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I first conceived of the idea of a Brain Based Enterprise (BBE) in the shower while writing the book Leading Innovation, Creativity and Enterprise. To be completely correct I was in the shower thinking about the book rather than actually working on my laptop. Perhaps this will be possible in the future to capture those creative moments! Anyway a pithy definition helps begin our exploration of the BBE:
A Brain Based Enterprise (BBE) is an enterprise that encourages people to bring their heads, hearts and souls to work.
You might well ask “why not just their brains?” Well, we need a wider palette of intelligences as mentioned: IQ, EQ and SQ as we shall discuss later. Arguably, however, our basic IQ will be less important than our EQ and SQ in a world in which much of the analytical work will be automated. We might, however, need much higher IQ skills to process the data and information, which machines will process on our behalf. A BBE is characterised by:
1. A happy marriage of people’s passions, the enterprise’s purpose and profitable outcomes, be they measured in financial values for a profit-seeking enterprise or social good for a non-profit-seeking one, be it a public or social enterprise.
2. An enterprise that maximises talent, in terms of leveraging people’s abilities to use knowledge, skills, experience and wisdom. This is reflected in every way through the attraction process, the development of people to become continuous learners and the use of machines and AI to augment human endeavour for maximum effectiveness.
3. Teams that collaborate through sharing knowledge, insight and wisdom where it is often impossible to achieve the enterprise’s ambitions by working alone due to the complexities of innovation and the need for skills not normally resident in one individual. A good example is the United Nations Weapons Inspectorate, where sadly, due to the complexities of modern weapons, they need people who are experts in physics, computing, bioscience and other disciplines in order to have the relevant knowledge and skills to be effective.
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4. An obsession with innovation as a modus operandi and a relentless thirst to never let today’s successes become tomorrow’s plateaux. Essentially to increase the churn rate between ideas and innovations, what we call the ROI (Return on Innovation) or what Arthur D. Little call ‘Next Practice’ over ‘Best Practice’.
5. An open systems approach to the enterprise’s boundaries. In some cases people will be collaborating with others who are not on the payroll and who are motivated by different things than that of the host enterprise. Brain Based Leaders must therefore be adept at motivating people who work for a mix of motives: staffers, freelance gig economy workers, volunteers, customers and possibly competitors.
6. Leaders who harness diverse talents and personalities and blend their skills in pursuit of the enterprise’s aims while giving meaning to the thing we call work.
7. A culture that encourages productive synthesis of human- and machine-led endeavour and not a War of the Worlds approach to technology adoption and augmentation.
At an individual level, the atoms of a BBE are the people. Unless we get the atoms right we will not be successful at building molecules (teams) and macromolecules (enterprises). The field of study that we call Organisation Development begins from the ground up and we therefore begin by looking at individuals and intelligent contributions at a personal level before examining teams and the whole enterprise.
Brainy people
Our notions of what makes a brainy person will change in a world where we will not need rote memory in terms of recalling facts and data. However, all of us need a mental model of the area we are working on in order to be able to synthesise knowledge. So, recall and connectivity become more important than memory per se. My two sons are ‘learnatics’ with a great thirst for learning. As such they offer me a great stimulus to my own learning, as do all children. They constantly challenge my ideas and this helps me stay young. One day they pointed out that IQ has dropped by 13.35 points in the last 100 or so years and asked me “Will IQ be superseded by Q in the James Bond sense of the word?” I took this to mean something around the question is formal intelligence as measured by IQ tests the model form for the future? I would argue that as we mechanise there is an even greater need for those things that humans do so well if we are to coopete with machines. While we can probably design algorithms for humane qualities such as empathy, compromise, creativity, etc. nobody does it better than a human being.
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Yet, their example points out that much of the essential knowledge required to function at work and in life is already codified on the Internet. This codification has taken place over the last few hundred years from the development of the first printing presses. Printing made it possible to write down instructions for things as simple as baking a cake to waging war. It has accelerated considerably with the advent of computing power and data storage. The noun ‘Google’ has become a verb and the question facing many people these days is ‘To Google or not to Google?’ The goal of learning becomes one of harnessing the plethora of data we collect and converting it to information, knowledge and wisdom. Yet, we are stuck in a rut of believing that education is about our abilities to retain facts, when most of the facts we need are available at our fingertips. In a world where we are drowning in data, how shall we learn to swim with information? We will need to make some significant shifts or upgrades in some familiar and some less familiar skills:
• To search for facts in a jungle of data. Asking more questions than seeking answers.
• To separate what really matters from what is shouting in our face. To pick out key information from gigabytes of data.
• To notice the difference between causation and correlation.
• To separate the important from the merely urgent.
• To look for connections between disparate pieces of information.
• To let go of the notion that we must know everything and replace it with the notion that we can know how to know everything we need to lead fulfilled lives.
• To take seriously the idea of continuous learning and a PSP (Personal Sanity Plan) covering IQ, EQ and SQ. Darwin’s notion of survival of the fittest will take on a new importance in terms of mind, body and soul fitness.
If Continuous Personal Development (CPD) is vital for success, it helps to take a brief history lesson on the topic. Back in the day, I used to belong to the CIPD and took CPD very seriously, using a wide variety of methods. On reflection it seems that I was in a minority of about 10%. I recall that those of us who wanted to improve ourselves through learning even suffered subtle social disapproval from more casual members who thought that learning was for dummies. This will no longer do in the automation age. In short Bill Gates was right when he said, “Be nice to nerds. Chances are you will end up working for one.”
