In the 17th century, Europeans were switching over from wood to coal as an energy source. That also meant mines needed to be dug much deeper. The problem was that meant water seepage. In the late 1600’s, Spaniard Jeronimo de Ayanz borrowed from the ancient Greek inventor named Hero of Alexandria who had arguably invented the first steam engine prototype in the first century A.D. But de Ayananz’s steam engine was mainly a novelty. So in 1698, British inventor Thomas Savery created a more practical steam engine that could remove water, which was later improved upon by another Brit, Thomas Newcomen with his “atmospheric” engine. Arguably, this was a great application of technology as a means of improving production as the Industrial Revolution unfolded. Automation became a mantra.


Today, being “digital” has become a mantra as well. Some suggesting Artificial Intelligence may be the new steam engine, its “fuel” being data. The pandemic lead to a massive drive for business to become more digital and significant advances were made. Perhaps cutting three to five years off of where most technology companies saw adoption of their products going. According to a Harvard study, businesses worldwide are expected to spend upwards of $6.8 trillion on digital transformations by 2023. They are seeking to lower operational costs, improve speed to market and find entirely new revenue opportunities.


But the failure rate of digital transformations still sits at around 70%, or higher when companies retain large consulting firms. When companies engage smaller, focused consulting firms, the success rate goes over 70%. An interesting paradox. Big is not always better.


Many businesses run head first into a digital transformation, with many believing they need to add new technology, when sometimes they need to take technology away. The technology that they employ, like the early steam engine, only partly solves the problem and can’t clear the flood from the mine. Business leaders overthink what they need to do to become more digital.


Some businesses, such as we’ve seen with manufacturers, suddenly decide they can switch from selling to wholesalers and distributors and go D2C (Direct to Consumer), shifting their entire model that way. They’re overthinking it and they fail. What they should do is build an adjacent business model. This leverages their existing strengths while bringing in the new skills and tools that are digital. For the biggest issue with a digital transformation is organisational culture. Digital workforces are very different from manufacturing workforces.


A digital transformation should never be about making massive investments in hardware, software, mobile apps and digital products. But that’s where many will go and it is also where massive consulting firms will want to take them, because that’s good for their revenue.


It should be about going back to the very principles of the business first, understanding the culture, change issues with culture, taking a systems based view. It is the relentless pursuit of adding customer value and being extremely clear on the desired outcomes.


Scaling is the other issue. Businesses think that going digital means going all-in and investing in going too big, too fast. This approach, along with not addressing digital culture, understanding weaknesses in the system and not taking a holistic approach are a recipe for disaster. If a manufacturer takes a disciplined approach to producing new physical products, the same should be applied to digital products, only in an agile and iterative approach. Learn to experiment and adapt first. Find niche successes, then you scale.
Become agile. Underlying success in the digital world is agility. From agile product development to agile governance. If a business is in a traditional physical product sector, the concept of agile to senior management will be at complete odds with how the business is run. That means change at the very top. It’s another reason building an adjacent business model helps. It reduces friction and tension at the executive level, enables experimentation before scaling and avoids unnecessary technology investments and over-spending. Don’t overthink it, find people who can help you think it through logically and systematically.

We also discuss why digital products shouldn’t be created in a silo here.

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