Insight

What makes this a time of disruption?

Every generation has had its share of shifts and disrupters.

5 years ago really saw the coming of age of cloud to make SAAS a reality.

10 years ago it was mobility and social impacting the way we worked and played – changing retail forever.

15 years saw the emergence of platform businesses such as google and Amazon – creating one of the most significant transformations in business model for a century.

20 years ago was Y2K – in the end a non event but creating a huge update on the financials and technology.

25 years ago was email and ERP changing the way Business was done. This paved the way for standardized processes and the creation of supply chains and ecosystems.

All of these had a significant impact on business, in the day and ongoing. (And all had started well before the year I mentioned)

So why is now the age of greatest disruption?

It is the convergence of all the shifts noted above with the coming of age of AI, the introduction of 4G moving to 5G creating the Internet of Things, the changing expectations of consumers and the connecting of regulation around the world that makes this a momentous time. All of this means that businesses are compelled to address their business model in order to survive and thrive.

Voice on AI, Eye on AI

Recently I posted about AI not being for fast followers. ( see post from May 6).

At the risk of ‘I told you so’ see below an extract of a post today from Jonathan Vanian of Fortune – saying the same thing.

Great minds think a like or ….

“Executives who are afraid of long-term commitments should avoid artificial intelligence.

Like with romantic relationships, using the technology requires an appetite for hard work, planning, and patience. Even then, failure is a real possibility.

“If you are not going to make this investment for the long term, it is not a good idea to do machine learning,” LinkedIn’s vice president of artificial intelligence Deepak Agarwal told Fortune in a recent interview.

Agarwal leads the social network’s many machine-learning projects that power tasks like recommending job openings to users or determining which posts are the most relevant to them and that they are most likely to click on. He’s been involved with machine learning and statistics for years, after previously working at Yahoo and AT&T in senior technology research roles.

One thing Agarwal has learned is that it can take at least a year to see a financial return from machine learning. During that time, companies must navigate the mundane work of cleaning and properly labeling data, and figure out the correct machine-learning algorithms and data infrastructure to use.

Agarwal recommends that small companies, which often have little data, make an effort to collect it before implementing machine learning. Without a large archive of information, the technology is nearly useless.

For some companies, machine learning makes no sense because it requires a lot of computing power to crunch the data. And renting cloud computing infrastructure can cost more than any additional profit that machine learning can create, Agarwal explained.

But when the technology works, the payoff can be huge. For large companies like Google that have embedded machine learning throughout their businesses and apps, a modest 2% improvement on a particularly important metric could result in financial gains in the hundreds of millions of dollars.”

Who are the biggest private employers in the USA?

The answer might surprise you.

Number 1 is Walmart – but the next eight are the major private equity houses through their vast holdings in investee companies. Think the likes of KKR, Carlyle, Blackstone, TPG etc.

It demonstrates the huge shift we are seeing in capital markets – a shift away from public companies to private organizations.

In addition, thanks to Geoffrey Garrett The Dean at Wharton School, the graphs below show that more companies are owned by PE than publicly listed.

The second graph shows that the value of publicly listed is greater, however this will most likely change over time.

The rise of ‘wealth’ funds of all kinds – sovereign, PE, mutual, hedge etc – is fueling this change.

In addition, the move to quarterly reporting and monthly benchmark of returns is accelerating the move away from public companies.

Publicly traded organizations have had to focus on short term results – no longer being able to look at longer term strategies.

Ironically, this a complete flip from ten years ago – now if you want to invest long term or restructure, being in PE’s hands is a better place to be.

#privateequity #PE

Angst that AI will take our jobs ….

There is huge angst about AI taking over human jobs – with talk of 30%-40% of roles disappearing.

What if we were to reframe the discussion and look at it a different way?

What if we were to look at it as an opportunity to really enhance human capabilities?

To look at it in a way that says AI will take away the mundane aspects of our jobs but increase the need to bring the human capabilities of creativity, problem solving, collaboration, driving social purpose and communication.

