“When Can I Have It?” - How I Found the Product the Market Was Already Asking For
Series: No Playbook, No problem.
Summary:
In a sea of innovation ideas, one stood out immediately. Every time I pitched it, even for 5 minutes, the reaction was the same: “When can I have it?” This series of posts explores how the winning idea grew into its own product category for cold chain transportation and logistics through real customer collaboration and early experimentation.
There is a moment every product leader and innovator dreams of and fears they never have. You pitch an idea. You explain the concept. You pause for reaction. And instead of the usual “That’s cool” or “Let’s us know when it is built”, you hear:
“When can I have it?”
Not IF, but WHEN.
That is the moment, you know you are onto something big.
Chasing the Problem: Cold Chain Logistics
At the time, my team and I were exploring a portfolio of innovative ideas in logistics and transportation, specifically around temperature-controlled logistics for perishable goods like medicine, vaccines, and food.
We explored a wide range of emerging technologies. Just to name a few:
Using IoT location data to determine optimal routes for temperature-sensitive cargo
Estimating the probability of theft for high-value products
Assessing the impact of weather on delays and product quality
Storing sensor data on blockchain for food safety (look up IBM Food Trust)
Drone delivery of essential medicine to rural areas
Each idea had promise but none had that "grab-you-by-the-shirt" urgency. Until we landed on Lane Risk Assessment.
The “Old” Lane Risk Assessment
The concept was not new. Pharma companies had been building risk profiles for transportation lanes for decades. The service was available through multiple providers, including us, as a professional service offering. The traditional process that most companies went through looked something like this:
Define the lane: Origin, destination, transportation mode (air, ocean, road, parcel), logistics provider and carrier, packaging type, and season (spring, summer, fall, winter).
Simulate shipment: Send “dummy” packages equipped with temperature sensors to record environmental conditions, and actual product temperature.
Collect the data: Sensor data was manually downloaded at the end of each trip, cleaned, and prepared for analysis.
Analyze the results: Analysts created lane profiles, typically focused on temperature, using statistical methods.
For example, if a product needed to stay between 2 - 8°C (which is usually a temperature in our home fridges), the goal would be to maintain it around 4°C throughout transit. If too many shipments approached or exceeded those thresholds, the lane was deemed risky, and organization would often revise procedures or restart the study.
If temperatures during actual shipments trended toward the extremes or experienced too many spikes that would be close to limits or outside of limits, the risk to product quality increased. In this case, our customers would change procedure for shipping products on the lane and repeat the study.
The problem? It took months to do it.
It reflected only a snapshot in time, relying on assumptions that past statistical significance could predict future performance. And it ignored external events such as heat waves, delays, strikes, and packing failures.
And we asked: “What if we could predict risk and failures in the lanes before it happens, giving customers time to act?”
Customer Visits: From Listener to Pitcher
At the time, I was leading our innovation effort - mostly early-stage explorations, connecting emerging technologies to potential market needs. I started by talking to internal SMEs: analysts, product marketers, sales consultants, and program managers - basically anyone who was mostly spending their days with customers. It gave me a great perspective about:
What we offered
Who our customers were
What pain points they faced
Why they bought our flagship solutions.
There was still a gap. How important was the problem I was trying to solve? How much did it really matter?
With support from leadership, I began joining customer visits - tagging along with sales to listen. In exchange, I would present our latest innovations to keep customers excited. I usually had 15 minutes at the end of long sales meetings… if I was lucky.
The First Pitch
I will never forget the first visit. It was a 2-day session. At the end of the first day, my manager - our CTO - casually told me: “Tomorrow, you are pitching. And you are opening the meeting.”
Wait, what?
The plan was for him to present, but after a slight panic, we pulled together a great pitch in just couple hours. In the pitch I also included tidbits I heard from the discussion and tour around the facility on the first day. I then showed them a basic prototype that was illustrating the idea. It sparked a very engaging conversation around the table:
“Should we adopt it? Will it help us?”
“Why are we still doing this manually?”
“Shall we be adding another tool to the number of systems we already have? Is it worth it?”
But here is a thing: no one said they did not want it. They were arguing about how to make it work.
The Moment
Soon after that, I went to another customer meeting. Again, I only had 15-minutes at the end of a long, draining day of meetings. The room was flat. People looked exhausted. I zipped through my pitch at 2x speed, walked through a prototype and wrapped it up fast.
My brain went: Phew, that’s over.
And then - the moment.
A senior executive at the client site said 3 magic phrases:
“THIS is what we wanted.”
“Why didn’t you start with this?”
“When can we have it?”
That was it. The spark.
From that point on, I joined every trip I could. My pitch evolved, and validation of the problem grew.
What I heard:
“If I had this today, I could sleep better at night.”
“We will give you our data and connect you with our SMEs if you can build it.”
“Can we trial it?”
“We did something similar in-house, and here is what we learned…”
The message was clear: It was real, urgent and needed.
Takeaways: No Playbook, No Problem
There is no single framework that guarantees a winning product or startup. But there are behaviors that increase your chances.
Assuming you have hypotheses around your customer unsolved needs based on market signals and you have an idea for solving it. Pause, and breath out.
Build a quick prototype to communicate your problem and solution idea (Figma, vibe coded demo, as long as it demoable and low effort that will work).
Specifically for data products (aka AI products), make sure you have data and can use it. I highly recommend engaging with your data teams to search for particular outcomes.
Go visit customers (a lot!!!) and pitch them your idea. Their reaction will help you both validate the problem and your idea. Bonus: you will get to meet your other colleagues and build relationship with them.
Validate with data, make sure you have enough signals that this is a problem worth solving. Record quotes, and KPIs you hear in conversations.
Up Next: Part 2: From Pitch Deck to Product: Turning an Idea into Product
Afterword
This story one of many innovative ideas my teams and I worked on. I am starting these blog series with success story to take you with me on long journey of building and launching this product. Why am I doing it? To inspire those who are just getting started, to remind you that you are not alone, and maybe to help you avoid a mistake or two.
I will share templates and approaches with you that I used. All of the approaches I recommend evolved from a lot of trial and error. If you ever find yourself needing the conversation, just reach out.
There were plenty of highs, and more than a few discouraging lows in this journey. But I kept moving forward, because I had people who believed in me. And if it were not for them, I would not be the person or the leader - I am today.
