It’s springtime and many of our customers are at or approaching peak shipping. Now is the time that the results direction for the year start to take on some form.

It’s at this time of year, with the proper analytical view, you can start to see if you are behind, ahead or what your situation will be.

• Are you ahead of last year? How do you know?
• Are you behind where you thought you would be? How do you know? Do you know the causes?
• How is your plan variance?
• What statistics, metrics and analytics are you missing to get the real picture of your business?
• Are you profitable?

It’s also the time of year that without some analytical views of your business, you are flying blind as it were.

It’s also time to assess your forecasting methods and plan and decide on changes to improve it.

As part of that assessment, it’s important to understand your key data needs.

Below are 4 areas of important data that growers need to have available.

Item and SKU data

It goes without saying that the items you produce and sell and the associated other information like size, color, or category are the starting point for a forecasting data build.

Growers should be able to “slice and dice” their results and plans by other aggregating factors such as category, size, or other factors relevant to the business.

Make sure your item set has the relevant factors linked to the item so that you can do aggregate statistics for a variety of aspects.

Historical Sales Trends

As my colleague Ken Lane says, “The trend is your friend”.

Thus, any forecast effort must include historical sales. Typically for high level forecasting, this is a yearly result by SKU or item, with quantity and sales dollars. Usually, 3 years of history is sufficient. However, due to the extreme swings related to the pandemic and large-scale weather effects of recent years, sometimes we want to look at pre-pandemic sales as an alternate baseline as well.

Selling Prices

Make sure for your projections you have your selling prices.

Many growers have multiple price levels on an item depending on customer volume or loyalty.

Make sure that for your pricing you use the accurate weighted average to represent the correct expected revenue for forecast sales volume.

If you use catalog price only you risk overstating predicted revenue.

Demand Factors

Demand factors come in many forms.

Picking up a large new customer or starting a new program with an existing customer will change demand. Introducing your products to a new shipping area or a new sales modality can also affect future demand.

Geographic factors such as housing starts, population movements, past weather events (such as the “Wintermageddon” Freeze of ’21), and the like can all yield amplification or attenuation of demand for your products.

Each one of these should be considered by your team and they should adjust the demand forecast for your affected products you grow.

Just the data requirements can be daunting and the ability to perform the analysis in Excel (or similar tools) takes some knowledge, time, and practice.

If you want to learn more about the theory, mechanics, and tools of Forecasting, check out the class that Ken Lane and I are teaching a class at Cultivate ’24 in July. Signup for Cultivate ’24 Forecasting Workshop today!!

Learn more here.