Many pieces were written in the last years on the future of work. It is well accepted that work is will go through a radical change in the next decades. Many predict that some professions will become obsolete due to robots and automation while new professions will emerge. Articles titled ‘Will your job disappear within ten years? becoming popular. However, one perspective is not present in the discussion: the future of managers. Will managers continue to take the same responsibilities? Will managers be replaced by robots and automation? Which skills managers will need ten years from now?
Let’s start with defining ‘manager’: the most basic definition is someone who directs, supervises, plans or conducts the work of others. The US Bureau of Labor Statistics defines managers using negation: The Bureau’s Current Labor Statistics publications include the category of ‘production and non-supervisory employees’, generally these are the people doing only actual production (for the exact definition). So, we can say the all employees not counted under ‘production and non-supervisory’ are managers. Indeed, many of them are not CEOs, CTOs of other types of ‘officers’. The most are low-rank managers dealing with daily operations, the people who are the backbone of business management, keeping operations running, and solving problems every day.
We can generally say that as there are less managers per production workers, the business is more ‘managerially-effective’, meaning making more production will less resources spent on managing it.
Look at figure 1, it shows the total number of employees in the private sector in the US since 1964, together with number of production employees in thousands (from here production employees stands for the long phrase ‘production and non-supervisory employees’. Data source for of all figures is https://www.bls.gov/data/). It looks as most of employment development happens within the production category, growing most of the time and dropping during recessions, marked grey in the figure. It also looks as the managerial layer remains a constant portion of the total employees. However, this is not the case.
Figure 2 shows the exact percentage of manager out of the total employees for each year. We can see three distinguished periods: 1964-1982, 1982-1991 and 1991-present. During the first period of 1964-1982 the percentage of managers jumps with each recession. During economic growth periods it still grows, but slower. This makes sense when we think on basic business development: time makes business operations more complicated, and therefore more managers are needed. The first employees laid-off during recessions are productions workers: business owners look to cut expenses, and terminating managers will result in losing organization knowledge. On the same time, these managers can take some of the production work. So, the first to go are the production workers and the percentage of managers raise quickly. When the recession ends new production workers are hired, and the percentage of managers drops. In fact, performing linear regression of change in percentage of managers over GDP growth yields R2 of 0.7, evidence to the strong relation between these two indicators.
Managers’ world starts to change
Things change during the long growth of the 1980s. Percentage of managers is steady with a small decline, ending with the recession of the early 1990s. What happens here? Figure 3 shows the percentage of managers per sector. First, we can see that the percentage of managers varies greatly across sectors, as each sector has some ‘basic level’ of managers. This is reasonable as the number of managers needed in order to run a hotel is very different than needed to run a film production, given the same number of production employees. Second, we can see that most sectors show a slow increase in managers’ percentage until 1982 and after that year each sector behaves differently.
Some sectors, such as travelers’ accommodation, retail trade, or construction show increase of the percentage of managers from 1982 until today. Other sectors like wholesale trade, financial activities and transportation and warehousing show overall stability over 1982-2003 and then a decrease since 2003. The information sector, which includes traditional and modern information industry including publishing, television, filmmaking and IT, shows stability over the entire chart with a sharp decline after 2003. We can conclude that some sectors experienced improvement of managerial-efficacy beginning on the 1990s, which was dramatically increased since 2003. On the same time, the managerial-efficacy declined throughout the entire period. What can be the source of these differences?
Managerial efficacy and IT
Figure 4 shows the change in the percentage of managers since 1990, per sector. This chat includes more subsectors, as new classifications are available since 1990. In this chart, 100 means no change since 1990, and 110 means increase of 10% since 1990. This method allows to understand the trends over time, removing the effect of the ‘basic’ manager percentage of each sector. The chart shows that sectors can be divided into four distinguished groups. The first group is of sectors showing significant decline in percentage of managers, or significant improvement in managerial-efficacy of ~30% or more: financial activities, office administrative services, and data processing, hosting etc. The second group less significant shows improvement of 10%-20%, including: travel arrangements, utilities, and facilities support services. The third groups shows almost no change, including: construction, retail and wholesale trade. Finally, the forth group shows an increase in the percentage of managers, meaning decline in managerial-efficacy: transportation and warehousing, accommodation and food services, and travelers accommodation.
What is common to the sectors in which managerial-efficacy improved? What is common to those sectors in which it declined? We suggest that the undelaying cause is the adoption of information technology.
