Product Management in a Connected World: Five Tips to Survive the Digital Revolution
“Approximately fifty years ago, on October 29, 1969, the internet was born. It was a humble beginning—a single login from a computer terminal at UCLA in Los Angeles to the Stanford Research Institute (SRI) in the Bay Area. But it was a tiny baby step that would eventually catapult the world into the information age” — Matt Novak, Gizmodo, December 29, 2019 [1]
We can say that, 50 years ago, the number of connected devices was …. 2. How many there are today? I believe that nobody has even an approximate estimate, but we can safely assume that we are talking about billions. What is even more staggering is the progression. Look at this chart: What we are observing is an almost vertical hockey stick curve, which triggered what we can now consider a true revolution. In fact, in Europe, we started referring to this as the 4th Industrial Revolution, or Industry 4.0.
In case anyone would still doubt that we are in the middle of a historical transformation, just stop for a second to think how your daily life would look like without connectivity. Even if someone will say that it would be better, if we are honest, we’ll admit that if defies imagination.
Each industrial revolution has brought about a transformation of the job landscape, with professions and businesses changed, created or destroyed, and Industry 4.0 is no different. So, what happens to the product management professions in this brave new connected world?
In this paper I share my personal list of change drivers with the highest impact on product managers and provide some suggestions on how to prepare yourself in order to survive the change and possibly leverage it to succeed.
Big Data
Remember I mentioned at the beginning that we are now dealing with billions of connected devices. What does each of these devices do? They generate data and make it available for consumptions by other devices or systems, or humans! Product Managers today are literally bombarded by a staggering amount of data.
So, this is good, isn’t it? Data is the new oil, right? Yes and no: like you cannot fill up your car with crude oil, you will need to harness the data flood and refine it to make it usable. In other words, you need to be able to transform data into information, and possibly actionable information, meaning, information which is relevant for you, your product, your business and your strategy. It is not a “simple” data analytics challenge: to make your analysis significant you need to combine it with a context that gives it meaning.
Let me share a story with you from a colleague of mine. The event happens in the USA, where my friend is a regional sales manager for distribution transformers. He loves analyzing data and makes it a point to regularly collect sales data for the different regions and spot patterns. He once observed an unexpected sale spike in one of the States.
He tried to figure out what could possibly have caused it, unsuccessfully, so he decided to hire a consultant to help him correlate his data with all possible trends, in a sort of data-driven PEST analysis. The only correlation that was found was that the spike happened right after that state legalized the sale of marijuana for recreational purposes.
A classic WTF moment, until he realized that this event gave birth to many weed-growing businesses, requiring hot houses, requiring energy, overloading the grid. The grid operators had to scramble to strengthen their distribution networks, purchasing new transformers as fast as they could be made. Was this actionable information? I’ll let you guess the answer.
So, what is the lesson from this? To me, this story has been the first eye opener, which was then reinforced when, discussing with the dean of a Product Management Executive education program in India, he asked me how many data scientist I had in my team and he almost fell of the chair when I said “none”. It takes a specific set of skills to be able to squeeze information from data, and you should really consider relying on data professionals. It will cost you some money but consider what the cost of ignoring data or deriving wrong information would be.
End user proximity
Customer centricity is the gospel of the product manager, nobody would disagree with that. Except, in many cases your customer is not the end user. This is generally the case for B2B: the buyer of your product will not be the same person who will use it. It has always been one of the key challenges of B2B product managers to have access to first hand usage pattern and user experience feedback. As a result, we have often observed products being developed to solve the customer’s problem, but not the user’s one.
IoT has closed this gap: if you are selling connected devices, it does not matter who is buying them from you, there will always be a way for you to be in touch with the actual user. Let me bring you the example of a low voltage circuit breaker, a flagship product from the ABB Electrification business. These products are sold through system integrators, OEM or distributors, while the end users would be the facility managers. A couple of years back these devices have been enhanced with a micro-edge, converting them to IoT devices. Ever since then it has become possible to analyze usage patterns and behaviors, providing new insights and opportunities.
If you want to take full advantage of these privileged window into the world of the real users you need to be prepared to collect, read and interpret this precious information. To this purpose, usage data gathering should always be a requirement in your backlog, not just for the device per se, but for the whole IoT solution. And oh, by the way, this is also an element of Big Data, so refer to the previous topic.
Complexity
When you think about the typical IoT solution, you can usually identify a set of recurring components: smart devices, a communication vector, a cloud platform, and a set of value-added apps. There are several frameworks which have been recently published to describe these elements in a structured way. The one I found most effective is The IoT Decision Framework by Daniel Elizalde, which captures all the elements and puts them in relation to a few common decision areas which need to be considered.
This framework is a good way to harness and document the complexity of the challenge a product manager will face. Let’s go back to the circuit breaker example: we have the breaker hardware, the embedded firmware, the micro-edge, a cloud platform based on Azure and a set of apps. For each one of these, all the decision areas must be taken into consideration, explored and resolved, requiring several iterations. A product manager should really need to be the essential Renaissance Man to be able to effectively master all of these.
What we have seen is that IoT Product Management is becoming more and more a team undertaking. In order to be successful as a Product Manager of an IoT solution you will need to develop a basic understanding of all the elements in the framework, but you will then need to tap into skills and expertise from several sources. The framework will help you understand what skills will be needed, so that you can either develop your team, or develop a network of partnerships to cover the full scope.
