How can smart applications make manual grocery picking faster?

While our automated picking bots are the ones that often grab headlines, our in-store-fulfilment (ISF) solutions allow grocery retailers to meet the growing demand for online orders using existing stores.

Our ISF solutions are an important component of the wide fulfilment ecosystem we are building with partners worldwide, and are already a part of international partnerships with Coles, Sobeys, Kroger, ICA, Morrisons, and Bon Preu. It allows our partners to get their boots on the ground and scale orders quickly, or to serve areas not yet ready for full automation.

But there’s a challenge. Physical stores are set up for a leisurely shop — encouraging customers to spend as much time in the aisles as possible. This is exactly the opposite of what is needed for picking in-store where every second is of the essence. How can manual store pickers get orders picked, packed, and out the door quickly enough to make this economically viable?

How does store-based, manual picking work?

Online customer orders are processed and planned so that pickers receive instructions on a mobile app, to pick orders for customers. This is managed by an order management system, which communicates with the eCommerce platforms used for the orders.

With a trolley in tow and a mobile device, the picker races around the aisles in order to pick customer orders as quickly as possible.

Think supermarket sweep — without the matching jumpers.

For grocers, time is money.

Key metrics such as units-picked-per-hour (UPH), pure pick rates (PPR) and order accuracy are crucial to productivity and profitability.

There’s a lot to think about:

• Store layout — physical stores are usually set up for customer browsing in mind. Deliberately long-winded layouts entice shoppers to zig-zag around the store, spending more time and money. But this layout is far from helpful for pickers, who want to complete orders as quickly as possible.
• Store congestion — the problem is compounded when it’s busy. During peak times stores become congested with shoppers, pickers, and putaway operatives. Pickers have to bustle around customers to get to goods — leading to lower throughput.
• Store familiarity — pickers who aren’t familiar with the layout of the store may misplace items, with order accuracy suffering as a result. Missing or duplicate items provide an added problem as they need to be ‘rectified’, resulting in hidden costs over time.

Improving pick rates. The need is speed

Our in-store fulfilment (ISF) team built a smart app to guide pickers around the store with the most efficient routes possible to fulfill orders.

The app, on an android device, seamlessly integrates into the retailer’s Ocado Smart Platform (OSP) eCommerce platform, order management system, and transport management systems.

The routing calculation problem is a complicated one to solve, and it’s completely unique for every store as every store has a different size, shape, and layout. ISF uses smart algorithms to combine orders and plan pick walks in an optimal way so that pickers can spend less time walking and more time fulfilling orders.

The app guides the picker to identify the exact location of items on the shelves — using data from retailers using an API and provides the picker with a list of smart substitutions if the item is out-of-stock. Picking routes are planned using the location of the items, meaning pickers can collect multiple orders at the same time, with less walking. Orders are fulfilled faster, and accuracy is improved. What’s more, pickers experience less fatigue.

Pick walks are split into regimes (ambient, chill, and frozen) to achieve maximum efficacy with the constraints of the store space and layout. On top of that, ISF enables bulky items and service counter picking.

The app also allows for multiple orders to be broken up into multiple pick walks — so one pick walk could contain items from multiple orders at the same time. This can be used to reduce store congestion and to speed up pick rates.

The simulation team can even factor in different trolley designs to measure the impact on pick rates in-store.

So what’s next for in-store fulfilment?

In-store fulfilment is often retrofitted into existing physical stores but the in-store fulfilment team are now using simulations to help our partners design and optimise brand-new dark stores / dark floors.

A dark store / dark floor is a dedicated physical store or area used solely for online-order fulfilment, not as a customer store. This means it can have bespoke features to make order picking more efficient.

Before building a new dark store, simulations can be used to quickly and accurately test and optimise store layouts.

As a key contributor in picking rates, we can experiment with this to determine optimal product placement and optimise shelf designs — without having to lift a finger on the ground.

With plans to improve scale and build applications to cover end-to-end inbound capabilities in the future — the team continues to perfect manual picking for our partners.

Originally published at https://www.ocadogroup.com.