“Set yourself to becoming the best-informed person… on the account to which you are assigned. If, for example, it is a gasoline account, read books on oil geology and the production of petroleum products. Read the trade journals in the field. Spend Saturday mornings in service stations, talking to motorists. Visit your client’s refineries and research laboratories.”
David Ogilvy (1983)
In this quotation, marketing icon David Ogilvy highlights the need for a deep and direct understanding of a problem in order to develop an effective solution. He emphasises the importance of immersion, attention to detail and engaged passion. This edition examines why his approach to problem-solving was so successful, and why it has been in decline over the last twenty years. It highlights how the search for ‘real world’ understanding has been replaced by ‘artificial’ and ‘constructed’ views of the world, simulacra. It identifies that the problem of artificiality is becoming more acute with the growth of AI, with its introspective forms of learning. Finally, it explores the adverse consequences of this change on how we view the world and shares some ideas to reverse the trend.
Ogilvy’s quote captures the three dimensions of deep and direct understanding: the immersion of spending ‘Saturday mornings in service stations’, the attention to detail, of reading ‘books on oil geology and the production of petroleum products’ and the passion of ‘becoming the best-informed person’. Ogilvy’s approach underpinned the creation of one of the world’s largest and most respected advertising agencies (and the highest valued at $864m in 1989) and led him to be regarded as ‘The Father of Advertising’, a man who shaped the entire industry. His biographer Kenneth Roman stated, ‘Notwithstanding a reputation as a creative genius, his defining characteristic was as a leader. He articulated and inculcated principles of management’. The origins of the NHS were based on the same principles. When Aneurin Bevan stated, ‘No society can legitimately call itself civilised if a sick person is denied medical aid because of lack of means’, he was talking from direct experience of the working man. He knew in detail what illness meant, it ‘is neither an indulgence for which people have to pay, nor an offence for which they should be penalised, but a misfortune the cost of which should be shared by the community’. Tim Price, in his play ‘Nye’, captured the passion of the founder of the NHS when he gives him the line: ‘I don’t want to help you survive. I don’t want to give you medical care. I want to give you your dignity’. The same principles underpinned the innovative years of Apple as a product design company. Jonathan Ive described his design philosophy as focused on a ‘fanatical attention to detail’ and said ‘coming across a problem and being determined to solve it is critically important’. The passion is evident in the commitment of the Apple design team; as Ive said in 2014, ‘in the last 15 years, not one of the 18 designers has ditched Apple for greener pastures’. The power of the approach used by Ogilvy, Bevan and Ive lies in its analytical and emotional depth. It shifts attention to specific problems in context, it allows for nuance, it responds to the changing nature of problems, and it can draw solutions from practical ideas already in place and proven. As an approach, it is also emotionally engaging, it emphasises involvement, two-way communication and demonstrates most importantly, a sense of care. As Ive stated, ‘what we make testifies who we are. People can sense care and can sense carelessness. This relates to respect for each other’. This component of decision-making is often seriously overlooked, with significant adverse consequences.
Despite the proven effectiveness of this decision-making approach, it has been replaced over the last twenty years by a diametrically opposed model. Instead of solving problems based on ‘real-world’ data, decision makers increasingly rely on ‘constructed’ views of the world, which sufficiently resemble the ‘real’ as to be deceptive, but are actually incomplete and sometimes false. Baudrillard, who developed the idea of ‘artificial’ worlds, which he called simulacra, argued they emerged through ‘four successive phases: the image first reflects a basic reality; then masks or perverts that basic reality; then masks the absence of a basic reality; and finally, the image bears no relation to any reality whatever’. Debord argued that the emergence of ‘artificial’ views occurred across many fields of human activity. In addition to decision making, he identified the conversion of tangible consumer products into intangible brands, and exploration and travel being replaced by theme parks. Critically, the ‘artificial’ views embedded into problem-solving emerged largely unnoticed. Mäki has highlighted that the problem was partially the consequence of increased use of economic models, which lacked ‘resemblance’ and, as a result, ‘economic inquiry (became) predominantly a matter of examining the properties of those imagined systems only’. In turn, business organisations began to use management methodologies which simplified and standardised the view of the world, which were supposed to be applicable in any country or culture, and which could be deployed rapidly, often with limited training. The resulting high level of ‘artificiality’ was further compounded by the increased use of spreadsheets and other digital tools. This allowed managers to build complex and dynamic views of the world, based on limited and abstract data that often excluded information concerning moral values, social context and emotions. The extent of this transition is captured in the film ‘War Games’, a simulacrum of war, where the characters are prepared to uncritically use games as stand-ins for reality (which reflected certain aspects of the US war planning in the 1960s). The result of this ‘artificiality’ is that nuclear war becomes seen as both conceivable and winnable, as the nuclear strategist Thomas Kahn argued. This terrifying idea, in the film, suddenly becomes a reality when the computer running the games gets control of the actual missiles. In the end, it requires real people living in the real world to stop the nightmare by teaching the computer deterrent theory, and that ‘the only way to win, is not to play’.
Relying on ‘artificial’ constructions as a stand-in for the ‘real world’ data creates three risks. The base data sets lack granularity; interpretation rests on perspectives that are disguised as objective truth, and the degree of bias, which is inevitable, is not explicitly understood and discounted. The net effect is to reduce the probability that any proposed solution would work. Furthermore, even if the answers were ‘right’, the dialogue, empathy, and trust that are not built up when developing these ‘artificial’ constructions, especially compared to an immersive approach, create an additional risk. The ability to persuade people to change their minds and behaviour is significantly reduced. The result of reliance on ‘artificial’ models compared to direct contact can be seen in US politics. In recent years, Republican politicians have made deliberate and repeated attempts to be where the people are. For instance, in 2024, nearly 75% of GOP Congressmen held in-person town halls. For the Democrats, the figure was only 58%. This has been a sharp decline. In 2020, there were 1,992 Democratic town halls; by 2023, the figure was only 685. Today, these issues of ‘artificiality’ are compounded by the use of AI, with its introspective form of learning. The tendency of many AI platforms to be trapped in their own self-referential data is exemplified by the Galileo test. In this experiment, an AI platform was trained on the data that was available to Galileo when he wrote ‘Dialogue Concerning the Two Chief World Systems’ to see if the AI could make the same discoveries he did. They found that the AI consistently argues that the Earth, rather than the sun, is at the centre of the Solar System. The AI was incapable of profound, insightful thought and was only able to regurgitate what it already knew. This test suggests two risks with AI platforms: that they will create ever more complex ‘artificial worlds’, but the models will not be able to identify inconsistencies in their own conclusions or develop insightful, original answers.
Pushing back on these trends will be challenging, as ‘artificial’ worlds are now well embedded into decision-making processes. Furthermore, problem solving based on ‘artificial’ views is often simpler, less complex and less risky than ‘real-world’ problems and shifting back to real-world approaches would require additional expense and time. In addition, decision makers would need to ‘get their hands dirty’ and spend more time developing more customised solutions. However, failure to do so will result in organisations that are unable to respond to real-world problems, to address people’s aspirations, and apply technology effectively in the same way that Ogilvy, Bevan and Ive successfully did in the past. Artificial constructions of the world can be interesting and stimulating, but it is important to take care with them, and not to confuse them with the real world, its real problems, and the real, practical things that we can do about them.
The Archive of Free Thinking 
Leave a comment