E-commerce merchants and

warehouse management 

Do you know who’s behind your delivery? Can you imagine what process happens after clicking the confirmation button? And how many services start working after that? Let me share quick desk research, which probably give you some visibility and next time, if something, goes wrong, you will know where is an issue.

Industry Overview

As you can imagine, delivering process includes many steps. And warehouse management is a part of a big management order system (I’ll call it OMS). It contains several tools for customer service, accounting, Point of Sales (POS), warehouse management, inventory control, picking tools, etc. The process includes many participants, starting from customers, managers, pickers, finishing delivery workers. The highest chance to catch some issues is when an order moves from one part of the system to the another. In this story, I’ll focus on the picking process and users who do this job - pickers. This part requires interaction with people, and the human factor might add extra issues.


Problem statement

After reading several articles about the picking process I can highlight several problems, that frequently happened in fulfillments storages:

  • Pickers pick the wrong items or quantities;
  • Lack of navigation in the storage increases the time for picking the order list. It appears a delay the order fulfilment;
  • No prioritisation for urgent orders during picking;
  • Some pickers use printed order lists for picking. It can create a lot of errors caused by the human factor, and wouldn’t allow to update the quantity or replace an item;
  • No visibility of who is assigned to the order. It means no visibility of the order status. It creates difficulties in order to track responsibility. Workflows should show visibility on all actions and movements and who has performed each action;
  • No clear navigation in the storage. Often racks has no identifier to track your position in the storage and track where is an item. Especially it’s a problem for newcomers or when new items which weren’t in an assortment earlier arrived;

Generally speaking, the issues connected not only with software but also with the physical environment.

Benchmark analysis

Let’s check how other market players solve these problems. So I reviewed competitors to understand the picking process and typical workflow, solutions they are providing. It’s not a very deep analysis, but it helps you understand the industry overlook. Follow the link to see the full version: 


Market overview insights

So, long story short:

  • Most of the solutions adjusted only for mobile phones. Tablets are used rarely, mostly as a stationary device near the racks;
  • In-build camera or a separate Bluetooth device scanning are used for scanning. NFC rarely used;
  • Big UI elements, high-contrast elements are the typical things for interfaces. Which make sense because of the environment of using, - dark and rush context make work very stressful;
  • Most of the solutions clearly show validation of the picking process, by using bright red or green colors for errors, success states;
  • Manual scanning of each item protects the picking up the process from the human mistakes;
  • Some solutions allow to work with several orders simultaneously;
  • Very few solutions show item details with a proper photo, description and fulfilment;
  • Typically the flows for the picking up process are straightforward and plain;
  • Most of the solutions show the location of items and use physical navigation in storage;
  • Most of the solutions have a bad visual hierarchy in-app.


To release you from looking at the competitors screenshot, just check the typical flow for the pickers app. It’s pretty straightforward, as such work requires minimum mistakes.


Understanding the user contexts and create empathy

Before we jump to shaping the design solution, let’s, firstly, check the context and user need based on benchmarking that we've done.

  • Who - workers who are working on the warehouse, sometimes, know nothing about a store inventory. Workers have many orders and try to do their job efficiently. They rarely have the empathy to their customers, because they’ve never interacted with them
  • When - let’s say each worker has a shift, it’s some hours, over which a picker focused on doing their job like updating inventory, picking the products, and many others. And apart of that their work requires interacting with other pickers. 
  • Where - typically during shift pickers spend time in storages with racks, with lack of light, rounded products, boxes, and packages, usually their hands are busy with device or a paper pick list and picked products. 

I divided the whole process into the logical stages, that every order is passing over on the way to your home.


Journey Mapping

The process interacts with many users, so I proceeded to Journey Mapping to understand what dependencies between the system, app, and users. The map includes all users and but focuses only pickers needs, obstacles and tasks.
Below the link for full version of Map. Yeah, the map is complex and big. 


