by Becky Frankiewicz and Tomas Chamorro-Premuzic
As The Economist recently noted, one of the most obvious consequences of the current Covid-19 pandemic will be “the infusion of data-enabled services into ever more aspects of life.” We except digital transformation to be an even bigger imperative for organizations in the short-term future.
Contrary to popular belief, digital transformation is less about technology and more about people. You can pretty much buy any technology, but your ability to adapt to an even more digital future depends on developing the next generation of skills, closing the gap between talent supply and demand, and future-proofing your own and others’ potential.
As it turns out, most of us end up in jobs and careers for serendipitous reasons, and stay in them for a long time, rarely pausing to rethink our potential: Am I in the right job? Is my career the best fit for by interests and abilities? Would I enjoy my life more if I had chosen something else? Furthermore, while every job requires learning, we are prewired for familiarity, routine, and simplicity, which is why most of us end up learning less on the job, the more time we actually spend on the job. This is good in the short run, because we can do our jobs on autopilot, freeing up mental resources; yet it’s counterproductive in the long run, because what we gain in experience, we miss in new learning opportunities. An even bigger loss is that we may go through our entire working lives without discovering, let alone unlocking, our true potential. As Winston Churchill once said, we should never waste a good crisis. Perhaps this is the biggest gift of the current pandemic, that it provides us with the opportunity to rethink our potential and ensure that we are positioning ourselves toward the future. To be sure, it is too soon for most people to realize this, yet in the long-term, a significant number of people will likely end up in better careers and look back on their less meaningful and less engaging past careers like someone who looks back without regret on the end of a less fulfilling personal relationship, even one where it wasn’t their choice to exit.
With this in mind, we wanted to provide a few suggestions: some based on science, and some based on our own experiences leading, coaching, and mentoring current and future leaders across a wide range of industries, helping them ready themselves for an even-more-digital future. Our main assumption here is straightforward: While the future is more ambivalent and uncertain than ever, we are confident that a pretty strong bet on the future is to focus on reskilling and upskilling people so that they are better equipped to adjust to change. Just as our past efforts have enabled us to adapt to our more digital and virtual present world (and a non-trivial fact is that we are writing this, and you are probably reading this, in physical isolation), there are few reasons to suggest that this trend will go away or be reversed anytime soon. If anything, an even bigger proportion of jobs, tasks, activities, and careers will find ingenious and novel ways to coexist in the digital world. Here’s how we can all prepare for that eventuality:
Put people first: Technology is always about doing more with less, yet that combination is effective only if you pair technology with the right human skills. Just as technological disruption has generally led to automation and the elimination of outdated jobs, it has also always created new jobs. This is why innovation is commonly described as creative destruction. But the creative aspect of innovation is entirely dependent on people. If we can leverage human adaptability to reskill and upskill our workforce, then we can simultaneously augment humans and technology. It’s really quite simple: the most brilliant innovation is irrelevant if we are not skilled enough to use it, and even the most impressive human minds will become less useful if they don’t team up with tech. The main implication is that when leaders think about investing in technology, they should first think about investing in the people who can make that technology useful.
Focus on soft skills: Just as digital transformation is more about people rather than technology, the key technological skills are soft skills rather than hard skills. Sure, the recruitment market is hot for cybersecurity analysts, software engineers, and data scientists. But as we recently argued in our article, “Does Higher Education Still Prepare People for Jobs?”, there’s an even bigger need for people who can be trained in the next wave of IT skills. Paradoxically, higher education is always playing catch up, because where universities perceive employer demand, they follow up with relevant courses and learning programs, creating a future surplus of talent supply in those areas. In our view, the best way to make your organization more data-centric and digital is to selectively invest in those who are most adaptable, curious, and flexible in the first place. Since nobody knows what the key future hard skills will be, the best action is to bet on the people who are most likely to develop them. Our own talent development philosophy is to combine this dual focus on potential for soft skills, and knowledge for hard skills: we select people with high learnability (people with a hungry mind) and match their interests to in-demand skills, while understanding that those hard skills may soon become outdated — so the key is that their curiosity remains intact. Technical competence is temporary, but intellectual curiosity must be permanent.
