Data-Driven Decision Making and AI: A Risky Business for Leaders
The rise of AI is going to significantly change the role of leaders. But that does not necessarily mean it will benefit innovation, meaningful business, or the well-being of employees, customers, and other stakeholders. Digitalization and Big-Data have already given leaders insights that could help them make better decisions. But instead of ‘really’ making a better decision, in practice, it turns out that they often do exactly the opposite.
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Trends based on the past can be deceptive
I once worked as interim Marketing Director for a large retail chain that also sold suitcases within its huge product range. The purchasing specialist for this product group was not so much a suitcase enthusiast as a data-driven ‘leader’. His data consistently showed that black suitcases were the most popular and would continue to be according to the trend.
When it came to designing the window displays, the layout of advertisements and leaflets, and the design of the online product overview pages, this purchaser naturally also had a say. If it were up to him, every inch of the page would be covered with multiple black suitcases. According to him, the data didn’t lie. But what he did not take into account was the real need of the customer.
What research also shows is that customers prefer a modern, original, and colorful suitcase. That is also what they notice first when walking down the shopping street or when they see an advertisement. But just like with clothes, people see something fashionable and still most often walk away with the standard black dress or blue jumper.
Innovation and distinctiveness require more than past data
The above example is just about the difference between what to stock and how to entice customers. Far worse, people like this buyer stand in the way of real innovation and distinctiveness. The question also arises whether this will change in the future with the use of AI. Because even AI can only make predictions based on the past and is not yet capable of coming up with something original. AI cannot come up with what was not already there.
The unknown and ‘unpredictable’ success of the Smart
In 1998, the trend in the Netherlands when picking a car was to choose a solid and traditional model. At that time, in the Netherlands, that was the choice between an Opel, Volkswagen, or Renault. Each model was available in a number of modest colors and there wasn’t much choice in terms of features. Above all, the car did not have to be too flashy.
What trends, based on data from the past, could never have been predicted was that there was also a huge market for a small two-seater available in the most colorful versions. They called it the Smart. A name that stands for Swatch Mercedes Art. I myself was one of the first to drive it around the Netherlands and was laughed at by many at the time. But the people who laughed then are now themselves driving around the canals of Amsterdam in even smaller and more unusual versions of the Smart. The concept has become a mega-hit. Again, this was something that ‘the data’ could never have predicted.
Leaders who rely too much on data and AI don’t break trends and die
If you keep doing what you’ve always done, you can’t help but expect the same outcome. Lack of disruptive and visionary thinking, therefore, gets many companies into trouble.
AI works mainly by analyzing existing data. That makes its predictive ability based on extrapolating from that data. AI cannot “imagine” something entirely new like a human can.
If leaders rely too much on historical data and its extrapolation when making forward-looking decisions, for example, because of the data-driven insights AI provides, this can hinder innovation immensely. And companies that cannot innovate fast enough and thereby anticipate changing market conditions simply die.
Many leaders and managers have resistance to risk
Through my background as a strategist and marketing & communications professional, I have come across a lot of managers and leaders. Unfortunately, only a few were able to transcend the data and research based on which they could make better decisions.
The times when we made a disruptive proposal but the data could not back it up and thus did not get approval on our proposal are uncountable. Of course, this is not to say that all our proposals could have always been or are a success. What it does mean is that a lot of managers have resistance to the risk and thus (disruptive) innovation and have missed huge opportunities.
When I was still swimming with swimming straps, I thought I was smart as a young boy. I did not yet know the word incremental innovation, but already took a taste of it. Because one day I decided that I wanted to swim without those swimming straps, but swimming in one go without the 2 swimming straps was also a bit exciting. So, I made the choice to take one off first. I took a big run-up, jumped as far as I could, and the rest you can imagine.
This is exactly how many traditional managers and leaders prefer to approach it as well. A bit of the new and a bit of the old. Usually, that ends as badly as it could have ended with me had it not been for a vigilant mother who dived right in after me.
Big data and AI are resources, The leader is the steering wheel
For fear of their jobs, making mistakes, losing face, or simply for lack of creativity, most leaders and managers continue to do what they have been doing. If they don’t decide to get at the steering wheel themselves and continue to rely completely on data, they will drive straight into the abyss. Big data and AI are fantastic resources, but they are no match for human visionary thinking.
Right now is the time to think outside the box and come up with new solutions to the problems that arose in the past. The world is in crisis everywhere and inflation is skyrocketing. If leaders stay focused on past data, they miss the shifts in consumer behavior and emerging trends that have emerged from this crisis.
It is actually just like with investments. Past results do not guarantee the future.
A leader of the future to take an example from
I have had the privilege of working with people like Steven Bakker for decades. A person who naturally understands the perfect balance between automation and data and intuition and vision.
In the mid-1990s, for most entrepreneurs, internet sites were luxury ‘business cards’ for the occasional ‘geek’ who had access to the internet. Above all, one shouldn’t invest too much time and energy into them because the data indicated so. Steven Bakker, with his then three small computer shops, thought otherwise. Thus, the first online computer shop in the Netherlands with a shopping basket was born.
A few years later, data based on research showed that a concept like ‘same-day delivery’ could never exist. That would simply be too complex and expensive and people weren’t interested in it. So Steven started ‘same-day-delivery’ with its then 16 shops. To reinforce the concept, he bought five Ferraris and, if the customer was lucky, the parcel was delivered in the Italian sports car and he was allowed to take it for a spin. Those were the days!
The examples with which Steven has been successfully disruptive with his vision are numerous. With his current new venture New Black, too, he is setting the market alight, but now worldwide. New Black, whose slogan is “cut the crap”, took on the biggest players in the market like Salesforce and Oracle as an underdog with a completely new approach to Unified Commerce automation.
New Black’s Unified Commerce Platform is now running at thousands of retailers, outperforming almost all ERP, CMS, POS, CRM, BI, and PIM functionalities. Consequently, they now work with almost all the major players in this field of expertise. Why? Because the traditional players trusted the data and kept doing what they were doing. Steven and his team let the same data and facts speak for themselves but only used them to turn vision into disruptive action.
Simply put, New Black’s ‘trick’ is as simple as it is visionary. All traditional systems are developed on the premise of streamlining processes and controlling employees. On top of that, new systems are built – or plugged in – to enable customer satisfaction. By reversing this approach and developing a platform that prioritizes and serves the customer, you get New Black’s Unified Commerce Platform.
Conclusion: I don’t believe that Big Data or AI can surpass the human ability to innovate disruptively in the short term. Perhaps in the long run, it will, but we haven’t reached that point yet. So that means we need more people like Steven to turn the worrisome prospects of many a company into opportunities. The only question is: Who dares?