For the past few years, the on-demand nature of the modern customer has been pushing retailers into a new era of data-driven, iterative decision making. As with nearly every other facet of digital transformation, COVID-19 has accelerated the need for decision making at every level of retail — product development, factory, key account coordination, inventory planning, order delivery, in-store data, etc. — to get up to speed.
Marketing and e-commerce have been going through this evolution for years. But it's time for faster, data-backed decisions at every step of the retail value chain, not just the end customer experience (CX).
Product and merchandising teams need to rethink their current assortment development process — which often stretches between 12 months and 24 months today — to be agile and responsive to the changing market. This idea is integral to making sure that supply chain and sales teams can meet the needs of increasingly on-demand consumer purchase decisions. However, too many retail brands and other merchandising-based companies currently lack the tools. In fact, our company’s research found that brands bet 4.5 times more on inventory than in marketing, but spend four times less on technology to support those investments.
Merchandising Needs a Tool Kit
To understand the urgent need for agility in the retail decision-making ecosystem, it's important to know about the existing status quo and systemic vulnerabilities. Product development processes are beholden to dozens of teams scattered all over the world, outsized spreadsheets, 100-plus email threads, and annotated PDFs to keep everyone aligned. For decades, in-person meetings have been integral to the decision-making process, especially when it comes to product line reviews.
Teams are also highly siloed, with each group operating largely in a vacuum for extended periods of time before reconvening for short-but-intense periods of feedback, deliberation and honing. Collaborators spend weeks and sometimes months sitting on the sideline, instead of iteratively participating in line development. The infrequent and "bursty" nature of this form of collaboration often leads to crunched decision making where hasty compromises are made based off of imperfect data, factory deadlines and internal politics.
Brands can't move fast enough, and it's no wonder that retailers are wasting $1 trillion a year on products that consumers don't want. Worse, there are over 21 billion pounds of clothing sent to U.S. landfills each year. Today’s cumbersome processes hurt industry players’ return on investment and pass the buck to future generations to clean up the wasteful mess.
Due to shelter-in-place orders, COVID-19 has upended "business as usual" and gives brands an unexpected chance to deconstruct and reinvent decades-old workflow processes. To do this, teams across organizations must be empowered to collaborate digitally on product lines and assortments — including 3D samples — and easily access the data they need for efficient, consumer-driven decisions.
Winning brands are the ones we see successfully pivoting to these more advanced workflows. For instance, Target Chairman and CEO Brian Cornell recently told WWD that his brand “is putting a premium on being really responsive, being real agile. We're taking a much shorter-term horizon as we are thinking about the business.” And Hoka One One has successfully shifted its product development process to entirely remote, enabling cross-organizational collaboration and readying the brand for the holiday season with relevant products for customers.
Empowering Supply Chains
Data, of course, is at the center of this emerging era of retail. McKinsey proclaims that "winning decisions are increasingly driven by analytics more than instinct, experience or merchant 'art'; what succeeded in the past is now a poor predictor of the future, and analytics is helping to inform and unlock new pockets of growth.”
Thankfully, some brands are already out ahead of the trend and are clearly rethinking retail, product creation, and supply chain logistics for the new era. They're taking product decision making to the next level and should serve as inspiration for other retailers to get the modern decision-making tools they need.
For instance, Nike last year purchased analytics and machine learning (ML) startups to ramp up its data science practice, which is helping it predict product demand locally at a global scale. Meanwhile, fashion retailer H&M employs internal data to manage the supply chain and external data to forecast product demand trends across markets worldwide. And before even considering inventory and supply chain complexity, shoe seller Soludos is using ML-powered data for various product-driven decisions, including what its shoes are made out of, how many the brand makes, and what images appear on slippers.
In all cases above, the brands have modernized their workflow processes to meet the desires of increasingly on-demand consumers. In their own ways, they're well-positioned to enhance their ROI while contributing positively to sustainability, which is extremely important to young adult shoppers.
As we head further into this decade, expect more retail players to embrace new tools that let them make decisions collaboratively from any location and then swiftly execute them. Even though the industry was moving in this direction in recent years, COVID-19 has been a forcing function for workflow and product-creation change — it’s now up to merchandisers to decide whether they want to meet the challenge.
Matthew Field is co-founder of MakerSights, a company that partners with leading brands to modernize their product-to-market process and more efficiently create products their consumers love.