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The new, “digitally powered” lifecycle


Digitization allows us to change our products' lifecycle, which in turn allows us to conduct business in a different way. This change of lifecycle occurs because our products powered by software and thus, they can thus have changes of functionality downloaded to them. For example, one morning Telsa owners awoke to find that they cars could now self-park.

Let’s look at the ways in which the product lifecycle can change because of digitization.

new product lifecycle.png

Minimum Viable Product
Firstly, we will be able to release products before they are “ready”.

When we couldn’t change the functionality of products once they were released, we had to ensure that a product was highly competitive before we released it.

When we have digitally-enabled products, we can release a “minimum viable product” in order to get something into the market. We can then add functionality to our product as we learn how customers use it.

At present, releasing minimum viable products is something that startups do. Traditional companies don’t tend to think, “let’s release our new product idea and see”. This will change - business leaders will move from traditional “I need a clear return-on-invest and a complete product before I release” to “let’s try it and see what happens”.

Experimentation - “let’s test”
Minimum viable product leads us to our second attribute of a digitally-enabled product lifecycle. Because we can change the functionality of our product thru software, and because the software can send us data as to how customers are using it, we can experiment. We might, for example, release in just one country, monitor the usage data sent, and then adjust accordingly.

At present, experimentation is the domain of newer companies like Twitter, Yammer and Game Show Network (, part of Sony’s gaming division), but in the future, experimentation will be adopted by business managers in larger, more traditional businesses.

Continuous Innovation
Related to both minimum viable product and experimentation is the concept of continuous innovation. If our product can have its functionality changed by an overnight download of new software, then we can continuously innovate, adding exciting functionality on an ongoing basis. So, rather than only Tesla owners talking about how amazing it is that their car didn’t self-park but now it can, cooker owners, e-bike owners, users of smart cities and of smart buildings will all experience the joys of continuous innovation.

Data-based design
If you are going to experiment, you need fast and accurate feedback as your customers use your product. You can't afford to wait for information from your field organization or your partners to trickle in. Companies that experiment make data collection part of their products. They are then able to adjust in a timely manner, designing adjustments based upon detailed, real customer usage data.

For example, collects terabytes of information from the users of its games. can go from release of a version of their game, thru collection of detailed feedback data, to design of the adjusted product, to coding, testing and release - all in seven days. While techniques like Agile development and DevOps help to make this lifecycle fast, it all starts with the terabytes of data collects from its games as they are played.

Who analyses this data? Today it’s often data scientists. But that’s simply not a scalable solution. Look out for tools that will allow your product managers and product architects to “get their hands in amongst the data”. They will then be able to play with different analyses, maybe gaining new insights in the process.

When people talk about continuous innovation and experimentation, they are thinking in terms of their applications. The same principals apply to the data analytics that are used to guide the product’s design, and the data analytics used to market and sell it. We should get into the habit of thinking, “is there a data analytics experiment I try in order to get a better handle on how people use this product?”

Embracing “Fast Fail”
Anyone who has been involved in innovation or who has studied innovation will tell you that not every step on the road to innovation is a forward one.

The wonderful Picasso Museum in Barcelona shows the route that Picasso took to his first cubist painting. He tried one route. That didn’t work so he backtracked. He tried another route. That wasn’t quite right, but a combination of the first and second route, with a slight twist, led to something that changed art forever. Picasso didn’t dwell on a route that “didn’t work”. He stepped back and tried another route. He “fast failed” - he quickly realised a route wasn’t working and backtracked.

Successful innovators “fail fast”. And they are not afraid to pull a product even if it’s been in existence for a while. Google, for example, pulled Google Reader after many years of providing blog feeds because they believed the world had moved on to a Facebook / Google+ paradigm. We need to ensure we don’t cling to our latest cool idea or, to our old favourites, for that matter.

Fast fail is not just something for the application programmers and data analysts. It’s something that management needs to embrace too. People involved in “failures” need to be praised for trying, not tarnished for having worked on a “failure”. Both Bill Gates and Jeff Bezos talk about the importance of embracing failure. Jeff Bezos believes that failed experiments are a necessary evil to creating successful inventions - failure and inventions are “inseparable twins”.

Lower the cost of “getting something out there”
One would have thought that if the cost of, say, fuel falls, that people would bank the savings. Not so. In 1865 the English economist William Jevons observed that as coal prices fell, consumption rose so that the amount spent on coal remained the same.

Anecdotal evidence suggests that Jevons' paradox applies to experimentation. If we make it easy and inexpensive to experiment, then we will have more experiments and our rate of innovation will improve.

Lowering the cost and friction of experimentation and lowering the cost and friction in collecting and analysing data from these experiments is an essential component of the new product lifecycle. One of the key components of this, of course, is allowing the experimenters to pay for their compute platform on a pay-as-you-go basis - putting into operational expenses at least until the experiment is no longer an experiment but a strategic product to the business.

Should you adopt the new product lifecycle?
So that’s what’s possible with digitally-fuelled products. But should you do it? Just because you can do something new doesn’t mean you necessarily should.

The answer, from research by Professor Rita McGrath, professor of management at the Columbia Business School, is “yes”.

Professor McGrath wondered if there was something that companies that achieved solid, predictable growth did differently. She looked at 2,347 established companies and analysed the difference between those that achieved 5% growth per year over a 10 year period and those that did not. Only 10 companies out of the 2,347met her criteria.

What did Professor McGrath’s “outliers” do differently ..

  • Firstly, the outliers did a significant amount of experimentation and innovation
  • Secondly, the outliers made small bets early, releasing minimum viable products to get into the market quickly to test.
  • Thirdly, they adjust and re-adjust. They take a small step. Adjust. Take a small step. Adjust. They moved their resources around as part of this adjustment. In order to allow this movement, there was little “organizational rigidity”.
  • They make a number of smaller bets rather than a few, big bets. The average size of their acquisitions was much lower than the 2,337 who didn’t grow predictably.
  • They have diverse, but related, portfolios. They don’t “lurch” from one business area to a totally unrelated one. So, a pizza manufacturer might try 3D pasta printing (yes, a number of companies are working on this), but they would not go from pizza to robotic sheep sheering.
  • They use small acquisitions to get into new areas. And they were good at making these acquisitions work
  • Innovation is everywhere in the company - anyone can innovate and top management ask about and praise innovation. Innovation is not limited to a special “innovation unit”.
  • The whole company strives for speed and flexibility. Flexibility is valued above efficiency. They were okay with having flexible, but slightly inefficient systems.
  • They are stable. This seems like a contradiction, but it’s only because they have stable management, a stable company strategy and loyal, long-term customers that they are able to be flexible. Also, while they are flexible, innovative and love experimentation, each step is a small one so that they don’t lurch into instability.


Mike Shaw
Director Strategic Marketing

linkedin.gifMike Shaw

About the Author


Mike has been with HPE for 30 years. Half of that time was in research and development, mainly as an architect. The other 15 years has been spent in product management, product marketing, and now, strategic marketing. .

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