Responsibilities of the exponential professional

Responsibilities of the exponential professional
This post is the second in a three-part series on the exponential professional, focused on the expectations and responsibilities of the exponential professional.

Posted by Darryl Wagner, and Caroline Bennet on March 21, 2018.

HR professionals use virtual reality to facilitate employee training and increase retention. Sports reporters use natural language generators to automatically recap games and to highlight interesting statistics. Actuaries use cognitive computing to automatically evaluate data, compute results, and predict new patterns. Professionals across many industries engage employers in alternative work arrangements through the gig economy. This future of work is rapidly becoming reality as technology develops exponentially. Exponential professionals are those who capitalize on the shifting workplace by embracing new technology, leave behind traditional automatable tasks, and apply their uniquely human skill set to more high-value, strategic roles.

Over the last century, machines have replaced many tasks previously performed by humans in nonprofessional workforce segments. Advances in machine learning, robotics, and cognitive technologies are now also disrupting the professional workplace. Today, many professionals regularly perform repetitive, routine tasks that could instead be performed by a machine. Truck drivers transport material back and forth between point A and B. Financial analysts execute a checklist of activities to calculate and evaluate financial reports. Machines will soon be able to accomplish such tasks more efficiently, economically, transparently, and with fewer or no mistakes.

Consider the case of a life insurer that was using hundreds of spreadsheets and databases for financial reporting.1 Recognizing the need to modernize its financial reporting function, the insurer implemented a single vendor-based system solution combined with an automated end-to-end process. As a result, the financial reporting results were produced more reliably, in less time, and with three times the analysis available prior to this transformation.

An evolving role
The exponential professional will need to evolve his or her role to augment the capabilities of the machine.2 Machines are strong in executing routine tasks without bias; however, critical thinking, creativity, communication, social perception, and resilience are uniquely human abilities that characterizes the professional.3 When an autonomous vehicle replaces driving for the truck driver, the driver can focus on troubleshooting delivery issues, making decisions on the go, and building customer relationships.4 When a bot automatically performs an analyst’s financial reporting procedures, the analyst can focus on interpreting and communicating findings, asking new questions, and identifying new, forward-looking strategies. Furthermore, organizations today are driving a huge increase in demand for analytical roles. These roles are typically called “data scientist” or “analyst” and are growing rapidly, with the number of annual positions expected to reach 2.7 million by 2020.5 These jobs combine technical expertise with expertise in design, project management, and communication to augment exponential technology.

In addition to altered responsibilities, exponential professionals will need to adapt their professional judgment and conduct. Primarily, the professional will need to adapt to trust the work6 of the machine to benefit from it. However, machines are programmed by humans and thus prone to error. As such, professionals should also learn how and when to challenge the results of the machine. Currently, many professional standards worldwide discuss trusting or relying on the work of others. For example, Actuarial Standard of Practice #23 discusses the use of data and reliance on data created by someone else.7 The standard states that the accuracy and completeness of data provided to an actuary is the responsibility of the supplier, subject to review. To what extent does this change if the supplier of data is a bot? Similar professional standards will have to be created for the human-robot relationship for various industries and careers. Undoubtedly, professional standards and the professionals’ duty to their stakeholders and the public must not be compromised. On the contrary, professional quality inspection and review will likely be of added importance, attracting a greater proportion of the total effort in a more automated work environment.

Another aspect of professional conduct that is especially relevant for the exponential professional is mitigation of conflicts of interest. Professionals of today may find themselves conflicted between responsibilities to their employer, clients, professional organizations, government, and other stakeholders, such as the public. These responsibilities become increasingly complicated when the professional is a member of the gig economy and may be employed by several entities simultaneously. Consider the example of two different rideshare companies where drivers can work for both companies at the same time. When a driver is waiting at the airport and receives ride requests on both rideshare apps simultaneously, how does the driver choose which request to accept? Does the situation become more intricate if the vehicle in use has been arranged through one of the rideshare companies? The exponential professional will continually need to be on the lookout for conflicts of interest related to their professional assignments.

There is a large gap between today’s professional and the exponential professional when it comes to responsibilities and professional expectations. Regulating bodies, employers, and professionals themselves will all play major roles in bridging this gap. This will be discussed in detail in our final post in the series, Creating the exponential professional.

Darryl Wagner is a principal in Deloitte Consulting LLP and the Global Actuarial, Rewards & Analytics Leader and US ARA Insurance Services Leader.
Caroline Bennet is the National Leader of Deloitte Actuaries & Consultants, the Insurance Leader for Deloitte Australia, and Leader of FSI Consulting, and is a member of the Global Deloitte Actuarial, Rewards and Analytics Executive Team.
Contributors: James Dunseth, Trent Segers, Wes Budrose, Nate Pohle, Ajay Parshotam, Mehul Dave, and Corey Carriker

 

1 “Actuarial 20/20 Transform the function,” Caroline Bennet, Jason Morton, Bruce Fell, Stephen Keane, Roger Simler, Deloitte, 2016.

2 “Machines as Talent,” Global Human Capital Trends 2015, David Schatsky and Jeff Schwartz (Page 95).

3 “Catch the Wave,” Deloitte Review Issue 21, Josh Bersin (Page 73). https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/Growth/deloitte-uk-talent-for-survival-report.pdf; https://www.theaustralian.com.au/higher-education/communication-business-skills-essential-for-graduates/news-story/42c790b1ebebeb513b100af2a2c1212b

4 “Quarterly Report #3 What’s next for labor in a world of automation,” Line of Sight Simler (page 7).

5 “Catch the Wave,” Deloitte Review Issue 21, Josh Bersin (Page 72).

6 https://analytics-blog.deloitte.com/2017/05/19/who-determines-ethics-in-a-machine-run-world/

7 http://www.actuarialstandardsboard.org/wp-content/uploads/2017/01/asop023_185.pdf