Top 5 Tips to Manage Your Agriculture Supply-chain Data

Alright. Enough is enough. If you hear the term “data-driven” one more time your ears might fall off. It’s finally time to organize your database and figure out how to collect your data in a more strategic way. Well, hats off to you! It’s not a simple road, but when it comes to driving a food or beverage business, it’s the only one that doesn’t lead to a dead end of inefficiency.

Whether you are looking to leverage AI or Big Data or just get your payroll and cost of production sorted out, unscrambling your historical data and setting a clear strategy moving forward are the essential first steps. 

Over the past few years I’ve spent countless hours untangling spaghetti plates of data served to my company by food and beverage businesses. It seems that companies fall into the same bad habits of data collection no matter what they grow or process. Whether recorded in English or Spanish, growing peaches or processing tomatoes, from Australia to Brazil, the same mistakes play repeatedly like a bad 80s song on the radio. These bad practices carelessly toss away the countless hours and dollars invested in data collection.

So do your company a favor and follow these five rules. Future-you will thank you…and so will your boss.

#5: The devil is in the details.

I imagine your sock drawer is not much different from mine. There are always those coupled up socks that you unfold, ready to put on, only to find that they are simply not an identical pair. You are in this situation for one of two reasons: either the person who paired them together didn’t realize they were mismatched because they seemed so similar, or, they were fully aware that they came from two different sets but figured “what’s the difference? Its close enough!”

Whether the reason is “the supplier’s name seemed similar enough” or “I’m pretty sure those varieties are the same,” take the time to match properly. This “sock mishap” is extremely common in food and beverage business data, but unfortunately, wearing different socks for a day in data science is a fashion faux pas you will pay dearly for.

#4 Save the date

Data is the world’s best storyteller. However, like any good story, the order in which the events occur is vital to understanding the tale. I recently attempted to rebind one of my daughter’s favorite bedtime books only to find that there were no page numbers. This was a nearly impossible task – there was simply no way of knowing whether the princess rode her unicorn before or after meeting the prince. 

Obviously, recording information in your database is important, but without including a timestamp of what date that delivery occurred or when that sample was taken, there is no context for the event. When utilizing that data later, either that page of the story will be left out, or it will be stapled wherever you guess it might belong – which isn’t necessarily accurate.

#3 Don’t merge!

In a frustrating attempt to paint a birthday card for my wife one year, I found that the green tree, the blue water, and the yellow sun kept blending together into an abstract psychedelic mess that, although pretty cool, just did not capture that beautiful summer day the way I wanted it to. 

Following a process from beginning to end through data entry is not easy, but merging suppliers or fields together simply because it was challenging to track separately during harvest or production is a huge value inhibitor. Make the extra effort, keep the inputs separate from supply through production, and avoid combining individual items together along the way. 

#2 Everyone counts

Because of the multitude of information that is collected by food and beverage companies, oftentimes functions like averages and sums are used to make data more concise and user-friendly.

Although carrying around a 20-dollar bill as opposed to 2,000 pennies will undoubtedly do wonders for the longevity of your pockets, when it comes to generating value from data, having more granular and nuanced information is of unparalleled benefit. So, if you are thinking about just saving the average of the quality samples taken for your inventory, think again. Your cloud storage space can handle it.

#1 Consistency is king

No NBA player has made more free throws in their career than longtime Utah Jazz forward Karl Malone (9,787 to be exact). Whether in an inconsequential practice in Utah or in a championship game 7 in Chicago, Karl would whisper the same mantra to himself before each shot taken throughout his career.

In our innovative world, where techniques and technologies are constantly advancing, maintaining any form of consistency in business processes has become increasingly difficult. It is inevitable that your business will change the formats and systems into which you input data across the organization. The tools used today to measure quality, waste or efficiency will be adjusted or replaced several times during your career. Investing the time to translate and adapt these methods to ensure continuity between systems and practices will make all the difference.

It’s no secret that data is a headache and organizing it no short of a migraine. The following Shel Silverstein poem really sums up the feeling.

“What do I do? What do I do? This library book is 42 years overdue. I admit that it’s mine, but I can’t pay the fine-Should I turn it in or hide it again? What do I do? What do I do?”

But don’t worry, there’s good news. These rules, while helpful, are not a zero-sum game. Every time you make the extra effort to follow any one of these principals, you will find yourself and your company in a better place tomorrow. 

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