Peter Cheese provided me with some insights on the issue of CPD. Alongside the declining half-life of products, services and enterprises themselves, the upskill/reskill cycle will be much more frequent and this will require those enterprises to develop people not just for their current occupation but also to prepare them for the next one. He sees three levels of skills needed for the future:
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Employability skills: These include literacy, numeracy skills and the notion of resilience in order to manage a career, which might span several changes of focus. The ability to market yourself will also be very important in a world where we work globally. We discuss the issue of personal and collective branding later on in this book.
Core skills: Examples will include digital skills, risk, basic financial understanding for starting businesses, learning to learn – how do you develop someone’s capacity to learn? We discuss this under the heading of learnacy later on in Dialogue I.
Emotional intelligence: For example critical thinking skills, empathy and the ability to relate to people. Again, we pick this theme up under our review of seven intelligences for the future.
I can Google any subject under the sun and I get tens of thousands of references, but then I must apply critical thinking to the information. This also throws up the question of what do I actually believe in a post-truth world?
Peter Cheese
Perhaps the one skill that humans have also been good at will become the most essential of all – that of “sceptical questioning” or “critical thinking”. It often baffles me when I see people re-tweet or post clearly nonsensical information or “news” to others in the social media world. These individuals never seem to stop and think to themselves – “can this actually be true?”
The old cliché of a lie being able to “travel half-way round the world before the truth has got out of bed” has never been more apt. So in a professional world where a lot of data is going to be presented pre-organised, visualised and perhaps even qualitatively assessed by machines, the ability to stop and calmly think could be the most powerful skill of all. And that is not necessarily an easy one to learn.
Simon Warren, MD, CaseWare
How then will we augment our humanity with AI? I went in search of some clues . . .
Artificially intelligent?
We are entering a world where machine learning is a reality. In this respect Google is an Artificial Intelligence company. Google Translate used to operate on a principle called phrase-based translation, which offered me great amusement from time to time as people attempted to translate my articles from Russian into English using Google Translate.
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TABLE 3.1
While writing this book, Google Translate was replaced by the Google Neural Machine Translation system (GNMT). It achieved much better translations by inventing its own language. The important transformation here was that the software actually learned to make the translation process more efficient. I have still not yet been tempted to pass my article back through the software for fear of some new transformations of meaning. My colleague, data genius and author Jason Bell also tried an experiment to see if AI could write a book. He said:
It turns out that it’s not that bad but very rough around the edges. TensorFlow is better at some things than others. This is one of the positives. However, the training took all night on a modest laptop. Text generation takes a few seconds, so an 11,000 word novella in less than two minutes is do-able. Does it make any sense or have flow? Not really.
Astra Zeneca’s example earlier on shows us one view of what is possible from technology and AI. Yet it is well known that human beings do not always act in accordance with their own best interests in questions of personal development and health. Turning our attention to financial services, the following example shows us what is starting to be possible in a world of augmented intelligence. In this visit I went to meet Simon Warren at CaseWare to find out how AI is, and will continue, affecting business (www.caseware.co.uk). CaseWare is devoted to helping accountants do a better job by innovating in the space of accounting software used by accountants and auditors throughout the world, for auditing, financial reporting, management reporting and taxation. The business has been developing cloud-based applications for about four years and one of the primary missions behind this project is to design software for a ‘data-driven audit’. This means adopting automation, machine learning and AI wherever possible to eliminate the areas of inefficiency and risk throughout the audit process.
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In the accounting sphere it is still early days for machine learning, but there are probably two distinct areas where artificial intelligence can make significant differences to the general auditor or accountant. Firstly, in the area of data transfer/exchange between systems and secondly in making sense of unstructured data, finding patterns and drawing conclusions from that information.
Data exchange can be a very simple and logical process but it is tricky to apply the solution without an agreed global “taxonomy” that labels similar things with the same name. Despite moves to use a common dictionary people place things in different areas and “label” them differently. Machine learning could solve these issues by being able to “learn” from the behaviour of users. CaseWare is doing this with its core cloud platform, under the name of “Automapping”.
Secondly, AI can be used to make sense of the very scruffy world of social media data, professional articles, half-baked journalistic opinion, etc. This is important, because one fundamental aspect of any audit is the “Understanding the business” phase of planning. This is not just about understanding what the business actually does (or how it does it) but also what else is going on in the same industry, and perhaps what are others saying about the business or sector. If AI was to really be able to make sense of this noise (and ignore the load of “false positives”) then we could solve another key audit challenge – the identification of risk. Audit risk is a concept that the general public misunderstand, believing it to be about the risk of mistakes, risk of a business getting things wrong, etc. This is the risk that the auditor fails to spot a significant mistake that could undermine their conclusion that accounts present a “true and fair” view of the business’ performance. Failure to get this right can, and has, resulted in serious lawsuits.
So risk is close to an auditor’s heart, and only AI can possibly hunt through all of the information available to a modern reader and attempt to identify potential risks. Obviously this was something that accountants relied on years of experience to be able to do at a senior level.
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But, and here’s the kicker. What if a firm of young ambitious accountants was to deploy all the technology available to them to shortcut and automate their work? They could undercut fees dramatically and actually spend more time advising their clients rather than simply meeting regulatory requirements. That is the potential disruption that AI could bring to the professional world.
Simon Warren, CaseWare
Embedded in Simon’s final reflection is the decision as to whether given enterprises will adopt the Man-Machine strategy or any of the alternatives, including Planet of the Apes. While it seems obvious that it would make sense to adopt technology, I recall that lawyers refused to use a fax machine or e-mail for many years, so maybe this is not such a no-brainer. If we are to hand much of this work over to machines, what then counts for intelligence?