Every entrepreneur knows that growing and scaling a business is a tremendous challenge. We make efforts to run our organization as smoothly as possible by implementing straightforward processes coordinated between various employees, teams and departments. It’s no longer just 10 colleagues in a room making every decision. While these processes are necessary to perform our day-to-day business activities at scale, they also have the potential to trap employees in rigid routines that leave little room for innovation and data-driven creative thinking.
In a 2018 survey focused on business process management, 52% of respondents said that business processes in their organization were only occasionally documented or modeled. It’s time to take a closer look at your business processes and the tasks required of employees to complete them.
Imagine if every process in your organization could be represented visually as a kind of interconnected virtual flow chart with people, tasks and the types of data needed to complete those tasks. The resulting visual would resemble something close to what engineers call an ontology or a hierarchy of relationships between certain concepts and their peripheral data points.
Take a back-office process like invoice approval, for example. For the person approving that invoice, there is a multitude of data points to consider:
• Is there an existing relationship with this customer?
• Are there any red flags in this customer’s past business dealings?
• Where is this customer located, and are there any geography-based compliance issues?
There are many more questions and data points like these to ponder, and often, the answers to these questions reside with one or more individuals in the organization. The ontology, in this case, would be made up of these various questions and the departments that own the data needed to answer them.
However, if we were to create a visual representation of this specific task in reference to the specific data (the actual answers to these questions), the result would be what I like to call a taskonomy. A taskonomy is a hierarchical structure of individualized data that helps an employee in your organization perform a specific task. This is a new term, but it’s important to get familiar with the concept.
Soon, machines will be able to align with these taskonomies, curating all of the pertinent data needed to complete a single task — while ignoring the data that is not integral to that task. This will transform back-office data from an overwhelming headache into a streamlined asset for your organization, its processes and its people.
To assess the importance of this systematic structure change in the contemporary tech landscape, I want to go back more than 150 years to one of the great seismic shifts in human understanding.
In November 1859, Charles Darwin published On the Origin of Species, a landmark thesis that introduced the theory of evolution — the idea that individual species evolve over time according to natural selection. The theory almost immediately created a new discipline of evolutionary biology and was so impactful in its discoveries that it would go on to influence public discourse around religion and anthropology. Seminal ideas and events like these do not happen in a vacuum.
Darwin’s ideas were predicated on a system of biological classification established by Carl Linnaeus. Linnaeus’s two-name taxonomic nomenclature system is still used by biologists today to identify not only individual species, but also related species that have evolved from common ancestors. But, these evolutionary relationships were not a part of Linnaean classification from the start: The classifications and relationships in Linnaeus’s taxonomy were considered to be divinely ordained. The evolutionary lens through which we view Linnaean classification today did not come into fruition until Darwin published his breakthrough theory.
The point is, by the time Darwin’s revolutionary idea came forth, there was already a strong system in place that allowed scientists to put those ideas into practice almost immediately. Darwin’s theory essentially transformed the function of biological taxonomy by introducing context.
Similarly, artificial intelligence will soon bolster existing processes by enabling employees to see contextual data associated with their tasks. Engineers today can already construct an ontology pertaining to a specific task because we know the types of data needed to complete the task. But, the rising tide of AI will enable the realization of specific taskonomies in real time. This development will be transformative for back-office processes, empowering your employees with the best analytics for their jobs. And, this transformation will have a ripple effect back up the chain of command: Employees freed from data-entry tedium will also free up their bosses to perform work more strategic to the company.
Of course, the technology powering this change will not magically appear overnight. And, when it does surface, it will require an investment of time, money and employee resources. But, it shifts the enterprise productivity debate from the organization to the individual — a change that is long overdue. For centuries, older generations have claimed that younger people do not work as much or as hard as their elders. For the first time, this might actually be coming true. The next generation of workers will spend far less time bogged down in mind-numbing manual business processes than their ancestors. But this doesn’t mean the next generation will be lazy. It means we have to find better tasks for them to do.