In late 2008, four students set out to change an industry. All of them, over a few drinks, lamented at the cost to replace their respective eyewear. One had been wearing the same damaged pair for over 5 years, held together with paper clips. He just could not afford new ones.
At the time, Luxoticca was the 800-pound gorilla of the industry, having more than 80% of the market. Having watched Zappos transform shoe sales by selling them online, they wondered if they could do the same.
Despite all the experts and friends telling them how stupid their idea was, they forged ahead. They would end up selling eyeglasses that normally cost $500+ in a store, online for only $95, while donating a pair to someone in the developing world with every purchase.
In late February 2010, their fully functioning website went online. The company was named Warby Parker, based on the names of two characters by the novelist Jack Kerouac. They loved Kerouac with his rebellious spirit and infused it into their company culture.
Warby Parker was a hit. Sales soared. And, in 2015, Fast Company named them the world’s most innovative company.
Now, it’s easy to say that all these guys did was sell eyewear online, utilizing a model that’s been successful in several other product lines. But they did much more than that.
They challenged the default thinking.
Almost every business model, or business process/approach has, embedded in it, default thinking. That’s the thinking that has been cemented, over time, to be essentially a given. So much so, that it’s the default – the norm.
For eyewear, the default thinking was that they were expensive and needed to be purchased in a store, since people like to touch and feel them.
Warby Parker challenged this thinking and changed the model for millions of customers.
In supply chain planning, default thinking manifests itself in a few areas – arguably the most damning is in demand planning.
The default thinking in demand planning is one of complexity, with lots of variables to be considered and numerous forecasting algorithms and models used by different classifications of products. But wait, argue the complicators, “the system will automatically pick the best algorithm and voila, you’re golden”. We’ve all seen this movie before, haven’t we? People are accountable for demand planning and complexity that they don’t understand, is not used, or worse, worked around.
Most of the default thinking regarding complexity arose from the fact that for decades we’ve been looking at the supply chain from the wrong lens. With our faces pointed at the supplier/manufacturer and our asses pointed towards the customer, we’ve built default thinking that to properly plan demand, we’ve got to factor in loads of variables.
And to be fair, that’s somewhat true if you are considering the demand plan at the manufacturer.
But what if you pointed your ass in the other direction, turned around, and looked squarely at the customer?
You’d be planning for consumer demand – a demand stream that’s pure, has more clarity and is not polluted like DC and plant demand.
A simpler and more uniform approach could be used to predict store level consumer demand. And once predicted, all other demands could be calculated throughout the supply chain with alarming clarity.
All you need to do is change your default thinking.
And point your ass in the right direction.