For years, the focus of many organizations has been on standardizing and automating existing business processes to achieve significant gains in efficiencies.
Within the office of finance, mundane transactional processes such as order-to-cash, procure-to-pay and record-to-report have been the epitome of standardization and automation.
As a result, a number of finance and accounting professionals have had their jobs taken over by automation or machines.
Compared to humans, machines are best at handling repetitive tasks, analyzing enormous data sets, and handling cases with usual modus operandi. On the other hand, humans are best at resolving cases that are complex, requiring application of critical thinking and problem solving capabilities, listening skills, and empathy.
In spite of the job losses of the past as a result of standardization and automation, we are continuing to witness a plethora of new technologies come to the fore and play a vital role in adapting operating models and driving business transformation.
For example, modern technologies such as cloud computing, RPA, advanced analytics, artificial intelligence, and machine learning are transforming the finance function and progressively enabling finance and accounting professionals create and deliver value across the organization.
Sadly, because of these technological advances, many finance people have embraced the false gospel that we are in the era of men-versus-machines.
They are of the incorrect view that machines have arrived to oust humans from the workplace. As a result, they are constantly fighting to protect their turf and are hamstrung by old habits.
Although there are always casualties as a result of implementing new technologies or solutions, the simple truth is that machines are not taking over the world, nor are they removing the need for humans in the workplace.
Instead, these new tools are augmenting human capabilities and collaborating with us to achieve productivity gains that have previously not been possible. Further, the emergence of modern technologies is also creating completely new roles and new opportunities up and down the organization’s value chain.
Given robotics and automation are here to stay, it’s imperative for business leaders to let go of this woefully misguided view of men-versus-machines, and embrace the modern era in which humans and machines collaborate to drive business performance.
Instead of becoming stuck on the old way of doing things, making it difficult to envision things that might be, a completely different mindset is required.
The key to achieving the expected benefits from having humans and machines working closely together is laying the proper foundation and sending out a clear message across the organization to alleviate any fears.
Humans and machines should not be viewed as rivals fighting for each other’s jobs. Rather, they should be considered as close collaborators, each impelling the other to higher levels of performance.
Since machines are better at performing tedious or monotonous tasks, and people rarely find delight in fulfilling these tasks on a daily basis, in order to take advantage of human-machine augmentation, companies should discontinue training their teams to work like robots.
Management and leadership must conduct a resolute review of organizational processes, identify and determine which tasks humans do best, and those that are best suited to machines.
The ultimate goal is to have people focus less on low-visibility tasks and more on higher-value tasks, requiring their judgement, experience and expertise.
In determining which processes to change, there are certain elements to look out for in your business operations. These include repetition, replication, redundancy or a well-outlined process. A significant presence of these elements is a sign that tasks or processes are ripe for change.
But before you reinvent business processes, job descriptions, and business models, you need to make prudent decisions about how best to augment your existing employees. For example, they are needed to design, develop, train, and manage various new applications.
A large part of that effort requires experimentation or trial and error to determine what work should be done by humans, and what work would best be completed by a collaboration between humans and machines.
Replicating the best-in-class process of an industry leader no longer cuts it through. In today’s highly competitive environment, to compete, management and leadership must customize processes to the eccentricities of their own businesses. That’s why experimentation is key.
Additionally, to get buy-in from employees across the company, leadership should foster a culture that encourages experimentation and not discourage mistakes. Provide clear objectives and also clarify to employees that you are investing in new solutions to replace tedious tasks and make their day-to-day work more engaging.
Technology is only an enabler of step-level increases in performance. Don’t rush into human-machine augmentation without initially laying the proper foundation.
First, automate routine work and concentrate on developing the full potential of your employees; then they can begin to focus on human-machine augmentation.
To be highly effective the implementation of AI is a multi-discipline exercise that will require resources from many parts of the business. A good example of this can be illustrated when using AI to assist in auto invoicing and payment applications. The sales department, manufacturing and shipping departments will provide data that allows these two functions to operate autonomously. The data from these departments will be incorporated into algorithms that function to determine how much, when and to whom to send an invoice; and, how to apply payments when the bank reports them as received.