New Competitors
Think about a traditional hotel chain, say Hilton, and then think about the origin of Airbnb. The first being a consolidate hospitality industry leader, the second being launched on the concept of sharing economy applied to hospitality. I suspect that, when Airbnb launched, it did not really show up in the Hilton marketing department competitor radar. Five years later, Airbnb booking volume has surpassed Hilton group. And history is full of even more dramatic examples of big, solid, established companies bowled over by the disruptive power of digital technologies.
Most of these companies share the underestimation of emerging technologies, combined with the complacence of the leaders of the pack. When they realized that they neglected to keep an eye on some new competition, these newcomers were already eating away at their market share and it was too late to do anything. This is not limited to new technologies entering the market, but also new ways of offering the same service. Think Uber, eating away at the traditional taxi service, or Amazon, introducing groceries in their on-line shopping. And the list goes on and on.
If you are in a traditional kind of business, you probably know your current competitors better than your kids (joking, I hope). Remember, however, that the largest your target market, the more likely it is to become the target of unknown or unexpected companies which will try to solve traditional problems in non-traditional ways. This is the keyword: focus on the customer problem, not on the features or benefits of your products. When you do that, you are more likely to keep an open mind and come up with solutions you did not think about. This will in turn help you broaden your perspective when you look at the competitive landscape, putting on your radar screen companies which may be in the proximity of these alternative solutions.
And one more thing: if you are a market leader, you have an advantage on these unexpected competitors, you know the market. Never fail to feed your knowledge into a Porter’s 5 Forces analysis considering the new perspective of the digital transformation, and really leverage and act on the insights you get from it.
New Business Models
One of the most rewarding experiences in product management is to achieve the perfect product-market fit and see your product flying off the shelves. In the product-market fit triangle, the problem to solve and your ability to solve it are not so much impacted by digital, but the economics element is, significantly. It used to be that you would build your product, decide your pricing strategy, and sell it at a profit, all very transactional. In today’s world, your customer’s will to pay is significantly more sophisticated, with so many different business models appearing in the market. I have found the map below which provides an excellent overview:
This map associates each business model to some examples. Interestingly, most of these companies and businesses are Millennials. Think about your daily life: you probably have done business with at least one them. Another example: the number of people owning a car is fast decreasing, in favor of leasing or long-term rental (servitization) or car sharing (sharing economy). And the list can go on.
So, which business model will you choose for your product? Unfortunately, a discussion around this question may probably require a dedicated paper, and I would certainly recommend that you develop at least some familiarity with all of them. With that, you will be able to compare your product or service to what you see in the map above: this may be a good indication as to how you may want to bring your product to the market.
Conclusions
In the course of history, humanity has evolved through disruptive and often violent events, and the people who survived and thrived are the ones who have been able to see them coming and prepared accordingly. The digital transformation has certainly proved to be as disruptive as many past transformations, so we better make sure that we are ready to surf the wave and stay on top of it. Here’s then a quick recap:
- Big Data: the new oil, but you will need to refine it into actionable information. Learn data science, or partner with an expert
- End-user proximity: never has the end-user of your product been so close to you. And to your competitors too! Leverage the advantage you have through your product, design ways to capture usage data and discover patterns and insights
- Complexity: there are many more layers and decision areas in an IoT solutions than in traditional products. Adopt a framework to ensure that you either have the skills or skilled people to cover all the map
- Competitors: the competitive landscape broadened significantly, so you will need to broaden your horizon. Master tools to analyze competition, like the Porter 5 forces, and focus on the problem with an open mind
- Business Models: digitalization has brought to the market a lot of different ways to monetize the value delivered by your products. Learn them, see how they are used by other companies, recognize which one is suitable for your product
In case this discussion has let you concerned about the future, let me leave you with an extremely positive outlook: the number of product management jobs has been growing in the last years at a faster pace than most other jobs. Look at the graph below: 32% job growth in the US over the last two years. I do not have statistics yet to prove it, but somehow, I feel sure that many of these new jobs are in the IoT business.
The suggestions in this paper are certainly not a full survival plan, but hopefully they may be a good starting point to give yourself the skills you may need to get one of these jobs.
[1] Source: “Here’s the Internet’s ‘Birth Certificate’ From 50 Years Ago Today”, Matt Novak, published on Gizmodo, December 29, 2019
[2] Source: “The Digital Imperative”, Ralph Dreishmeier, Karalee Close, Philippe Trichet, published on BCG, March 2, 2015
[3] Source: “The Fourth Industrial Revolution is here — what makes it different?”, Mahesh Velliyur, published on Medium, February 24, 2019
[4] Source: “If data is the new oil, then why I am still broke?”, SingularDTV, published on Medium, January 10, 2019
[5] This Photo by Unknown Author is licensed under CC BY-NC
[6] Source: “A Simple IoT Framework for Product Managers”, Daniel Elizalde, published on danielelizalde.com, Copyright © 2016
[7] Source: “50 Examples of Corporations That Failed to Innovate”, Katrina Aaslaid, published on Valuer, November 22, 2018
[8] Source: “Digital Business Models Map: The Most Popular Digital Business Model Types”, Gennaro Cuofano, published on FourWeekMBA,
[9] Source: “Surprising Stats on the Demand for Product Manager Roles in the US”, Neal Iyer, published on Medium, September 17, 2019