Shelf Engine Raises $41 Million to Transform the Grocery Supply Chain, Quadrupling Retailer Profits While Reducing Food Waste by One Third
SEATTLE — March 18, 2021 — Shelf Engine today announced a $41 million Series B funding round to expand its automation solutions to grocers facing mounting customer, labor and competitive pressures. Currently live in more than 2,000 grocery stores nationwide, Shelf Engine’s intelligent forecasting and order automation system uses advanced statistical models, machine learning and neural networks to generate the most accurate orders for grocers, drastically increasing sales and margins while reducing the 43 billion pounds of food the industry wastes every year.
The round, which brings Shelf Engine’s total funding to date to $58 million, was led by General Catalyst with follow-on investments by Series A lead GGV Capital along with Foundation Capital, 1984 Ventures, Correlation Ventures, Founders’ Co-op, Soma Capital, Firebolt Ventures and Initialized Capital. In addition to continued expansion, the round will enable Shelf Engine to further invest in its rapidly growing team of engineers, data scientists and supply chain automation experts.
Prior to the pandemic, average grocery profits hovered around two percent, largely due to store and supply chain inefficiencies. Shifting product demand and rollercoaster sales further compounded these issues, with stores now throwing away one-third of their fresh inventory. This over-ordering not only costs profitability, but forces retailers to increase prices to make up for these losses.
“Grocery retailers today need to innovate quickly or they’ll put their companies at risk.” said Stefan Kalb, co-founder and CEO, Shelf Engine. “We’re reducing waste, while simultaneously increasing sales, and that goes straight to the grocer’s bottom line. We’re helping grocers to make much more money, better positioning them to gain market share and offer competitive prices, especially important as tech giants and other disruptors are entering the market. This latest round will enable us to further meet the demand from our customers to launch into thousands of new stores in the next 18 months.”
Traditionally, buyers at major retailers use unreliable Computer Assisted Ordering (CAO) and SaaS solutions that require significant upfront hardware and software investments to manage their inventory. These solutions often fail to account for on-hand inventory data and high volatility in sales patterns such as with pandemic or weather-related buying, leading to wasted time and inaccurate orders
Conversely, grocers who utilize Shelf Engine’s order automation solutions benefit from an average profit margin increase of more than 50 percent, while reducing food waste by as much as 32 percent. By analyzing historical orders and sales data – alongside real-world considerations such as holidays, school schedules, local events and weather – Shelf Engine creates the optimal order for every single product every day, automates the order submission process and minimizes stockouts by 90 percent, which increases sales and margins. Providing more value and peace of mind, Shelf Engine actually guarantees the sale of every item it manages and orders for the grocer, buying back all unsold products and virtually eliminating the grocer’s inventory risk.
“Shelf Engine’s business model hits the trifecta of simultaneously benefitting retailers, consumers, and the environment. That degree of stakeholder alignment is a rare accomplishment,” said Kyle Doherty, managing director, General Catalyst. “That the company has been able to help transform ordering and inventory management for thousands of grocers in just a few short years is a testament to CEO Stefan Kalb’s instincts and the strong, data-driven team he’s built.”
“The grocery industry is on the precipice of monumental change, with few companies driving the same level of innovation as Shelf Engine,” said Hans Tung, managing partner, GGV Capital and Shelf Engine board member. “GGV looks to support companies with the potential to create significant impact on the efficiency and evolution of existing industries. Shelf Engine has the ability to overhaul the entire supply chain, providing direct, tangible benefits for both the grocery industry and the environment.”
About Shelf Engine
Shelf Engine is transforming the food supply chain by helping grocery stores increase profit margins while drastically reducing food and beverage waste. Using machine learning, Shelf Engine forecasts demand for highly perishable foods, reducing waste and out-of-stocks. Shelf Engine’s unique business model handles the entire ordering process from vendor management to shelf optimization, saving retailers money and reducing risk by buying back any remaining unsold items. Launched in 2015, Seattle-based Shelf Engine has more than 145 employees and manages orders for leading grocers at thousands of locations nationwide.
About General Catalyst
General Catalyst is a venture capital firm that invests in powerful, positive change that endures — for our entrepreneurs, our investors, our people, and society. We support founders with a long-term view who challenge the status quo, partnering with them from seed to growth stage and beyond to build companies that withstand the test of time. With offices in San Francisco, Palo Alto, New York City, and Boston, the firm has helped support the growth of businesses such as: Airbnb, Deliveroo, Guild, Gusto, Hubspot, Illumio, Livongo, Oscar, Samsara, Snap, Stripe, and Warby Parker. For more: www.generalcatalyst.com.
By analyzing historical orders and sales data – alongside real-world considerations such as holidays, local events, and weather – Shelf Engine’s intelligent forecasting creates the optimal order for every single product, every day. The completely automated ordering process minimizes stockouts by 90 percent, increasing sales and margins. Providing peace of mind, Shelf Engine guarantees the sale of every item it orders for the grocer, buying back all unsold products to virtually eliminate the grocer’s inventory risk.
from the Shelf Engine team.