Digital is out, smart is in

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It’s not about how digital you can become, but about how smart. The majority of emerging technologies exist and evolve to enhance our cognitive capabilities. They are there to make us smarter.

As more organizations move themselves along a path to the digital era, it is important that they understand what digital means. It is crucial to have a clear perspective of what their digital future looks like. Many organizations have at best a fragmented point of view.

Replace the word “digital” with “smart” and the understanding changes rapidly. “Smart” has a much more intuitive connotation to people than “digital.” You can apply “smart” to different capabilities: smart customer service, smart supply chain, smart manufacturing, smart marketing, and so on.

Emerging technologies like artificial intelligence (A.I.) have the intent to augment our knowledge, skills and experience. The main purpose of machine learning for example is to help organizations make better decisions. If they do, they can “outsmart” their peers in various ways.

Smart can be defined as a function of being connected, real-time and intelligent. Recently I worked with a group of thought leaders on “smart” capabilities and together we defined smart as follow.

  • Connected: An organizational entity that is horizontally and vertically integrated in real-time to facilitate the flow of intelligent data between people, processes, technology and assets.
  • Real-time: Actual time during which an event occurs. Within a connected system, events occur in milliseconds and the output is available for immediate use.
  • Intelligent: Capability to analyze events in response to varying situations and scenarios, needs and historical patterns, with the purpose to trigger a new event or enable decision-making.

It is important that leaders have this definition top of mind every time a decision needs to be made about smart people, process and technology change. The challenge that organizations face with emerging technologies like A.I. is that over-enthusiasm and opportunistic behavior leads to sub-optimized or point solutions.

Organizations need to make sure that the supporting building blocks for AI solutions are in place. Enterprise solutions need to be real-time. As an example, enterprise resource planning systems must be able to process transactions, data and analytics at the same time (milliseconds). If you don’t, any integrated A.I. solution has limited value.

As an example, a chatbot in a customer service operation must be able to access actual data about a customer and all the transactions that have occurred in order to provide correct answers. If the company has a batch process for billing the chatbot cannot provide that.

Technology and consulting firms push customers hard down the path to digital. That’s the right thing to do, because the potential of A.I. and other technologies (e.g. blockchain) are of the same disruptive order of magnitude as steam, electricity and internet. However organizations must develop an enterprise-wide smart strategy first. That strategy shapes the journey to digital smart and identifies any prerequisites for emerging technologies.

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