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Future of work

People Make the Difference

The ‘Uberisation' of work or workforce is the new premise of the future enterprise. There won’t be full time enterprise needs. There will be distributed teams driven by data delivering data driven programs and reporting their progress with data.

Each role of the enterprise will be under or behind a siloed data view and will have pick and choose as they need. There will be self-service as a role since each role will become data enabled. But then:

  • How to replace the "manager"? in the enterprise
  • How to ensure information as you need based on the role is only accessed
  • How to understand and monitor the trade secrets of you workplace
  • How to leverage the best in class of solutions.
  • How do the missing dots add up
The Stream View of Businesses:

Each Enterprise is mimicked around a stream of specific capabilities and processes. And each process is driven by data driven bots as indicated in bubbles above. The role specific functions and processes have dual alignment towards the enterprise specific needs as well the process specific needs. The future actors will need to create a personal cloud/virtual marketplace for themselves wherein they subscribe /borrow the bots per their needs. There will be 2 different realms of a role, one fairly permanent belonging to a individual ad much to be called the core, the other will be the transitory realm. This is where the subscription based bots will reside and will provide the insights to be successful. This realm will deliver the Sixth Sense to the individual to operate in an ambiguous data driven and data monitored environment.

The data monitored environment will be governed by a virtual KPI matrix of performance and quality and will have a virtual self-tracking mechanism to operate.

Performance Quality
First Call Resolution Work unit reduction %
Time To deliver Correct process delegation
Work unit Duration Reopened Call for action
Feedback Frequency Late/No Feedback
Speed To Answer Abandoned Rate
Number of Followings % Solved
Number of missed SLA’s Number of Stories completed