS data, sales team forecast or the internal data like stock-outs, shipments, orders, etc?
Apart from this, it is also important to determine which time buckets are most suitable for forecasting. For example, whether to use monthly time buckets or weekly time buckets for planning. All these factors changes from organization to organization.
Nobody can predict 100% accurate inventory forecasting every time. It is very essential to understand this and review the past forecast, learn from the trends and improve the accuracy.
Are you looking for an omnichannel inventory management solution with integrated B2B order management for your eCommerce business? Drop us a line at email@example.com or directly sign up for a demo here.