Lesson 23 of 101
Build a Hype Filter
I've come back to this idea repeatedly in my work because the mindset behind innovation usually changes before the results do. What people notice, question, challenge, and act on determines how ready they are for what comes next.
I was exploring Second Life back in 2007, long before the metaverse hype cycle arrived. That experience reinforced a useful rule: every big technology trend contains three things at once: something real, something exaggerated, and something too early.
Your job is to separate them.
Dismiss everything and you miss the future. Believe everything and you waste money chasing headlines. The best leaders build a hype filter that asks what underlying capabilities are improving, what customer problem is actually being solved, what economics are changing, and what has to happen before scale becomes plausible.
Skepticism and curiosity can coexist.
So what does that mean in practice? It means challenging the assumption, habit, or hesitation that is keeping you anchored to the present. Here are three places to start.
Seen in the wild
Augmented reality has repeatedly been surrounded by futuristic promises. The practical question is whether putting information in a worker's field of view saves time, reduces errors or improves safety. DHL examined that question in a warehouse, far from the more theatrical demonstrations of immersive digital worlds.
In a 2014-2015 pilot with Ricoh and Ubimax in the Netherlands, ten warehouse workers used smart glasses that displayed aisle locations, products and quantities during order picking. Over three weeks they picked more than 20,000 items and completed approximately 9,000 orders. DHL reported a 25 percent improvement in picking efficiency during the pilot.
The trial was small, and an improvement in one warehouse is not the same as an industry-wide result. But DHL kept exploring the operational use of the technology. By 2019 the company reported rolling out vision-picking smart glasses across multiple geographical regions and extending the approach to freight hubs.
That is a disciplined hype filter in action. DHL did not need to predict the future of the metaverse to test augmented reality. It connected a new capability with a tedious, measurable task, then used field evidence to decide whether broader adoption made sense.
Why it matters: Test the unglamorous operational problem hiding inside the fashionable technology narrative.
When blockchain became a corporate buzzword, it was tempting to launch projects simply because the technology sounded transformational. Walmart had a narrower problem. During foodborne-illness outbreaks, identifying the farm associated with a particular shipment of lettuce could take days while people located paper records across multiple suppliers.
After pilots with IBM Food Trust, Walmart announced in September 2018 that fresh leafy-greens suppliers would need to provide digital traceability information, with staged milestones in 2019. The company wanted to trace specific products back to their source in seconds rather than rely on a succession of phone calls and scattered files.
The project is best understood as a serious implementation attempt with a clear operational objective, not proof that blockchain later solved every supply-chain problem. Supplier onboarding, data quality and the ability to sustain end-to-end records remain real challenges. Walmart's public announcement demonstrates the business problem and intended standard, not a universal industry outcome.
The value of the example is the screening question: would this technology improve something necessary and measurable if customers never heard its name? Walmart framed the experiment around identifying unsafe food faster. That is a far better reason to investigate blockchain than the fear of missing the latest technology trend.
Why it matters: A genuine innovation proposal begins with a costly problem and testable outcome, not a headline technology.
Make it real today
- For the next hyped technology, write down what is real, what is hype and what is simply early.
- Track enabling trends rather than headlines.
- Invest enough to learn before you invest enough to regret.