Amazon - redefining the 80:20 rule

The 80:20 rule is oft bandied around in the retail world and Amazon have taken an established business saying and turned it on its head...

Amazon - redefining the 80:20 rule

How do Amazon use it?

The 80:20 rule is oft bandied around in the retail world and Amazon, not content with disrupting numerous retail industries and the very way we shop have even taken an established business saying and turned it on its head.

Amazon uses the 80:20 rule to demonstrate their approach to product decision making - they base selections 80% on data and 20% on experience and gut feel, whereas traditionally decisions in retail are entirely the other way around, with 20% being based on data and 80% on gut feel.

No-one can argue that the 80:20 model isn’t working well for Amazon as the company announced a near doubling of their profits for the first quarter of 2019 as it continues its expansion into new categories by using the data they generate from selling 3d party products.

Amazon treats product selection in all categories - from electricals, fashion, garden equipment to pet supplies in the same way that it treats all decision making - focusing more on data over the human elements.

In new categories, the company utilises its marketplace offering to understand what works well and what doesn’t before analysing the data and then utilising their own inventory or creating their own products. Powered by Prime this approach can quickly mean that what was once a lucrative market for an Amazon marketplace seller can vanish overnight.

How do other retailers use it?

So, how do other retailers utilise the 80:20 rule in this manner to unlock growth and performance? Is it possible? Or is this Amazon innovation untouchable by others?

Some of the biggest (and most successful) names in fashion retail at present; think Zara, Boohoo and PLT have created their own data led models to determine what to stock and in what quantities. Their approach is based on stocking small initial volumes of product and using the data this generates to optimise future buys. This approach works when you’re able to position your supply chain to support it but for many, this is a task that is out of their reach.

One of the main shifts is that for traditional fashion retailers, data used is historical data which is heavily skewed by merchandising and marketing positioning - for example, showing as a false positive if an item has been heavily marketed or discounted as a loss leader - both actions drive spikes in sales which mask the true appeal of the product.

Whereas Amazon and fast fashion innovators Zara and Boohoo use real-time, non manipulated, customer-centric data to inform their stock decision. These businesses were built with a focus on data but how can a more traditional fashion retailer emulate these new entrants successes and move from a 20:80 approach to an 80:20 data model?

For many retailers now there is a gold rush to utilise data in a similar way and create their own approach to the 80:20 rule. The first decision companies need to make is to decide if they’re focusing on their own data sources or bringing others into the mix?

Owned data sources enable companies to look at the data they already have within their organisations currently and use this insight to help them make informed decisions. The challenge is knowing how to extract the most meaningful data from legacy systems and then having the time and resources to analyse and embed it in decision making. In many of my conversations with retailers, they often focus on the data they’ve got, but are so often unable to really harness it.

A solutions based approach

Companies from IBM to Tableau are now providing solutions to help companies turn this data into insights across many sectors. In hospitality hotel chains such as Marriott have combined weather and local event data to forecast demand and determine a value for every individual hotel room - allowing them to optimise its setting of prices and improve profitability.

That’s why so many retailers are now working with external providers to either generate data for them or unlock the data they have internally to create actionable insights to improve performance.

An example of this is Manchester based PEAK who has created a powerful AI platform that helps retailers understand performance based on their own data insights and work with a range of leading names.

With moving to an 80:20 strategy many companies have to change their people strategy as well, turning traditional buyers and merchandisers into hybrid data scientists. Marks and Spencer’s announced last year that it was setting up a data academy to train 1000 staff members on data science courses to enable just this change.

Amazon has changed the game with their approach to utilising data in the product decision-making process, many new retail success stories are now built on a version of their core principles and many traditional retailers are now rushing to catch up.

This post was originally published on Forbes on 27/5/19


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Tags: Fashion, Data, Retail

Cally Russell

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