Drive change from the top: The idea of bottom-up or grassroots change is both romantic and intuitive, but in reality, change is much more likely to happen if you drive it from the top down. This does not mean that you have to embrace an autocratic or hierarchical structure, or that you need a culture of fear. In fact, it’s a simple matter of leadership, whether transactional or transformational. In the context of digital transformations, the main implication is that you cannot expect big changes or upgrades to your organization unless you start by selecting and developing your top leaders in that vein to begin with. It has never been clearer that leadership — both good and bad — cascades down to impact every single aspect of the organization, with as much as 50% of the variability in group or unit performance being attributable to the individual leader. This is why when we are asked about the single most important factor in determining the effectiveness of an organization’s transformation, our answer is always the same: the CEO or head of the firm. Sure, industry, context, culture, people, legacy, and actual tech all matter, just as resources do. Yet most of these things tend to be rather similar among direct competitors, whereas the mindset, values, integrity, and above all, competence of the most senior leaders will stand out and be the main differentiator. Needless to say, everything in business can be copied except for talent, so if you are looking for impact, do invest in top talent, which is where you will get the most value. The distinguishing feature in the war for talent is always leadership: in-demand skills such as software engineering are what we talk about, yet the key is to find the people who can manage the software engineers and get them to work as a team to outperform other software engineers.
Make sure you’re acting on data insights: So much of the current discussion on data is focused on AI (artificial intelligence), or specific types of computer intelligence, such as machine learning, deep learning, or natural language processing. These powerful advances in AI are exciting, yet we don’t see them as the main differentiator for future-proofing your organization. A much bigger competitive advantage is to harness valuable data, having the necessary skills to translate that data into meaningful insights, and above all being able to act on those insights. In our view, data without insights are trivial, and insights without action are pointless. We cannot overemphasize the importance of this point, because too many business leaders operate under the false assumption that if they hire smart data scientists or buy fancy AI tools, their problems will go away, or they will somehow become more high-tech. The big difference between Google and the rest, between Amazon and the rest, between Facebook and the rest, is not the brain power of their data scientists, or the actual functionality of their technology (and, yes, we may see them as first-in-class), but their radical data-driven cultures. They have harnessed amazing data assets and have great algorithms to interpret (and monetize) that data, but their key strategic advantage and biggest asset is that they live, breathe, and act according to the data. Data truly is their oxygen, and that is something you cannot buy; you cultivate it, nurture it, and harness it with time — and above all, with leadership (back to point 3).
If you can’t fail fast, make sure you succeed slowly: The statements that speed is king, that action is key, that perfect is the enemy of good, and that you should be willing and eager to fail fast, have all become clichés in management thinking. But, the only way to adapt to a constantly changing and rapidly disrupted present is to speed up and operate at pace. Of course, there is always a trade-off between speed and quality, so if you cannot fail fast enough — meaning you don’t have a culture in place that tolerates quick experiments with the view that the lessons learned from those failed experiences will make you stronger and smarter, then you need to be sure that your long-term bets are working out. In other words, it’s okay to succeed slowly if you can’t fail fast. At the end of the day, failure is only a strategy for getting to success in the long run, so if you pick another strategy, that’s fine — just make sure you can actually get there. However, remember that few things breed stagnation and a false sense of security like an obsession with success. Indeed, we often hear leaders rationalize their failures with a self-congratulatory “we have learned from our mistakes,” yet it’s much harder to learn from your successes.
As the last several weeks have demonstrated, we are agile as a global community. This agility has been people-led and technology-supported. Human beings are the common denominator to the concept of future proofing, whether it’s as a compliment to the technology being unleashed for remote working, or whether it’s because we possess the soft skills and leadership needed to navigate a historic crisis, or because we have the insights needed to drive slow success or fast failure for a cure. It all starts with each and every one of us, and those we are responsible for developing. The key is to nurture curiosity, so we have options, even outside of a crisis.
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