Imagine walking into your favourite Starbucks, only to find a chaotic scene: baristas frantically juggling mobile and in-store orders, customers impatiently waiting, and a once-smooth operation now resembling a complex juggling act. This was the reality Starbucks faced when they introduced their mobile ordering system, inadvertently stirring up a perfect storm in their well-oiled machine of coffee production.
At its core, this challenge wasn’t just about coffee but about flow management. The introduction of mobile ordering was like adding a new, invisible queue to an already bustling store. It forced Starbucks to reconsider how they managed the flow of orders, balanced resources, and maintained customer satisfaction across different ordering channels.
Let’s dive into how this coffee giant navigated the complexities of flow, using critical concepts like Little’s Law, expedites, flow debt, and work item age to transform their ordering chaos into a symphony of efficiency.
The New Lane: Mobile Ordering Takes Priority
When Starbucks introduced mobile ordering, it aimed to enhance customer experience by reducing wait times. However, this new “fast lane” in their order flow created unexpected traffic patterns in their previously well-managed system.
As the story goes, Starbucks’ leadership made a crucial decision: mobile orders would be treated as expedited items, giving them a “green light” at every intersection. While this prioritisation seemed beneficial for mobile app users, it introduced a significant challenge to their flow management: flow debt.
Little’s Law: The Traffic Light of Flow Management
To understand the impact of this change, let’s start with a fundamental principle of flow management: Little’s Law. In its queueing form, Little’s Law states:
Average Cycle Time = Average Work in Progress (WIP) / Average Throughput
This formula helps us understand the relationship between the amount of work in the system (WIP), how quickly it can be processed (throughput), and how long it takes to complete (cycle time). In Starbucks’ case, both walk-in and mobile orders now contributed to the WIP, while the throughput (number of baristas and their capacity) remained relatively constant.
As mobile orders increased, the total WIP in the system grew. Without a corresponding increase in throughput, this inevitably led to longer lead times — particularly for walk-in customers. Starbucks had effectively introduced a parallel workflow, but one that remained invisible until mobile customers arrived at the counter. As a result, walk-in orders started ageing in the system, like cars stuck in an ever-growing traffic jam.
Expedites: The VIP Lane That Congests the System
In flow management, expedites are items that bypass the usual queue and receive immediate attention. Starbucks treated mobile orders as expedite items, prioritising them over walk-in orders. While this met the expectations of mobile customers, it had unintended consequences for the overall flow.
This is where the concept of flow debt comes into play. By expediting mobile orders, Starbucks was essentially borrowing time and resources from walk-in customers. While useful for urgent tasks, Expedites create debt in the system that eventually needs to be repaid. The walk-in customers had to wait longer, creating a backlog that would ultimately slow down the entire flow.
Flow Debt: The Accumulating Backlog
Flow debt is similar to financial debt: it accrues over time and can have compounding effects. Each time a mobile order was expedited, the walk-in queue was delayed. The more mobile orders there were, the larger the debt became, increasing the work item age for walk-in customers.
Work item age, a critical metric in flow management, refers to how long an item has been in the system. For Starbucks, the work item age for walk-in customers grew as more mobile orders were prioritised. The older a work item gets, the more likely it is to cause dissatisfaction. In this case, walk-in customers noticed the delays, particularly during peak times, and their experience suffered as a result.
Rebalancing the Flow: Operational Adjustments
To address these challenges and optimise their flow, Starbucks implemented several key changes to their system:
- Dedicated mobile order stations: Starbucks allocated specific baristas to handle mobile orders. This separated the flow for mobile and walk-in customers, reducing flow debt by ensuring mobile orders didn’t consume all the capacity.
- Staggered pickups: Through the mobile app, Starbucks began notifying customers of when to pick up their orders, effectively managing the influx of mobile orders to prevent overwhelming the system.
- Order throttling: At times of peak demand, Starbucks limited the number of mobile orders the system would accept. By throttling orders, they effectively controlled the WIP in the system, ensuring it remained manageable.
The Importance of Work Item Age
Managing work item age became crucial to Starbucks’ flow strategy. They realised that the longer walk-in orders aged, the worse the customer experience became. By creating separate workflows and balancing their resources more effectively, Starbucks was able to reduce work item age for both mobile and walk-in customers, improving satisfaction across the board.
In your own Kanban systems, work item age is an important metric to track. If items are sitting in your system too long, it’s a signal that something is off — whether it’s a bottleneck, unbalanced flow, or poor prioritisation.
Conclusion: Applying Flow Management Principles
Starbucks’ mobile ordering story offers valuable lessons in managing parallel workflows and the costs of expedites. By treating mobile orders as expedite items, Starbucks initially created a better experience for app users, but at the cost of accumulating flow debt for walk-in customers.
Using Little’s Law, we can predict that increasing WIP without increasing throughput leads to longer cycle times. Flow debt increases work item age, which negatively impacts customer satisfaction. However, with intelligent adjustments — like separating workflows, throttling input, and managing expectations through better communication — Starbucks was able to bring its system back into balance.
As you think about your workflows, consider these questions:
- Are you managing your WIP effectively, or are you overloading your system?
- How do expedites create flow debt in your process, and how can you minimise their impact? What policies control how expedites interrupt your flow (or whether you allow them at all!)
- Are you tracking work item age to ensure tasks aren’t lingering too long in your system?
Applying these flow management principles allows you to create a more efficient, balanced flow — whether you’re serving coffee or managing complex digital workflows. Remember, the goal is to process work items quickly and create a smooth, predictable flow that satisfies all your customers and/or stakeholders.