Predicting which choices lead to success is difficult. There’s nothing controversial about that. But here’s something that is. Experts are notoriously bad forecasters. That’s not my hot take. It’s borne out of evidence and is occasionally true of even exceptional individuals. Let me present three examples.
- Bill Gates once said that Microsoft would never make a 32-bit operating system. Just three years later, that prediction was in the bin.
- Arguably the smartest person in modern history, Albert Einstein, once said that nuclear energy would never become a usable source of power. That was in 1932.
- T.A.M Craven, the former chairman of the FCC, once predicted that satellite communications would never be a player in the radio, TV, and entertainment industry. A few years later, commercial satellites were launched and completely transformed the marketplace.
The traits of the ‘Super Forecaster’
Essentially, this is a long-winded attempt to illustrate that expertise, no matter how much we respect the individual’s talents, is not a guarantee of forecasting accuracy. Human beings are not good at weighing different factors statistically and measuring likely outcomes in grades of probability. When you ask most people to talk about how they view the probability of an outcome, responses are usually ‘never,’ ‘always’, or ‘sometimes.’ But often, there are many more shades of grey. In fact, it is a unique type of person who is comfortable with those shades of grey and can sidestep the cognitive biases of singular expertise. Those with this unique quality are proven to be statistically better at forecasting outcomes than recognized experts.
There’s a book that I often refer to by Philip Tetlock and Dan Gardner called ‘Super Forecasting: The art and science of prediction.” And within it, they try to explain the role of the ‘Super Forecaster’ and how to identify them. The pair conducted a study that looked at more than 3900 forecasters, none of whom had any specific expertise in the 500 areas they were trying to investigate. But these were also knowledgeable people with above-average intelligence. They found that of these 3,900 people, 2% fell into the category of ‘Super Forecasters.’
So, what makes them different? Here are a few individual traits that embody Tetlock and Gardner’s ‘Super Forecaster’:
• Humble – because they realize the reality of the world is complex
• Not deterministic – they don’t believe in things like fate and destiny
• Actively open-minded – everything is a hypothesis to be tested
• Numerate, knowledgeable, and intellectually curious
• Pragmatic – they are not wedded to any ideas or an agenda
• Super analytical – capable of stepping back and considering other points of view
Strategies for success
However, you don’t need to be a super forecaster to embody this way of thinking. When facts change, we all need to change our perspective on the potential outcomes. It’s important to step back and ask, “what are the things influencing my mode of thinking? And are they necessarily based on the reality of what’s in front of me?”
We talk a lot about data-driven decisions as an industry. And, of course, understanding data is one of the foundations upon which a super forecaster, or even a decent forecaster, is born. But we should also think about how data is approached. Data, in isolation, is not sufficient for good forecasting. History and context also inform how potential futures may unfold. Without that, no one can ask the right questions.
It’s also essential to make sure we’ve got a reflex in terms of evaluating data and the questions that come from that data. For instance, what do the numbers tell me? Explain the deviations? What are my blind spots? Due to my expertise or previous experience, do I hold biases that I’m not evaluating the right way? Am I ignoring opportunities and threats? And what actions can I take?
MediaKind’s experience, insight, and willingness to discover
At MediaKind, we use three principles every day. We use our experience, insight, and thirst for discovery to help guide, motivate and inspire future technology.
Experience: The history of MediaKind has been driven by amalgamating some of the most impactful and innovative smaller global media companies into one single entity, ranging from the earliest digital video compression to the latest, cutting-edge, multi-screen television platforms and network technologies. These shared experiences have enabled us to drive award-winning innovations, establish a pioneering industry heritage, and build strong foundations, powered by deep innovation and forward-thinking experts from the Americas, Europe and the Middle East, and Asia-Pacific.
We have a global, multi-cultural view of the media world imprinted within our DNA. Having equipped organizations with end-to-end technology throughout our history, we have the agility and knowledge to understand how to deal with adversity and enable businesses to become faster, smarter, and more efficient. We are proud of this heritage; it allows us to absorb and be receptive to new ideas and mold them into a single purpose.
Insight: I head up our Channel Partner Program, an ecosystem of over 100 different organizations, many of whom have come to our partner community through our acquisitions. It’s a testament to our Channel Partner Program and the strength of our organization that they continue to be with us after so many years.
Our partners’ voices really matter to us. They provide unique and valuable guidance to our business that helps us collectively assess and reassess how we realize our growth goals and vision. After all, they have the local and regional knowledge and close partnerships with the key broadcasters, telcos, and service providers. By embracing these different points of view and strategic insights from our channel partners, we can provide better support and faster operations – ultimately so that we can deliver the necessary value-add to their clients through our end-to-end portfolio.
Willingness to discover: The final element is our willingness to continue to push boundaries and discover breakthrough technologies that directly benefit the industry. One of the biggest recent examples for me has been MediaKind’s research into the use of Machine Learning for upscaling, specifically adapted to work in real-world video environments.
This work has directly impacted how new UHD services have been implemented, and we have seen this by working closely alongside content owners on a range of content, ranging from movies to sports. The results are difficult to distinguish from native UHD conversion, underlining why this technique provides a substantially better experience than traditional methods. My MediaKind colleague and renowned media technology expert Tony Jones explains more in this blog.
This willingness to push boundaries highlights why MediaKind has continued to complement its rich legacy in the video space by having one of the industry’s largest R&D and innovation budgets. And we continue to bolster it with new and exciting talents. This enables us to continually discover new methods and techniques that drive direct value and shape the success and innovation we deliver to our customers and partners. We may not all be super forecasters at MediaKind. However, we certainly understand that the ability to question the norm, drive innovation in new areas, and be open-minded in the midst of a dynamic market are the best ways to help our community be successful.
