AUGUST 15th 2017
Top 7 Insights for Retail Execs from McKinsey's 2017 AI Report
By: Annie Wu
The McKinsey Global Institute (MGI), named the 2016 number one private-sector think tank in the world, gives executives data and insights to make better decisions. Their reports have covered more than 20 countries and 30 industries, and they publish an annual detailed report to guide decisions around Artificial Intelligence (AI).

Their newest research shows that firms that proactively adopt AI have a significantly higher profit margin than partial AI adopters or non adopters. Since it's 80 pages long, we summarized the top 7 insights that can help retail executives.

The report describes four ways AI will transform retail operations: anticipating demand trends, automating inventory and merchandising decisions, personalizing marketing, and automating parts of the customer buyer journey.

Next, it describes how firms successfully implement AI within their organization: where to start and who to hire or partner with (since hiring is tough!).

1. AI will anticipate demand trends to increase revenue and cut costs

Forecasting plays an important role in retail financial performance because it drives pricing, inventory, merchandising, and replenishment decisions, and AI can reduce forecasting errors by 30 to 50% (22).

Machine Learning forecasting systems can analyze more data than legacy statistical forecasting systems. Using historical sales data combined with real-time external data such as weather, local events, pricing, and promotion campaigns, machine learning can more accurately anticipate demand and therefore sales. Predicting demand earlier and more accurately helps retailers reduce shortages, reduce inventory, and minimize waste. A European retailer had implemented machine learning to predict fruit and vegetable sales. Their system automatically orders produce and has improved earnings by 2% (42).

According to the report, companies can use this demand information to reduce supply chain administration costs by 25-40% (22). With over 20 different roles in supply chain administration and typical salaries of $50,000 to $100,000, this represents meaningful savings.

2. AI will automate inventory decisions

Retailers source thousands of SKU's from thousands of suppliers, and no forecast is perfect. AI can balance and optimize inventory in real time without sacrificing supply chain transparency to reduce lost sales due to product unavailability by up to 65%, and to reduce inventory by 20-50% (22).

Otto, a German online retailer, manages inventory with AI software that automatically orders from its distributors. It is 90% accurate at forecasting what the company will sell every 30 days, cutting surplus stock by 20% and reducing product returns by more than two million items a year. The AI system has proven so successful that the company lets the technology order 200,000 items a month without human intervention (25).

3. AI will automate and improve merchandising decisions

One of the greatest AI opportunities for retail is to improve pricing decisions. In accordance with the company's strategy, AI can price goods dynamically, lowering prices when there is less demand or price inelasticity. Overall, machine learning price optimization can improve efficiency by 50% (43).

4. AI will personalize marketing to grow sales

AI can help retailers uncover what customers want before the customers arrive at the store, reducing CAC, and growing revenue. AI software can analyze each shopper's past purchases, age, home address, and web browsing history to personalize discounts, features, and assortment. McKinsey's research shows that AI personalization increases sales by up to 5% (28). For online retail, AI powered personalization can increase sales by 30% (28).

One example of AI insight based selling is from 1-800-Flowers, which uses machine learning and language recognition to propose a selection of products based on a quick chat with the shopper (44). Also, there are retailers that use smartphone data to send coupons to shoppers as they approach a store, and increases discounts and offers based on how long the customer stays.

5. AI will automate delivery and in-store shopping

AI advances lead to nearly entirely automated experiences. In terms of warehousing and logistics, AI already optimizes deliveries and automated fulfillment. Ocado, a UK supermarket, introduced robots in their warehouses to move products to delivery vans. Their AI routing system picks the best delivery route based on traffic and weather (26). Costs related to warehousing and transportation can decrease by 5-10% with AI (22).

Another important advancement is in online retail, where companies are constantly working to reduce delivery times. In 2014, Amazon received a patent for "anticipatory shipping" where they use data such as order history, shopping cart items, and length spent on product pages to predict what users will buy and begin shipping the products to their homes before the purchase is actually made.

The in-store experience is also transforming due to new technology, particularly machine learning powered computer vision. Amazon launched a grocery store where sensors and cameras detect a specific shopper take an item off the shelf, relay this information to an AI system, and automatically charge the shopper's credit card when they walk out the door.

6. Smart firms start with small projects

To implement AI into, smart firms identify and build a business case around a pain point in their business. It is best to focus on a project that is limited in scope, where there AI has been proven to solve a specific problem at scale. When companies become experience the benefit of AI, they should apply it more broadly with long-term projects and experiment with unproven use cases.

7. Smart firms find top talent

Firms that choose to implement AI solutions often experience challenges finding data science talent and 'translators' who can lead AI business projects, because they're in high demand across the US. To implement AI, some firms choose to partner with third parties like AI startups or AI consulting firms. By doing so, they reduce their costs, reduce their risk, and can run quick experiments to evaluate their ROI potential of applying AI to different parts of their business.

In retail, AI can be extremely useful in anticipating demand trends to optimize decision making, marketing, and user experience. For a firm to successfully implement AI in their operations, they must start small and slowly build internal capabilities, whether this means partnering with academia or other organizations, hiring outside talent, or reskilling their current team. McKinsey's Artificial Intelligence Discussion Paper acts as a guide and outlines the current state of artificial intelligence in the business world, the benefits of AI in various industries, and how firms will be able to implement their own AI solutions.

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