While sitting on a panel at a recent HubSpot event, I was asked a question that made me stop and think. It was a simple, but powerful, question: “How will technology impact the future of work?”
The question took me by surprise, largely because the panel’s topic was company culture. However, the more I think about the question, the more I see it makes perfect sense: The proliferation of disruptive technology and the increasing digitalization of work are both bound to affect company culture and employee engagement.
Today, I’d like to expand on the answer I gave at the HubSpot panel by looking at the impact technology will have on culture in the short, medium, and long terms.
Short Term: A Stronger Focus on Continual Learning
In the short term, automation will change the scope of many roles. Artificial intelligence may be a long way off from achieving the general intelligence needed to replace knowledge workers, but it is quite capable of taking over repetitive tasks.
Look at the tech landscape in HR, marketing, sales, or any other professional domain, and you’ll see a plethora of vendors automating essential but monotonous tasks. These technologies promise to complete tasks with fewer errors while freeing employees from morale-sapping menial labor.
What should employees do with all the extra time gained from automation? For many, the answer is increasing the scopes of their jobs and adding more value for customers. For example, a salesperson who spends less time organizing meetings and updating their customer relationship management (CRM) software can focus more on understanding and meeting customers’ needs.
As roles change, employees will need new hard and soft skills to fulfill their obligations. The most efficient way to meet this challenge is to create a culture of ongoing training and learning. Companies that are really dedicated to upskilling their workers will have a significant competitive advantage, as they will be able to adapt to changes in the economic and technological landscapes more quickly and easily.
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Medium Term: Decentralized Decision-Making
As technology advances, the business landscape often grows more complex and more uncertain. Continual training will not be enough to surmount these challenges.
At the moment, companies are feeling the pressure to create interdisciplinary teams that can work cross-functionally to solve complex challenges. In the future, I expect these teams will grow to encompass more than just internal personnel. In fact, I expect to see customers become recognized as key team members, and this recognition will grant them greater control over the means of production and customization.
Traditional workplace structures are not suited to this kind of cross-functional work. Decision-making power is concentrated at the top of the organization, and the power grows more diluted the further down the corporate ladder you travel. Therefore, as the pressure to create interdisciplinary teams grows stronger, I predict we’ll see an accompanying shift to a bottom-up approach to decision-making and innovation. Hierarchies will flatten, and new processes will be built to support communication and transparency between teams with different skill sets and objectives.
We already see this trend starting to take shape, as more and more departments outside of engineering pick up agile methodologies. For example, marketing has taken a lot from the agile “build, test, and learn” process. Expect agile and similar methodologies to expand beyond isolated functional silos in the medium term.
While many executives pay lip service to agile, they rarely want to actually decentralize decision-making. However, decentralization is essential for any organization to realize the true benefits of agile methodology. I suggest reading Plain Talk: Lessons From a Business Maverick by Ken Iverson, who led the steel company Nucor through an unprecedented 30-year reign of success. According to Iverson, much of that success could be attributed to Nucor’s dedication to decentralization.
Long Term: More Contingent Labor and a Shift to Total Talent Management
The crystal ball gets hazier the further one looks into the future, but we can draw some conclusions about long-term cultural transformation based on the principles we’ve discussed so far. If we accept we will work in more agile and interdisciplinary teams, we should also assume roles will become more specialized to align with this new model of work.
What happens when a good portion of the workforce becomes highly specialized and highly skilled at working cross-functionally? In such a situation, permanent work arrangements may not provide maximum value for employees and employers. As a result, we may see an increase in the use of contingent and freelance labor as organizations begin deploying talent to meet specific challenges as required.
The extent to which the future workforce will become contingent is up for debate, though a 2016 Accenture report predicts there will be a Global 2000 company with no permanent employers outside of the C-suite by 2026. Whatever the scope of the transformation, when contingent labor becomes the new normal, organizations will have to change their approaches to accessing, managing, and offboarding talent. We’ll see an increase in freelance and contract talent pool technologies, and workforce planning and management tools will have to address total talent management rather than just the permanent workforce.
We’ll also have to think about how to maximize team efficiency with respect to the new dynamics of cross-functional, contingent labor teams. For the best outcomes, each team should contain a balance of doers, thinkers, relationship-makers, and excitement-builders. When it comes to the future of talent acquisition, contingent or otherwise, I expect to see candidates assessed not only on the basis of their individual skills, but also with a view to balancing soft skills to maximize team output.
Ben Eatwell is CMO of Weploy.
Ben Eatwell is currently CMO and leads marketplace growth at Weploy, an on-demand staffing platform. Previously, he led the LinkedIn marketing team for Australia and New Zealand. He is passionate about using data to understand industry trends. Ben graduated with a BS in cognitive science. During his schooling, he developed AI systems to better model and understand brain function.