Introduction
Welcome to The ContraMind Code.
The ContraMind Code provides you with a system of principles, signals, and ideas to aid you in your pursuit of excellence.
The newsletter shares the source code through quick snapshots for a systems thinking approach to be the best in what you do.
The Code helps you reboot and reimagine your thinking by learning from the best. It also enables you to draw a blueprint for what it takes to get extraordinary things done. You can share your valuable thoughts and comments and start a conversation here.
Take a journey to www.contraminds.com. Listen and watch some great minds talking to us about their journey of discovery of what went into making them craftsmen of their profession, to drive peak performance.
Should Tech Run The World?
Some articles may not be long, but they can create the impact of a long article in just a couple of lines or paragraphs.
One such article with this headline by Dave Winer on scripting.com got our attention!
Dave argues emphatically in his blog that, with all due respect to the tech industry, he questions why the traffic in the Bay Area is so awful. He also asks a hard question as to why they have not done anything about it! And he says, being a programmer himself, he wouldn’t trust an algorithm without a lot of QA!
His thoughts can prompt you to think more about this!
Read the entire article here.
Do Marketers Need To Think Like Engineers?
WARC’s David Tiltman is in conversation with Sorin Patilinet, Marketing Engineer at PepsiCo, who has also recently written a book on Marketing Effectiveness.
Sorin calls himself an effectiveness engineer!
Sorin makes an interesting point that many Marketing Mix Models studies have found the impact of media to be only between 5% and 10% of a typical brand's sales during a given year. He says most marketing departments across the world have focussed too much on communications or campaigns alone, while marketing as a function has a larger context across a company and an opportunity to drive the effectiveness of marketing spends.
Sorin says introvert, data-driven marketeers are the ones who are winning! He says we need to make effectiveness interesting!
The best marketers are those who have a deep understanding of the customers they serve. Sorin believes that one of the challenges companies face is the explosion of non-working media costs at the expense of working media. He says that while the definition of marketing effectiveness remains the same, the approach, the implementation, and the transition from insights to applying a specific insight within an organisation's culture will have to be entirely different.
You can listen to the entire episode on:
Software Is Eating Labor.
In this video, Alex Rampell, General Partner at A16z, discusses a very interesting trend that software companies are adopting - they are all targeting the labour market.
Alex traces the history of software beautifully and builds his narrative for this position, mentioning that the worldwide SaaS market is $300 billion per year, while the labour market in the US alone is $13 trillion.
The transition from traditional software license-based revenues to outcome-based revenues is what Alex confides these companies must move into as AI takes centre stage.
The real challenge, despite this narrative sounding compelling, is that the outcomes may not be linear as expected. There are many handshakes and physical interventions that may be required within an organisation, which are beyond the scope of the software or the agent. How agents are integrated into physical and digital workflows will make a significant difference to this narrative and will determine value creation for software or technology companies of the future.
You can click on the above link and watch the video.
More Tools Don’t Mean More Output.
David Winer’s article set us to reflect and think!
With over one million tech professionals in Bengaluru, it is the same case with Bengaluru, often touted as India’s Silicon Valley.
With the numerous tech tools and platforms we have been using (and more to come with AI) over the past few decades, has personal and company productivity or output actually increased?
We still discuss long, unplanned working days, organisational silos, unending meetings, last-minute product launches, and presentations, as well as a lack of data-driven decisions, poor service turnaround times from companies, and work chaos, despite the use of task organisers, calendars, schedulers, and various types of software.
Therefore, more tools do not mean more output!
Interestingly, Erik Brynjolfsson, in his paper at MIT, pointed to a productivity paradox—the visible tech boom hasn’t translated into consistent productivity gains.
In 1987, Prof. Robert Solow famously asked, “You can see the computer age everywhere but in the productivity statistics,” which led to the famous Solow Paradox (1987). This remains partly true when examining organisations even today.
McKinsey estimates that 61% of employee time is spent on communication and coordination, not on deep work or creation.
As recently as 2022, the Harvard Business Review estimated that close to 2.5 hours are lost due to tool fragmentation and searching for information.
Here are some of the real challenges for you to overcome, if you want to beat the tech hype and not be swept by the tsunami and chatter that happens with technology disruptions once every couple of years:
Learn to understand context - Often, tasks are completed without proper context. What is context? Context refers to the circumstances, background, or setting in which something exists, happens, or is understood. It provides the frame of reference that gives meaning to words, actions, or events. Context requires you to examine whatever task you do from a cultural context, linguistic context, situational context, historical context and business or company context.
Peripheral knowledge will no longer suffice - Most tools will automate and leverage on top of your domain knowledge. These tools, platforms, or agents do not come with the context and knowledge you will have. You must have the ability to prompt them intelligently and have the ability to fine-tune and direct generic agents and algorithms. In fact, most problems or information will be deciphered and made available to you in a pre-prepared state, say at a 50% or 60% level. It’s your deep expertise and knowledge that can take it to a 100% level. More and more information( not knowledge) will become accessible to all. It’s only the top 10% -20% of people who will be able to convert information into knowledge and actions. In fact, your ignorance or lack of knowledge will be amplified in the age of AI. It will compel you to engage in deep work and develop expertise. Those who don’t will have very little future.
‘Time to Adapt’ is often underestimated - It is always believed that a tool or tech platform will solve the problem. However, it is the humans or the people you work with who take more time to adapt. Ironically, people don’t accept that they don’t understand or agree that they don’t know. Their attitude and fixed mindset are the most significant barriers. It may be due to the fear of being seen in a poor light in a group meeting, fear of losing the job, or external pressure to act as if they have understood and know it. Many of these behaviours ‘slow’ outcomes or output. Hence, time is wasted in countless meetings, reviews, and so on. Fundamentally, what needs to be done is not clearly understood, largely due to insecurity, ego, and ignorance. Your ability to spot this, make people comfortable to express their ignorance, and your skill in explaining the context and principles will be as important as the tools themselves. If you are a manager or leader who primarily manages people’s time and coordinates tasks, you are at risk of becoming irrelevant to your teams and companies.
The nature of work is changing as jobs are becoming less linear and measurable. You must learn to think, design, and persuade effectively using these tools. They can never replace your thinking, expertise and contextual skills.
Some of the lessons we learnt from this week’s mission:
Just technology tools and algorithms alone don’t solve business problems. Never trust any algorithm without a lot of context and QA.
Marketers need to think like engineers and vice versa.
Software platforms will be forced to transition from a user or seat-based pricing model to an outcome-based pricing model.