Building Your Digital Strategy – The Amazon Way

Internet of things strategy examples

An Overview of The Amazon Way on IoT

How is digital disruption impacting your industry?  What do the next 10 years look like?  Should the Internet of Things (IoT) be a key part of our digital strategy?  My goal with writing The Amazon Way:  10 Principles for Every Leader from the World’s Leading Internet of Things Strategies was to help a business leader answer these questions for themselves.  The 10 principles outline the key questions and opportunities to explore in building your digital strategy, and demonstrate these principles by how Amazon and other leading companies have become leading digital enterprises.

But that’s not enough.  Becoming digital is about having the leadership and ability to change within the organization.  I outline the key techniques Amazon uses to gain clarity on what the many opportunities they could do, and rationalize to the few pursuits they commit to.  This is strategy.

Here’s an example of one of the principles.—Continuous Improvements via Connected Devices

One of the more unique aspects of working at Amazon is that everything—every process, every customer experience, and every function—has an improvement plan and roadmap. You can find nods to this focus on continuous improvement all throughout Amazon’s leadership principles and history. Bezos originally named his company In fact, if you type “” into a browser, it will still take you to “Relentless” still perfectly encompasses Amazon’s nature. For Amazon, IoT is the latest big opportunity to stay relentless.

Principle 3: Connected devices are a powerful enabler for monitoring and improving your operations to make your company more efficient, competitive, and profitable.

Amazon’s company-wide expectation on continuous improvement is reinforced by things like Amazon’s evaluation process, which assesses employees for their commitment to continuous improvement. “Always looks for ways to make better,” the standard reads. “Makes decisions for long-term success. Investigates and takes action to meet customers’ current and future needs. Not afraid to suggest bold ideas and goals. Demonstrates boldness and courage to try new approaches.”

Of course, Amazon is just one of many companies that have found value through a focus on continuous improvement. It’s likely you’re at least familiar with one or more of the business methodologies it has inspired.

  • Lean—the philosophy of creating more customer value with fewer resources.
  • Toyota Production System—management approach intent on eliminating all waste, which includes key strategies such as “Just in Time” inventory and demand signals.
  • Statistical Process Control,or SPC—a system of attaining and maintaining quality through statistical tools that emphasizes root-cause elimination of variation.
  • ISO 9000 Quality Management—a set of quality certification standards based on eight management principles, including continuous improvement and fact-based decision making.
  • Six Sigma—a data-driven methodology for eliminating defects, reducing costs, and eliminating waste.

All of these strategies empower employees at the companies that use them to gather data and to act on the insights that data provides. They are encouraged to drive change and improvement from within. But each of these strategies was also created before IoT.

The introduction of ubiquitous connected devices has changed the rules of the data game, creating the possibility for real-time feedback loops that power continuous improvement programs.

Instead of living in a world of manual data collection, which creates limited, slow, and stale data sets, IoT creates an exponential stream of affordable real-time data. That flood of data empowers companies to focus on the continuous improvements to their internal systems, saving them time and money while increasing productivity and consistency.

How Amazon Took Operations from Good to Great

Today Amazon’s operations—the way they fulfill, ship, track, and deliver your orders—are world class. But they didn’t start out that way. Amazon measured, refined, and executed its way to greatness. It embraced continuous improvement as a way of life.

In the early 2000s, the leaders of Amazon’s fulfillment and operations capabilities decided to implement Six Sigma, a data-driven five-step approach for eliminating defects in a process. Define, measure, analyze, implement, and control—or as it is referred to in Six Sigma, DMAIC. This is the root improvement cycle in Six Sigma and sets up the methodical, measured steps and mind-set to squeeze out defects, costs, and cycle times.

One of the challenges of completing a Six Sigma initiative is that so much of the effort—generally up to 25 percent—lies in collecting data. Depending on the project, manual data collection can be not only difficult but inaccurate. The data itself is often of questionable quality, skewed by bias or cut short due to time and effort.

Because of these challenges, Six Sigma certifies professionals in a set of empirical and statistical quality-management methods to help them execute on the process successfully. These professionals are installed in an organization during a Six Sigma process to make sure everything is completed successfully. These kinds of people are also highly sought after and well compensated. Creating a team of Black Belts within your organization is one of the biggest cost drivers of Six Sigma initiatives.

That’s where IoT comes in.

Using connected devices to collect data frees up the Black Belts in an organization to tackle more projects. It also leads to faster Six Sigma initiatives and a much richer, more reliable data set.

Connected devices can bring visibility to your company’s operating conditions, giving you real-time insight into the flow, status, and state of key items in your process. Not only does this enhance your understanding of needed improvements, but it builds a way to scale operations with active quality and measure built into the process.

At the time Amazon integrated Six Sigma into its operations, the company was experiencing a disconnect in a process it calls SLAM. SLAM stands for the ship, label, and manifest process. Every time something, like a printer, is ordered on Amazon, that printer is placed in a box in an Amazon fulfillment facility, labeled, sorted, and shunted through the fulfillment center, until eventually it’s placed in an outbound truck. That’s the SLAM process.

When Six Sigma was introduced, packages were labeled and moved down conveyor belts before being manually sorted and delivered to the correct docking station. This worked well most of the time, but there was no final confirmation that the package had actually made it onto the right truck, and there was no visibility—for the company or the customer—about where exactly a package was in the outbound process. As a result, packages were occasionally missorted.

An occasional missort doesn’t sound like a big deal, but over the course of a year, missorts can cost a company like Amazon millions of dollars. More importantly, even one missort breaks Amazon’s underlying promise to its customers: the promise that all of their orders will arrive in their hands on time.

For Amazon, the solution was to create a positive automated confirmation, or “visibility,” that a package had moved correctly through all logistics checkpoints after its shipping label had been applied. The change was simple in concept but incredibly complicated in implementation.

To execute, Amazon installed sensors and readers across its conveyor system. The sensors would automatically scan a package’s barcode as it moved through the SLAM process. Since packages were scanned to destination-specific staging areas, the sensors allowed Amazon to track the whereabouts of specific packages at any given time in the SLAM process. Furthermore, as Amazon employees loaded those packages into the outbound trucks, scanners on the bay doors would alert them if a package was about to be loaded into the wrong truck.

By creating a positive-confirmation system for its packages, Amazon lowered its missorts to within Six Sigma’s 0.0004 percent accuracy range. That’s fewer than four packages missorted in every million.

Integrating IoT-Driven Continuous Improvement into Your Operations

There are several questions that you can ask yourself to help identify situations that might benefit from an IoT-driven continuous improvement process.

  1. What operating condition information would be valuable to your company?
  2. What manual data entry or logging is done in your business today?
  3. What is the incomplete and inaccurate data in my business?
  4. What inspections and audits are done today?
  5. What shrinkage, damage, or underutilization occurs in the business?
  6. What are the operating risks?
  7. What are the quality issues and drivers of customer contacts?

In other words, you need a big vision, but you don't want to "bet big." Make small bets to test your thinking. This can involve creating a prototype, a minimally viable product or jointly developing a project with existing customers and partners.

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