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(This article has a difficult time differentiating management and leadership. The central point it makes however, is important. Paul)
Why have decision-making structures in large organizations changed so little since the industrial revolution? Leaders still base decisions on retrospective data that has percolated up through layers of filtering and consolidation. Decisions are then handed down through progressive layers of management, where they are adjusted to practical realities.
Such a world forces leaders to make educated guesses based on often flawed assumptions, and to have faith rather than evidence that the organization is doing what leaders decide, and that the results expected are indeed being achieved. Despite a torrent of information demands, when failures occur, leaders often learn that the causes were common knowledge to everyone, except leadership.
Technology can change all of that. What if leaders knew as much about their organizations as Google knows about them? By deploying appropriate technologies, it is possible today for organizations to capture data on practically every interaction and consolidate every performance metric in an organization.
Automating management offers decisive advantages. As the system knows exactly what everyone is working on and what is being produced, accountability is clear. Coaching and feedback can be automated, tailored to the individual, and delivered exactly when required
In an age when management of most work processes can be automated, leaders can be freed to focus more of their energies where their judgement and experience truly add value. But they must first embrace new organizational models based on accountability, transparency and collaboration, informed by data.
Leaders aspiring to be great will be challenged to build their understanding of data science, learning how to augment their personal experience, intelligence and insight with rich data sets and predictive AI.
They must also become skilled social media activists, using technology to communicate their vision and nudge the organization to achieve it. They must be coalition builders, making the connections required to deliver complex change programs. And leaders must drive new cultural norms, showing that failures are not a reason for blame, but an opportunity to build learning.
Leaders must also be comfortable that transparency goes both ways. With everything recorded, no leader can credibly say they did not know. And with every action recorded, the real value that a leader adds is clear to all.
Without question, much of what has traditionally constituted organisational management can and should be automated. Companies like Klick have proven that it can be done, and to profoundly positive effect.
Automation of leadership, by contrast, may be neither possible nor desirable. However, by augmenting leadership with technology, companies can become more effective, agile and better places to work.
Leaders should not be fearful of embracing managerial automation, nor of accepting the power of data and AI to augment their personal effectiveness. Both are urgently necessary advances in an increasingly disruptive world.
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It seems beyond debate: Technology is going to replace jobs, or, more precisely, the people holding those jobs. Few industries, if any, will be untouched. It is easy to find reports that predict the loss of between 5 and 10 million jobs by 2020. Here are four ways to think about the people left behind after the trucks bring in all the new technology.
The Wizard of Oz Is the Wrong Model
In Oz, the wizard is shown to run the kingdom through some complex machine hidden behind a curtain. Yet the CEO and founder of Fetch Robotics, Melonee Wise, cautions against that way of thinking: “For every robot we put in the world, you have to have someone maintaining it or servicing it or taking care of it.” The point of technology, she argues, is to boost productivity, not cut the workforce.
Humans Are Strategic; Machines Are Tactical
McKinsey has been studying what kind of work is most adaptable to automation. Their findings so far seem to conclude that the more technical the work, the more technology can accomplish it. In other words, machines skew toward tactical applications. On the other hand, work that requires a high degree of imagination, creative analysis, and strategic thinking is harder to automate.
Integrating New Technology Is About Emotions
When technology comes in, and some workers go away, there is a residual fear among those still in place at the company. The wise corporate leader will realize that post-technology trauma falls along two lines: (1) how to integrate the new technology into the work flow, and (2) how to cope with feelings that the new technology is somehow “the enemy.” Without dealing with both, even the most automated workplace could easily have undercurrents of anxiety, if not anger.
Rethink What Your Workforce Can Do
Technology will replace some work, but it doesn’t have to replace the people who have done that work. Economist James Bessen notes, “The problem is people are losing jobs and we’re not doing a good job of getting them the skills and knowledge they need to work for the new jobs.” Such jobs may not be in your current industrial domain. But there may be other ways for you to view this moment as the perfect time to rethink the shape and character of your workforce. Such new thinking will generate a whole new human resource development agenda, one quite probably emphasizing those innate human capacities that can provide a renewed strategy for success that is both technological and human.
As Wise, the roboticist, emphasized, the technology itself is just a tool, one that leaders can use how they see fit. We can choose to use AI and other emerging technologies to replace human work, or we can choose to use them to augment it. “Your computer doesn’t unemploy you, your robot doesn’t unemploy you,” she said. “The companies that have those technologies make the social policies and set those social policies that change the workforce.”
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