We know that information technology was not always here, yet we sometimes forget when exactly it entered our lives. Desktop computers became wildly available during the mid-1990s. Business owners could afford buying several computers for the managers sitting by their desks. On these days software was installed locally, and only large businesses could afford central databases. Under these circumstances, it was only natural to target the managers and production workers whose work could be easily done in a computer environment. In other words, work which has to do with processing written or information, of information which can be easily digitalized. The hallmark of such work is the financial sector, and as can be seen of figure 4 the percentage of managers in this sector drops by 10%-20% during the 1990s. When managers have better tools to collect information from their employees, process it and turn it into decision, the same number of managers can oversee more and more production employees. Think of the processing steps taking place after selling insurance policies: double and triple checking of documents, asking for additional documents, delivering to the main office, and so. How many insurance salespersons can one low-rank manager oversee when all she has are printed documents filed in cabinets and each interaction with an employee means writing a memo of making a phone call? How many she can oversee when all the documents are digitalized and she can send emails?
Figure 4 shows that the major improvements of managerial-efficacy occurs since 2002. These are the years that internet became wide spread. In 1997 only 18% of you had internet access. By 2000 41.5% had, and by 2015 76.7% had internet access. Since the 2000s enterprise software transformed into SaaS applications, allowing more managers and employees efficient cooperation and lower costs. Online platforms like Salesforce, SAP and various Business Process Management (BPM) transformed the way people work.
Why some are left behind?
But this transformation did not happen in all sectors. A well-known research by McKinsey examines the digitization of sectors in the US economy, shown in figure 5. The highly digitalized sectors, marked green, correspond to those in which the percentage of managers dropped since 1990. It is also noticeable that the sectors in which the percentage of managers increase since 1990 are of the less digitalized sectors.
The digital gap can be closed. Information technology can transform the less-digitalized sectors and to improve their productivity and managerial-efficacy, allowing to do more with less. A paradigm shift is needed. All sectors included in group 1 within figure 5, the most digitalized, are characterized by the fact that most of the work is done in form of a computer. In all the other sectors major parts of the actual work at done away from the computer, if not all of the work. Indeed, mobile communication has been transformed since the wide adoption of smartphones. Yet, smartphones alone do not make big enough change.
The next step is automation. In some sectors robots can easily replace human workers. But robots need a standardized environment in order to know what to do. Robots can easily work in controlled environment like a storage facility. Driverless cars are considered the next quantum leap in robots implementation. Yet, driving takes place in a highly standardized environment which was perfected over nearly a century: standard lanes, on-asphalt markings, traffic signs, signals, car lights and so on. Some sectors are not so suitable for automation by robots. Maintenance, hospitality, healthcare, construction, utilities, heavy industry, and similar sectors are all characterized by the fact that workers need to perform manual and semi-manual labor in a non-standardized environment. Even if one can design a nurse-robot, human workers will outperform it for many decades to come.
Digitalization is the key
Yes, automation can take place in these sectors: automating management of mobile workforce. In all these sectors one basic fact holds: almost all the decisions taken by workers could have been made in advanced. For almost every decision needed to be made by a maintenance worker, a nurse, a front desk operator, a window installer, and carpenter there is a by-the-book solution. Some of these decisions fall under the professional expertise of the employee: which screw to use? Or how to put a pressure band? But many decisions have to do with the managerial or business aspects of the manual work: which tasks to prioritize? When should I tell my manager there is a problem? Which information should I provide to the person working on this issue after me? How to coordinate other workers or limited tool with my current tasks? Today, supervising such decisions or taking them is the role of managers dealing with operations. Moreover, they oversee the professional work of production employees, approving it or deciding which work should be redone. They coordinate complex tasks demanding several employees, make sure prioritization is done right. Their daily routine is made of lots of phone calls, emails, spreadsheets, notes and checklists. Information technology as it exist today can help to be more organized, but cannot help them to scale up.
Bravo.ai digitalizes the mobile workforce
Bravo.ai is an innovative system that helps managers to scale up, focused on the least digitalized sectors. Bravo.ai gives managers two powerful tools: automatic SOPs combined with Artificial Intelligence (AI). The first tool, automatic SOPs, means that Bravo.ai managers the organization’s SOPs step by step, to the finest details: tasks are sent to employees, they report back and the system routes the SOP to the next task until it’s completed. Bravo.ai demands managers’ attention only when specific conditions occur, like critical issues or sensitive decisions. Automatic SOPs takes the largest and most repetitive chuck of managers’ work, allowing to make time for important decisions. Automatic SOPs allow coordination and communication between many employees, another tiring task for managers. You can say that Automatic SOPs are like ‘manager angels’ sitting on the shoulder of each employee.
Bravo.ai seamlessly combines AI components in SOPs execution. These AI components improve complex decisions, such as scheduling workers to tasks which can improve production by 300%. They allow to improve SOPs and resource utilization by revealing bottlenecks in SOPs. AI components also detect abnormalities and respond during runtime.
Bravo.ai allows managers to scale up: manage more employees while focusing on what’s important, making time for strategic decision instead of tedious micro-management. Bravo.ai is the future of work, but most important: it’s the future of managers.