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Disrupting Middle Management

By Colin Smith

2017 saw a flood of reports [1] on the impact of robotics, automation and Artificial Intelligence (AI) on jobs. Forecasts agree that almost 50% of today’s jobs could disappear in the next 20 years[2]. Automation has traditionally had the greatest impact on low skilled jobs, and in many industries, this is set to continue[3]. But closer to home, what does this actually mean for jobs in our biggest industries?

When the discussion turns to banking, telecoms and other white-collar industries, many people focus on customer service, contact centres and digital. The question becomes ‘how many seats can I take out of the contact centre with customer service robots, AI and chatbots?’ This is far too restrictive a view of the potential of AI. Customer-facing roles are generally lower cost, valued by customers and rife with sales opportunities. In a large bank, telco or insurer, there are many roles that deserve equal attention from disruption; and they sit in middle management.

Roger Martin, Dean of the Rothman School of Management, describes a framework for innovation used by some of the world’s most entrepreneurial companies. Simplistically, it has three steps:

  1. Understand customer needs
  2. Identify new ideas that meet these needs
  3. Systemise these ideas rapidly, so you can move on to the next

Step three in this process is frequently overlooked. This results in armies of senior, highly paid employees manually managing processes, simply because they are new or important. This layer of middle management, not the front-line, is where disruptive technologies have the biggest potential. Here are three examples:

Compliance. The day to day work of compliance departments is monitoring adherence to a set of rules. In many cases (sign off of marketing campaigns, new product development, monitoring activities, etc.) they are already a step in the process. The risk associated with these decisions has made organisations nervous of change. However, the potential upside in both cost and speed of decision making in these areas is huge.
Project Management. Anyone involved in a major project will tell you the time, effort and heartache that goes into reporting of black and white facts. No matter how bad the situation, the traffic light always seems to default to amber… However, the data on timescales, budgets and progress against plans is all available, so this is another area crying out for automation. Taking it to the next level, an AI can learn from your data and past failures, then provide intelligent input to refine governance and mitigate future risks.
HR and Recruitment. Due to our multiple subconscious biases[4], it could be argued that people have no place in the recruitment processes whatsoever. Machines have already been shown to do a much better job than people at picking candidates who will be successful[5]. This should be rolled out to other areas where we are traditionally weak, such as employee onboarding, performance management and remuneration.

As big as the benefits may be, this is not a call to replace entire departments with robots. Just like in the contact centre, the most powerful solution humans augmented by machines. As McKinsey[6] states ‘60 percent of all occupations could see 30 percent or more of their constituent activities automated’. Automation will happen, but not to every element of any role. In the same way that an engineer with a laptop can defeat a chess grandmaster or the world’s most advanced chess computer[7], the combination of big data analysis with empathy and contextual awareness will always provide the best experience.

The opportunities and benefits of AI and automation will be different in every company. To make their implementation successful, companies need to start by looking at the processes and areas that cause them the most pain and cost the most money, not the ones that appear most obvious from the outside…

4 ‘Thinking Fast and Slow’, Daniel Kahneman, 2011

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