The Top 10 ways AI can improve Retail Store Operations.
The Top 10 AI use cases that Retail Operators at every level told us would transform their daily work. AI for Retail Operations is...
Many businesses pride themselves as cutting-edge or market-leading, but when you look at their management strategy, it doesn’t take too long to discover that their core is one of the most outdated parts of the company. In an unexpected twist, answering how organizations should be shaping themselves up to dominate the future actually requires us to jump back 400 years.
In 1620, Francis Bacon (the British philosopher, not the painter) published a book called the New Method – although back then called by its Latin Name, Novum Organum.
The book is one of the most important foundations of modern scientific inquiry.
It was one of the greatest works in a pivotal point for mankind: The Age of Enlightenment. It typified a transition in the West from relying on ancient thought from Greek philosophers like Aristotle, to questioning all knowledge through logic, reason, and the evidence of their own senses.
Bacon introduced a concept now called Empiricism. This posited that you understand the world by observing and accumulating data whilst interacting with it, continuously updating your understanding of what is happening with each new outcome. Learning occurs by doing things and observing the consequences of those actions. This was at odds with a group called the Rationalists, who believed that knowledge is innate and governed by constant deducible laws.
Empiricism became a central tenet to the scientific method. Through this, we improved our understanding of the world and triggered scientific and industrial revolutions. Modern growth is built on its principles.
But enough of the philosophy and history lesson – why do I think Bacon’s ideas and that of later empiricists are core to business?
You’ll probably have heard of “agile”, and also “lean six sigma”. If you have a degree in management, you’ve may have even heard of Japanese Kaizen, or Taylorism.
Management theorists and business practitioners talk about these approaches as though they were different religions. But much like Ibrahimic faiths having the same God, management theories all descend from the same grounding in Empiricism.
That’s because the most effective way of improving, no matter which way you package it, has the same four fundamental components of scientific enquiry:
This simple method is how humanity has come closer to truths that improve their own learning of the world and guide decisions on optimizing themselves and the world they create. You would imagine, therefore, that this has been effectively adopted by businesses to drive forward their own growth and progress.
The reality is most don’t, and it’s only getting worse. Today the average lifespan of an S&P 500 company is less than 20 years, down from 61 years in 1958.
There are companies that do practice this cycling of innovation and iteration, and they are typically the highest growing tech companies out there. How have they made it work?
“How can we be more agile?”
This is the common refrain of the corporate boardroom witnessing competitors thieving their market share, or the confusing arrival of disruptors. The demand to be more agile without understanding how demonstrates that empiricism just isn’t part of their day to day mentality. When it is, agility is an emergent property of the organization, rather than an already-too-late goal.
“We work on agile principles.”
Speak to any successful technology company and you’ll see empiricism in everything they do. From marketing and sales, right down to product and development, constant iteration and learning of how to improve is ingrained into the mindset of how these people think and act every day.
“Most corporate decisions are made on the back of napkins, and on the gut of the most important person in the room.”
This was a statement made to me by an executive at one of the world’s largest companies.
In top tech firms, product teams have labeled the tendency for a prominent individual to drive agendas through opinion. They call these people HiPPOs – “highest paid person’s opinion” – and they’re analogous to pseudoscience.
Whilst senior opinions can be great for generating test hypotheses, it’s the user testing processes and structured measured data that give them validity. Whilst experience and talent can still set the direction, unbiased and objective processes help to ensure the most optimal decisions triumph. Moreover, with HiPPOs’ whims and ideas subject to the same scrutiny process as everyone else’s, teams feel emboldened to offer their own views and suggestions, ensuring that emerging talent is unleashed rather than downtrodden.
Most companies are good at setting a hypothesis, like planning to execute a project or campaign because they expect it will drive a certain business objective forward. Most companies are able to highlight the KPIs they’re looking at to improve performance.
They aren’t so good, however, at structuring interventions to test these hypotheses. The most rigorous way to do this is to granularly track the impact of the intervention on the expected outcome versus a control group.
For example, if I think more effective training will reduce my BOPIS time fulfillment, I should test it in a few stores first and compare the impact with stores that have remained the same. For this to be a valid comparison, the ability to benchmark peers in a data set but control for confounding variables in size, location, format etc., is invaluable. If your hypothesis looks to be validated by this early test, you are then able to roll it out to a much wider group, to continue testing and refining the hypotheses you hold.
As well as needing to control for variance in the data, there also needs to be a high-level of granularity to avoid “noise”, in order to understand more about the causation behind a correlation.
Companies struggle to do this for four main reasons :
Top tech companies, build in robust ways to test, measure, and learn through aligning objectives, actions, and their data all together.
The rate of change was rapid for businesses even before Covid, which has now turbocharged it. There is only one solution for companies to adapt, protect, and survive their way through this new environment: Empiricism.
It’s said that all companies are now tech companies, and so operating in archaic ways is fundamentally incompatible with an organization’s growth aspirations. Although most companies are talking about digital transformation and a great acceleration of new digital trends, they still lack the scientific mindset of testing, measuring, and learning from every action.