To sum up, the problems we have on each step:

  • An order placed;
    • Mismatch with inventory naming;
    • No relevant info about courier arriving;
    • No complete specifications about order;
  • Reviewing an order;
    • No ability to edit order;
    • The database is not appropriate and items aren’t available;
    • Difficult to change an item in the ongoing order based on clients demand;
    • Difficult to check availability in the database;
    • Another picker can already pick up the order;
  • Picking up;
    • No navigation in the warehouse;
    • Mess in the warehouse;
    • No visibility of the picking up process;
    • Difficult to designate the current order status;
    • Difficult to regulate the right amount of items;
    • Hard to control picking up the right item;
    • No visual association between the item in an order and in storage;
  • Ready to delivery;
    • Wrong order status;
    • Missing item in order;
    • Order isn’t ready when a courier arrived;

I will not consider the rest of the stages, because it’s rarely connected with the picking process, but I believe, it’s enough for shaping the design solution direction.

Design solutions

So, taking into account the problems, let’s figure out the possible scenarios and features for the app.

  • Using a phone camera or NFC for scanning items during picking, immediately update the inventory in the database;
  • Using physical navigation in the warehouse;
  • Using prioritisation for orders — complete in-progress orders firstly;
  • Showing % progress of order fulfilment and display the order status;
  • Allow pickers manage orders — remove, add, replace items with mentioned reasons;
  • Allow pickers to communicate with clients for discussing availability items;
  • Automatically send a notification to client and courier in case of changing the status;
  • Showing courier’s ETA;
  • Using personal barcode for fast login to the device;
  • Picklist for picking several orders;

Navigation architecture

The next step was creating a flow for application and finding all dependencies with possible use cases. While I was reviewing the picking process I realised some missed features which can help make the picker's job more smooth.

  • Finished orders can be in the separate menu because it’s rarely used;
  • Add a full store inventory copy, in case, if the customer asks to replace something or check availability;
  • Global search and filtering. It would help when the client doesn’t know the correct item name or SKU.
  • Also, add the ability to scan QR code for checking an item availability;

Here you can find the full flow with comments and notes.


The concept

Of course when you start thinking about wireframes for a new product, one of the things pops up is device orientation. For sure, there are many things that have impact on decisions, for instance, some pickers wear a device on hand. Landscape layout is better for arranging info, but the app is used during walking and portrait layout is better for this. I even walked with a tablet to check which orientation is better. With the portrait layout the device helds more stable. Also, it shouldn't be a big tablet, for more convenient using it must be approximately 7 inches. So probably it would be an android device.

The second point was a guideline, should it follow android guidelines? Then I thought over the condition of using the tablet. The condition is different from typical users. Pickers use the app in storage where lots of items, could be not enough light. Usually, they use device with one hand, in the meantime, they pick items with the another hand… So the recommended element sizes wouldn't work for us, but let’s follow just the android patterns of navigation, as devices could be low-performance. 

Then I started designing information levels for the app. On the top of the screen (more difficult-to-reach area) will include general info that doesn’t require any actions. The next is info related to content — orders status and etc. The next is content — orders + elements that require interaction. And on the bottom of the screen, in the most easy-to-reach area, is place for primary CTAs.


For the concept, I chose a dark turquoise color as a primary what creates a good contrast, big UI elements that stand out and increased font for better visibility. The yellow color I used as the accent color and only for status and other small UI elements. You can check the interactive prototype here: 

During the visual phase, I continuously tested the prototype on the device and check interaction, so the final layout had changed because of usability concerns. There are still many open questions, so, this design solution should be customised for specific company needs and picking environments. Some key solutions also described below in the images



Through the desk study, I have touched the surface of the entire warehouse ecosystem, it was certainly exciting for me to explore the new field. Of course, for a more holistic and contextual approach, you still need to do a deep user analysis to recognize precise user needs and business logic.

Thanks for reading, if you have any feedback or questions, drop a comment or write me to nadiia.shymchenko@gmail.com or Twitter

I hope you enjoy the study as well!