We finally have something worthy of the ‘moonshot’ moniker: the incorporation of a digital workforce, offering enterprises the ability to survive and thrive.
The Origin of the Moonshot
When I hear statements like: “We need to take a moonshot project approach to …”, my eyes usually glaze over. It frequently comes across as a promotional statement intended to imply importance, massive change and something no one has ever done before. But, here’s the problem: the 'moonshot' idea is usually nothing more than a remake of something that turns out to be of limited consequence.
However, for the first time in as long as I’m able to recall, we finally have something worthy of the ‘moonshot’ moniker: the incorporation of a digital workforce, offering enterprises the ability to survive and thrive in a world that is:
- Living through a pandemic with constant risk of more health threats in the future.
- Gaining population exponentially but with a declining labor participation rate.
- Experiencing climate change.
- Innovating business models that aren’t burdened by outdated operational models, IT systems or inaccessible data stores.
- Heavily regulated with more to come.
These very real challenges are enough to make any older, legacy business break a sweat. A moonshot is, indeed, a necessity. And implementing a digital workforce enables many transformative and protective benefits. In no specific order, they are:
- The ability to modify the human workforce labor model to respond to fluctuating circumstances.
- A reduction in risk and the need for more people to manage increased regulation compliance.
- The ability to compete more effectively with well-equipped and new businesses that are re-defining what it means to be a bank, insurer, etc.
- Human labor positioned to innovate rather than manage procedural tasks of lesser value.
Why the ‘Moonshot’ Reference is So Important
There were substantial limitations that plagued man’s ability to get to the moon in the 1960s. NASA’s organization of human labor and productivity was one of several problematic areas. Specifically, one of the areas in the early days of Project Mercury, was the inability to manage and calculate vast mathematical equations for varying trajectories. This was a huge challenge recently made widely known in the movie, Hidden Figures. In the final analysis, the women who were managing this work were nothing short of heroic and essential to our early ability to rapidly calculate escape velocities, changed trajectories and emergency thruster maneuver impacts. What’s more, the expectation was in real-time, when a person’s life depended on it. Now, that is mission critical and certainly not for the faint of heart!
However, it turns out that the calculations these women are well known for were not the final resolution. We needed far more computational horsepower with an accuracy and speed that was largely limited during their time on Project Mercury. Calculating things by hand for travel from the Earth to the moon and back again was not something that we (or the crews) would be able to depend upon long term.
NASA added mainframe support to the program during the second of three project components to land us on the moon, known as Project Gemini. By Project Apollo, the number crunching was being done on banks of mainframes. It was fast, reliable, limitless in its scale and the only way we could get to the moon and back.
The Evolution of Business Will Determine How We Get to the Next Frontier
The future workforce will be a seamless blend of interoperable human, digital workers and systems (synergistic workforces), working together to create new opportunities, efficient outcomes and customer value. We must solve this challenge of dividing labor between humans and digital workers (robots) to produce maximum business results. However, in order to manage that labor distribution into something that produces a harmonized value chain, more is needed from intelligent automation software. At the intersection of the human workforce, systems, the digital workforce and the business model is the need for a governance model to manage the newly added digital labor source.
This will not only provide the basis for corporate and IT governance, but it also forms the rules of engagement between digital workers and human workers. This is the framework that manages things like policy for credentialing a non-human worker to access systems and data stores. Effectively, this governance model becomes the human resources function for the management of a highly distributed, independently functioning digital labor pool. As a digital worker requires more “skills” to perform certain functions, the addition of advanced capabilities like machine learning, computer vision, speech recognition, etc., are also governed under this mechanism.
So, why is there a need to do this when an organization always has an operational model? Because that model was largely defined during the 1950s when mainframe computing was making its way into the back office of major corporations. Most call it the “People, Process, Technology” model, and it has worked very well since that time. However, with the addition of digitally sourced labor there is now an urgent need to modify the model of old.