Two Brief Lessons for Agri-Input Retailing from Amazon Prime

Editor’s note: This article was originally published on LinkedIn.

Let me start with a trivia question. Can you guess the original name proposed by the founding team which built Amazon Prime?

It is a tough one, but I am sure, you can work your way through, if you have well-honed quizzing muscles.

Here’s the answer: “Super Saver Platinum”.

Obviously, Jeff Bezos rejected this name, when the team proposed it. He didn’t want consumers to see it as a money-saver program. In fact, he wanted people to order more. One Amazon Board Member apparently came up with the name ‘Prime’, and the rest, as clichés are wont to be, is history

I find this trivia from Brad Stone’s “The Everything Store: Jeff Bezos and the Age of Amazon” interesting for many reasons. Primary being, it gives me a glimmer of insight about the origin story of Amazon Prime.

Here’s the legend about Amazon Prime, for the uninitiated.

Early in their game, Amazon realizes that people hate paying for Shipping Fees. Amazon tries really hard to solve this problem. They launch Super Saver Shipping. There is one problem though. It makes you order less, makes you wait until your order qualifies for free shipping.

And one fine day, a software engineer named Charlie Ward puts the idea for Prime on “Ideas Tool” on the Amazon Internal company website. Jeff recognizes its brilliance, foregoes testing, and puts his entire weight behind to go for it.

Such is the stupendous success of Amazon Prime that it makes Jeff Bezos say things like this. Look what he said in 2016:

“Our goal with Amazon Prime, make no mistake, is to make sure that if you are not a Prime member, you are being irresponsible.”

Two years later, this is the gospel truth. You are irresponsible, if you are not a Prime member.

Such is the pull of Flat Rate Bias, the fundamental cognitive bias, which makes us suckers for subscription programs. It was first studied by a Marketing Professor named Joseph C. Nunes in the year 2000.

What is “Flat Rate Bias” anyway?

Have you paid close attention to how we humans evaluate and decide over a subscription option in our heads?

Instead of analyzing the history of our product/service consumption, we calculate the tipping point at which the subscription will break even and make sense, and then calculate the probability or likelihood of crossing it. Even if there is 1% chance of crossing the break even point, we end up buying the subscription.

All of this sounds great and in fact, romantic, if you start wearing the agribusiness lens. The hard question I am wrestling with is this: Can Agri-Input Retailing learn a lesson or two from Amazon Prime?

What would it take to design an Amazon prime-equivalent channel relationship program for Agri-Input Retailers? Would it help build deeper relationship with the customers of Agri-Input Retailers?

Do I hear you asking why focus on Agri-Input Retailers when you could directly focus on farmers?

In the eleven months I have spent in this sector, I have realized this. If you want to create maximal value in the agri-input ecosystem, you have to start with the key bottleneck first. I am speaking in the language of Theory of Constraints (which I assume you would be familiar with).

And, if you understand TOC, you would know that great power resides in the key bottleneck.

Now, if you go back in time to say, thirty years ago,in India, there were almost no agri-input companies who were dealing with retailers. Agri-input companies were only dealing with distributors.

And today, agri-input companies understand the power of agri-input retailing, and have built channel structures/systems which enable them to deal directly with retailers. Dhanuka Agritech and Adama come on top of mind, when I look at this trend.

Today, as the market share for the leading agri-input firms stagnates, the number of channels are steadily growing and farmers are becoming more open to brands, which are powerful enough to create strong word of mouth among farmers.

All of which is to say this: Now is a great time to push status quo and try out radical experiments in Agri-Input Retailing. Let’s dive straight into the lessons.

Lesson#1: Understand the Amazonian flywheel and build your own.

Amazon’s flywheel has now acquired legendary status. Here is how Brad stone described its birth in “The Everything Store” during one Amazon offsite in 2001:

“Bezos and his lieutenants sketched their own virtuous cycle, which they believe powered their business. It went something like this: Lower prices led to more customer visits. More customers increased the volume of sales and attracted more commission-paying third party sellers to the site. That allowed Amazon to get more out of fixed costs like the fulfillment centers and the servers they needed to run the website. This greater efficiency then enabled it to lower prices further. Feed any part of this flywheel… and it should accelerate the loop. Amazon executives were elated… after five years, they finally understood their business.”

