In a recent newsletter, IAMCA reached out to ask our readers for their ‘go to’ sources of statistical information. Shortly thereafter, this new challenge to the dairy markets occurred.
Speaking for our New York market only, our processors and manufacturers were impacted quickly, and in unique ways.
Seemingly overnight, the market for consumer fluid products from retail groceries dramatically increased. There were many instances where milk was not to be found and stores began limiting purchases so that all consumers could obtain at least some milk and dairy products. This was followed by a period where the supply chain started to recover from this initial sky-high demand to more normal (or even reduced) demand. Store shelved were restocked (perhaps on an uneven basis) and the flow of product could not readjust as quickly. We started to see stores with no more capacity to hold milk and they began to reduce orders.
At the same time, food service and institutional sales, especially for cheese and similar products slowed.
Companies that had the luxury and capacity to shift production from these food service outlets to retail outlets were in an enviable position. Their net production may have actually increased. Unfortunately, this was not always the case.
Now here is the difficult part. Government leaders are trying to understand the various roadblocks to the efficient flow of products statewide. Why was there a period that the milk was unable to keep up with demand, then apparently exceeded demand? Was it simply a function of panic buying followed by consumers finding that they then had enough to get by for a while? How do we know for sure? Where is the data to prove this is real? What else is going on that needs to be addressed?
In New York, we obtain a significant about of data from our dairy industry through required reports from cooperatives, processors, manufacturers and other participants in the dairy industry. These monthly reports are submitted about 20 days after the end of each month. After that, due to staffing and technology limitations, it can be some months until this data is manually inputted into a database for analysis. Given the highly dynamic changes this industry is experiencing, and the policy makers’ need for information, this process is severely lacking.
While we continue to try to support the data needs of our policy makers, it may be that the coming months will provide a treasure of data to analyze this situation after the fact. We can debate the causes and impacts and assess if the solutions applied helped or were of not consequence. Sounds like a great topic for identifying opportunities to improve data collection and analysis and debate implemented solutions and their impact. Are we ready to take this challenge on?