I firmly believe that AI will create opportunity to do more, enjoy more, be more productive and to live more purposeful lives.

We know that increasing productivity creates wealth and in turn creates more and different jobs.

Every technological change has brought similar cries of job loss – the computer was going to take away jobs, that the ERP wave would eliminate significant parts of the workforce and the internet would eliminate significant numbers of workers.

However, every time, productivity has improved, mundane aspects of work have been eliminated and new roles have emerged. The take up of AI will be no different – it should be seen as an opportunity rather than a threat.

Below is a link to a recent Deloitte report that takes on the view of reframing the way we think about AI.

https://www2.deloitte.com/content/dam/Deloitte/us/Documents/human-capital/us-human-capital-flipping-the-narrative-toward-brighter-future-of-work.pdf

How do you compete with digital natives?

The No.1 issue for most business executives is ‘the sustainability of their business model’. In other words, they are asking the question ‘is my business model going to be disrupted anytime soon?’

They point to Uber, AirBnB, Amazon etc as great examples of new business models and talk about transformation to a ‘platform’ or ‘flywheel’ model as an imperative.

The trouble is that the companies mentioned are digital natives. They didn’t transform their business model – they were always online platform models . They transformed their industry but not their own model.

Finding organizations that have completely flipped their model is difficult. A lot have transformed components of their businesses through acquiring or developing digital components that impact the customer experience or make them omni-channel rather than purely physical.

So the question is, ‘do you need to completely transform your model?’ The answer? It depends- depends on your industry/sector/business and who your are competing with.

A number of organizations are doing incredibly well by taking on the challenge of a disruptor.

They understand the need to transform but also understand:

– what part of their organization they need to transform to compete, and

– how to leverage their traditional strengths and competencies.

Walmart is a great example. You could argue that they had more to lose than most from the rise of Amazon. Yet, they set out to bring technology into the heart of their business and become truly Omni-channel while leveraging their huge strengths of store coverage, distribution network and buying power. The acquisition of technology and platform businesses into the Walmart business has been successfully achieved.

We’ve moved from big data to big A!

IMG_0135

So what does the A Stand for?

The companies that are thriving are the ones that get a lot of users and data – but what sets them apart is their Algorithm. Companies such as Google and Amazon use their algorithm to personally tailor the site or offer for every user. This makes them far more effective than companies that display the same site regardless of the data and (often uncurated) knowledge they have of their customers.

Amazon is the most effective at this – constantly looking at what you’re shopping for and displaying the most relevant products. They are also scouring the net to make sure they are providing the most competitive pricing.

Facebook, Instagram, Google are all strong and improve their algorithm all the time. Never resting to ensure they can get even the smallest incremental benefit by improving their algorithm.

Clearly it is easy to think about online companies when we talk about tailoring the offer or product. But this approach is just as relevant for all companies – creating dynamic segmentation to ensure you are always tailoring your offering or taking a service or product to customers with similar characteristics.

This isn’t new – it’s just with AI/Cognitive techniques and huge amounts of data – it can be done far more effectively and tailored to a target audience of one.

Not all new age companies are good at it – but that’s a story for another day.

Where is the value in your organisation? 

  
IBM has just spent $2.6bn buying Truven Health – a big investment and one that is all about the acquisition of data (and customers). 

Increasingly organisations are seeing that the real value in an organisation is in the data assets – with the ability to use analytics to get rich insights from large data sets. The smart organisations are using analytics and big data to truly understand customer behaviour, value levers for an industry and value points in the supply chain (amongst many other things) to put themselves in an advantaged position. 

So the things that we have for so long called ‘intangible’ – such as data, customer contacts and relationships – have become the most tangible in determining value. 

The challenge for organisations is to ensure that they are capturing and curating the data and intangible assets that sit within their systems and processes and then using the analytical tools to extract the value. 

See below a link to an article in Fortune on the IBM acquisition. 

Why IBM Is Dropping $2.6 Billion on Truven Health