As the industries we are contrasting are as different as chalk and cheese, let us contextualize the lessons carefully in an agribusiness context.

Today, almost every agri-input firm we meet in India wants to build direct relationship with farmers, and no matter how hard you try, you will have to understand the agri-input flywheel to do so.

Let me illustrate this through defining the primary sales, secondary sales and liquidation, from Factory to Warehouse to Distributor to Retailer to Farmer.

Here is how the agri-input flywheel works.

When traceability and Farmer CRM technologies become more than a buzz word in agri-input value chain, there is going to be a virtuous cycle in which when farmers are more aware of brands and willing to buy agri-inputs based on their relationship of trust with agri-input retailers; agri-input companies are able to invest towards deeper relationships with retailers through better demand fulfillment and inventory optimization strategies, and which in turn will lead to better margins through their ongoing relationship with distributors.

Here is a simplified, generic view of this virtuous cycle. (I sense this diagram would evolve further with more deeper nuance. Consider this a beta version, if you will).

Bear in mind, this is a broad view of the flywheel, and would need to be customized, depending on how your channel strategy plays out in the market..

That said, this flywheel holds promise because, if you think about it, if you feed any one part of the flywheel here, it accelerates the complete loop.

Fascinating isn’t it?

But, here is the thing. If you are starting afresh to build a positive, virtuous cycle of this kind, you have to start from building traceability across the entire customer spectrum spanning across Primary sales transactions ( Warehouse->Distributor), and then, secondary sales transactions ( Distributor – >Retailer), and finally with, tertiary sales transactions (Retailer->Farmer). It would be extremely difficult to reach the final stage, building direct relationships with farmers, without first building a strong relationship with the channel.

There are companies which are bucking this trend and are now striving to build direct relationships with farmers. I talked about Sumi Max Product last week and what lessons it holds.

Lesson #2: Accelerate your flywheel.

Now that you’ve built your flywheel, it is now important to understand the drivers which would accelerate this flywheel. Flywheel kicks in only when there is improved efficiency in operations. if you go back to history of Amazon, they could accomplish this by reinvesting all the profits they had into effective and efficient automated operations through technology.

See this graph from Ben Evan’s excellent post, and you will understand what I am talking about.

So far so good.

What efficiencies can be improved in agri-input retailing?

If you consider the everyday life of agri-input retailers, they struggle with:

  • Getting the right support from the agrochemical firms incase of product returns
  • Visibility into distributor pricing, especially when it changes for particular brands, after they’ve provided the same brands to farmers on credit
  • Product P&L Tracking: Product wise performance, considering purchasing costs, logistics and other costs.
    Order Tracking
  • Counterfeit protection.

For the flywheel to kick in, these inefficiencies need to be addressed through robust traceability systems.

Wear the hat of an agri-input retailer and an agri-input manufacturer. For efficient operations, it is important to have access to the following intelligence viz:

  • Channel Intelligence: How do I ensure that farmers receive original products, in a market with rampant counterfeit problems? How can I manage purchases, Sales, Inventory, Customers of Channel partners? How do I manage inventory and get notified of expiry, low stocks? How do I manage loyalty programs for retailers which can be run across geography, product and season dimensions?
  • Order Intelligence: What is my credit limit while ordering stocks? How can you help me manage my capital and credit better? Can I get an expected delivery date of goods?
  • Promotion Intelligence: Can I understand where this particular brand stands in its Product Life Cycle Curve in order to tap its peak potential before it comes under attack from generics? How can I maximize sales based on what provides real value to farmers.

As you can imagine, each of these intelligence domains is going to increase the efficiency by multi fold.

Can agri-input manufacturers look towards building deeper relationships with their retailers by providing them with superior channel partner experience and in turn building a more richer customer experience with farmers?

Can agri-input manufacturers design and run such channel relationship programs in such a manner that channel partners feel that they are irresponsible, if they are not part of it?

How do you see the flywheel in action, when the rubber hits the road? Do you see any challenges that I may have missed in running such programs for retailers?

Let’s talk.

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