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Reorganizing work processes in order to utilize new technologies

Everybody is talking about predictive analytics, artificial intelligence, machine learning, digitalization, automation. But majority of companies are still in the phase when they ask them self, how can they utilize those new technologies in order to gain competitive edge. This is especially true for companies that are built with limitations of existing sectors and business models. New champions of digital age, companies like FANG’s and BAT’s of this world are natives in this environment and are looking for upgrades of their business models and not restructuring.

Introducing new technologies in old working process usually doesn’t work. Biggest innovations are the ones that bring different approach to old questions and by doing so giving better answers and as result, if they are used in proper way better results. Companies that are able to set up new task-oriented processes, improve their culture to better adapt to digital disruption, that have clear understanding of their sources of data and business knowledge and are prepare to modify their usability to match new technology driven demands and have clear strategy and tactics how they will gain competitive advantage with adoption of new technologies will be able to compete with digital natives that will dominate cross-sector environment of new economy.

In research of Michael Chui, James Manyika and Mehdi Miremadi about Four Fundamentals of Workplace Automation they estimate that as many as 45 % of activities individuals are paid to perform can be automated by adapting currently demonstrated technologies. If the technology that process and “understand” natural language were to reach the median level of human performance, an additional 13 % of work activities in the US economy could be automated.[1]

Accepting reality that not only routine operations and repeated actions are candidates for machine jobs, but also some activities that require “tactic” knowledge, experience, can be automated to certain degrees and that even today some AI capabilities exceed human abilities to solve complex issues. It is true that only few occupations can be fully automated using technology (accountants, assembly line workers, warehouse operators, stock analyst, quality control inspectors, truckers, paralegals), but almost all can be partially automated (doctors, insurance agents, financial advisors, teachers, even CEO’s – project iCEO), creating symbiotic environment of man-machine work.

In order not to be left behind companies need to prepare them self for New economy (technology led one). They should:

  • re-examine their data and knowledge source (and prepare them for algorithm usage),
  • redefine their processes through tasks and identify potential task automation or even outsourcing (with rise of sharing platforms that offers task specific knowledge on a worldwide level, lack of talent issues that companies are facing today could be addressed),
  • revise their strategy and tactics with potential impacts of new technology utilisation,
  • re-evaluate company culture and improve it to be ready for AI economy
  • start building strong talent pool for new competences
  • start building AI Centre of Excellence inside existing organization

[1]Michael Chui, James Manyika and Mehdi Miremadi: Four Fundamentals of Workplace Automation, McKinsey Digital, November 2015

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