Digital skill sets are important, but “soft” skills such as interpreting data and effectively communicating its insights are even more valuable.
In the recently published MIT SMR- and Deloitte-authored report on digital business, “Aligning for a Digital Future,” we emphasized the importance of attracting and retaining the right talent to compete in an increasingly digital business environment. In order to better understand these trends, we spoke with Professor Prasanna Tambe at NYU’s Stern School of Business about some of the current myths involving digital talent.
One misconception is that all jobs are becoming more digital. In our conversation, Tambe noted that it’s a bit of an open research question as to how many jobs are going to become more technical. At the same time that digital technologies are becoming more critical to business, they are also becoming consumerized. In a sense, employees don’t need many technical skills to work with many new, emerging analysis tools. Users can “drag and drop” and the analytics platforms themselves are going to be able to do much of the analysis for them. “I think it’s an interesting open question about whether or not people in sales or accounting, for example,” Tambe told me, “are actually going to need to have technical skills even if they directly work with data.”
This question remains open because of two competing forces. First, the pace of technological progress is not slowing down; there’s little doubt that the business world is becoming more digital. Second, the infrastructures that we use these days require not only technology skills, but a blend of capabilities like statistics and domain expertise. It’s not yet clear what the right blend of skills will be for future workers. Universities and companies face a very large dilemma about how to educate and train not only the people who are currently in degree programs, but also those who are already in the workforce.
Another misconception is the need for digital skills moving forward. There is a sense that the growth of technical work may actually be amplifying the importance of the “soft” skills — such as effective communication and collaboration — and those sentiments are increasingly echoed by employers. It’s not enough to just know SQL; successful technical workers also need to understand organizations and teams well enough to move forward once they have a data solution in place. If these skills are not all possessed by the same person, then people with these different skills need to be able to communicate with each other effectively. Although Tambe notes that dominant thinking suggests that “tech skills are separable and modular… [it] turns out that effective data science and other knowledge work increasingly also appear to require soft skills, collaboration, and creativity.”
It’s not only unclear what blend of skills are necessary for working effectively in a digital workplace — how best to obtain these skills is also somewhat nebulous. Tambe commented that skill development goes beyond training, simply because the pace of technological change makes setting up formal training programs difficult. Instead, much of it takes place on the job. Many organizations are focusing on creating the types of environments in which workers can teach themselves. Companies competing for workers often talk about what a great learning environment their company supports, and create physical environments where their workers like to spend time. The nonmonetary aspects of work are becoming an increasingly important factor for many employees. This includes using the best technologies, but also providing an environment where workers can signal their digital prowess to potential future employers.
He also noted that many companies also encourage a more open learning environment, where employees can actually gain skills from participating in technical communities outside the company. For example, companies may encourage their employees go to meetups with employees of other organizations. They may also encourage them to contribute to open-source technologies as a part of their work for their organization. There are a lot of different ways in which workers can learn while they’re at the company, and many organizations support that approach.
This model of employment is different than one in which companies require employees to be very secretive about the work they’re doing, and the technologies they’re using. Instead, employers are encouraging employees to engage with a larger technical community so that they can learn about new things and build their skills, expertise, and personal brands. The rationale for doing this is that the company will gain more than it may lose in terms of employee expertise.
In conducting the research for our recently published MIT SMR/Deloitte report, we were especially interested in looking at how attracting and retaining digital talent is both a geographic and a strategic decision. Tambe wrote a blog post on the topic of digital talent for MIT SMR, but he expanded on some of the strategic implications of geography and talent in our conversation.
He noted the strategic trade-offs companies face with respect to location. If you want a worker who’s really specialized in a specific cutting-edge technology, it’s easier to find these people in what you might call a “thick” labor market — a market with a lot of technical workers and a lot of employers who are employing technical workers, like Silicon Valley or New York. But, there is also a downside to locating in these thick labor markets, in that companies often have rapid turnover and face an employee retention problem. It’s hard to keep workers, because they can always move on to other places.
On the other hand, in other geographic areas, employers might lack the depth of talent pool to recruit from, but companies in these areas also may have lower retention costs than companies in hot markets. These thinner talent markets may not have as many of the most cutting-edge technical skills, but if you can help employees develop the skills your company needs, you may be more likely to keep these employees on board longer. This difference suggests very different strategies for attracting versus retaining talent, depending on the geographic labor market in which your company is located.
Yet there may also be an underdeveloped middle ground in terms of talent development. While many companies focus on a relatively small number of geographic tech centers like Silicon Valley, there are many more geographic regions that are very promising in terms of the talent pool.
Cities with strong universities, for instance, are often very rich in the kinds of workers who can provide new, emerging technical skills — and companies in these locations can sometimes offer a quality of life that’s better than you’d find in a tech hub. Tambe explained, “We’ve hit a point where some of these cities that are known as high-tech leaders have become very difficult to live in in terms of quality of life. We’ve certainly seen other cities respond to the problem, which now offer a nice quality of life and a good tech ecosystem. And it’s a trade-off for the firm between how deep the talent pool is and how much they have to pay to get the workers they want. As Silicon Valley and New York become more competitive from a labor market perspective, it’s going to make sense for employers to think carefully about what they get out of different locations. There are many cities that can offer a lot of value to employers.”