Monday, July 13, 2015

Laws for Mobility, IoT, Artificial Intelligence and Intelligent Process Automation

If you are the VP of Sales, it is quite likely you want and need to know up to date sales numbers, pipeline status and forecasts.  If you are meeting with a prospect to close a deal, it is quite likely that having up to date business intelligence and CRM information would be useful.  Likewise traveling to a remote job site to check on the progress of an engineering project is also an obvious trigger that you will need the latest project information.  Developing solutions integrated with mobile applications that can anticipate your needs based upon your Code Halo data, the information that surrounds people, organizations, projects, activities and devices, and acting upon it automatically is where a large amount of productivity gains will be found in the future.

There needs to be a law, like Moore's infamous law, that states, "The more data that is collected and analyzed, the greater the economic value it has in aggregate," i.e. as Aristotle is credited with saying, "the whole is greater than the sum of its parts." This law I believe is accurate and my colleagues at the Center for the Future of Work, wrote a book titled Code Halos that documents evidence of its truthfulness as well.  I would also like to submit an additional law, "Data has a shelf-life and the economic value of data diminishes over time."  In other words, if I am negotiating a deal today, but can't get the critical business data I need for another week, the data will not be as valuable to me then.  The same is true if I am trying to optimize, in real-time, the schedules of 5,000 service techs, but don't have up to date job status information. Receiving job status information tomorrow, does not help me optimize schedules today.

Mobile devices are powerful sensor platforms.  They capture, through their many integrated sensors, information useful to establishing context.  Capturing GPS coordinates for example, enables managers to see the location of their workforce.  Using GPS coordinates and geo-fencing techniques enables a software solution to identify the job site where a team is located.  The job site is associated with a project, budget, P&L, schedule and customer.  Using this captured sensor data and merging it with an understanding of the needs of each supervisor based upon their title and role on the project enables context to be established.  If supervisor A is responsible for electrical, then configure the software systems to recognize his/her physical approach to a jobsite and automatically send the latest information on the relevant component of the project.

I submit for your consideration yet another law, "The economic value of information multiplies when combined with context, meaning and right time delivery."  As we have seen, mobile technologies are critical for all of the laws discussed so far in this article.

Once sensors are deployed, sensor measurements captured, data wirelessly uploaded, and context understood, then business rules can be developed whereby intelligent processes can be automated. Here is an example, workers arrive at a jobsite and this data is captured via GPS sensors in their smartphones and their arrival automatically registers in the timesheet app and their supervisor is notified.  As they near the jobsite in the morning, using geo-fencing rules, each worker is wirelessly sent their work assignments, instructions and project schedules for the day.  The right data is sent to the right person on the right device at the right time.

The IoT (Internet of Things) is a world of connected sensors.  These sensors feed more sources of captured data into the analytics engine that is used to find meaning and to provide situational awareness.  If smartphones are mobile sensor platforms, then smartphones and IoT are both peas in the same pod.

Intelligent automated processes, like the ones mentioned above, are called "software robots" by some. These are "aware" processes acting upon real-time data in a manner that supports human activities and increases productivity.  Here is what we all need to recognize - mobile applications and solutions are just the beginning in this value chain.  Rule: Mobile apps provide only as much value as the systems behind them.  Recognizing mobile devices are sensor and reporting platforms that front systems utilizing artificial intelligence and automated processes to optimize human productivity is where the giant leaps in productivity will be found.

If you agree with my premises, then you will understand the urgency to move beyond the simple testing and deployment of basic mobile apps and jump into building the real value in the intelligent systems behind them.

Summary of Laws:
  • The more data that is collected and analyzed, the greater the economic value it has in aggregate
  • Data has a shelf-life and the economic value of data diminishes over time
  • The economic value of information multiplies when combined with context, meaning and right time delivery
  • Mobile apps provide only as much value as the systems and intelligent processes behind them
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Kevin Benedict
Writer, Speaker, Senior Analyst
Digital Transformation, EBA, Center for the Future of Work Cognizant
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***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.