During the peak shipping season of springtime, the direction of your business is likely starting to take shape. This allows growers to use collected data to forecast a view throughout the rest of the year and determine where they are and where they want to be. For instance, this analytical view of the situation can determine if you’re behind or ahead of key metrics compared to the previous year, as well as map out and answer important queries, including those related to plan variance and profitability.
Additionally, past the initial overview and forecast of your business’ position relative to the market and past annual and monthly performances, this data can allow you to create a plan that allows for changes geared toward improvement. However, in order to do so, you need to properly collect and identify the pieces of data that are crucial to building and implementing your plan. From Advanced Grower Solutions, here’s a look at four important data areas that growers should keep in mind when planning for their future forecast.
1. Demand Factors
Demand factors, or factors affecting demand, come in various forms, including:
- Economic factors (customer budget/income changes, change in product price)
- Geographic factors (extreme weather events, housing starts, population movements, etc.)
- New competitors
- New customers
- New programs
- Tastes and preferences in the market
These factors and more should be considered by your team when setting and adjusting your business forecast. Most importantly, determine whether or not these factors affect the demand for your product and (if so) by how much.
2. Historical Sales Trends
Any forecast or making expectations for the future must also consider the past. That primarily includes the trends of historical sales data your business has at its disposal. Depending on your system, this should be documented by SKU (stocking keeping unit) or item concerning quantity (amount sold) and sales price per unit.
AGS usually recommends a history of three years be taken into account for forecasting. However, caution should be taken when integrating data from during the onset of the coronavirus (COVID-19) pandemic due to extreme swings in the market, as well as instability relating to extreme and large-scale weather events. Due to these heavily affecting a baseline, pre-pandemic sales data should be considered as well.
3. Item and SKU Data
The items in your catalog (along with their details of category, color, size, etc.) should be used as a starting point for constructing a forecast from data collection. Additionally, items can be grouped by category, size, and other factors relevant to your business for easy organization and comparison of data aggregation.
4. Selling Prices
In addition to item and SKU data, your forecast predictions/projections should integrate the selling prices of your products. However, due to many growers having multiple price levels and tiers based on customer loyalty, relationship, and volume, this can be tricky to coordinate.
AGS recommends for pricing that “you use the accurate weighted average to represent the correct expected revenue for forecast sales volume.” Relying solely on catalog pricing can run your business the risk of overstating/overestimating predicted revenue.
