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...
The retail environment is more complex than it’s ever been, and the way people buy, what they buy, and how their orders are fulfilled is changing rapidly. Yet one area is mostly unchanged – how we manage retail. Should retail management reinvent itself by adopting the Agile practices of rapidly-scaling tech companies? And, if so, how can retailers make this shift quickly and painlessly?
Retail has driven down costs, but lost the silver service factor in the process.
Ever since WWII, U.S. retail has grown exponentially. First came the ever-expanding square footage and networks of stores, next came the massive increase in variety. Case in point: SKU numbers at the average supermarket increased ten-fold. Today, the latest battle lines are being drawn around the multiple ways people want to buy and be fulfilled.
This expansion in size, variety, and fulfillment has led to an ever more complex retail environment. Yet at the same time, there has also been a gradual deskilling of retail’s front-line, motivated by reducing costs, improving profitability, and increasing competitiveness. Veteran retail executives tell us that labor hours in stores today are down to a third of what they were 20 years ago, while Store Manager experience has reduced from 10-15 years, to straight out of college.
As retail businesses have grown bigger and bigger, the default approach to managing performance has been to add yet another report and load on another management layer or another department, rather than challenging the best way to manage retail and deliver value for the customer.
While some areas of retail have totally transformed, the way we measure and manage stores has barely changed.
Typically, store management has been made harder than it needs to be. The amount of real-time information can be overwhelming.
There are so many requisite reports it often resulted in both the store and central management to know which end was up. A massive disconnect came from strategy led by an isolated set of MBAs pushing management theory, while the field was actually living a different reality on the ground.
The beauty of retail is that it is built on enlightened trial and error. Continuous improvement is what keeps the customer delighted and willing to come back. But if you are always experimenting with the latest new thing, you never can be sure if you are focusing on the right things or following up to know whether what you had previously executed was working or not.
And from the frontlines, it’s no fun in always being told what to do without any input.
Technology companies have been the unquestionable US corporate success story of this modern digital era. Groups of companies that have grown rapidly using incredibly lean resources and young workforces bring tremendous value to the U.S. consumer.
Intrinsic to their success has been a specific Agile approach to management that has enabled tech businesses to grow exponentially as they have the flexibility to maximize success.
Agile product management takes an iterative approach — using small teams, working in short development cycles, and constantly prioritizing the deliverables that drive immediate and clear value to customers. Everything is measured, evaluated and the results used to inform subsequent cycles.
The diagram illustrates a high-level visualization of a typical management process versus an Agile management process. Both of these approaches involve setting goals and targets, taking action against those goals, and measuring variance to planned results. Yet there is one crucial difference: the feedback loop.
With Agile, you granularly measure the impact of each action and feed that intelligence into your learnings, reshaping the next set of targets and objectives. By its very nature, this continuous loop creates: