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What it takes to become a smart enterprise - VentureBeat

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We have smartphones, smart cars, even smart cities. In fact, there aren’t many things left that aren’t becoming smarter by the day.

But what about smart enterprises? With digital transformation well underway and artificial intelligence quickly making its way into the IT stack – in part to support smartphones, smart cars, and smart cities – how can we expect the enterprise itself to become smarter? And will we even be able to pinpoint the moment in which it becomes smart?

Smart actions, not words

Clearly, smartness is more than a mission statement or press release touting things like data science and intelligent analytics. As tech consultancy Plekton Labs noted recently, a smart enterprise is defined more by the way it uses these and other technologies, both strategically and operationally. To be considered smart, the enterprise will have to display a range of capabilities that it doesn’t have now, or at least cannot leverage to make an appreciable impact on the business model. These include the following:

  • Continuous availability
  • Employee empowerment at all levels
  • Collaboration inside and outside the organization
  • Deployment of user-centric tools and services
  • Improved innovation through next-gen networks, operations, and processes
  • New levels of productivity and creativity
  • Support for rapid digital transformation in both processes and practices.

While this transformation doesn’t depend solely on AI, it’s fair to say that it will play a leading role. As more tasks become automated, the enterprise becomes more responsive to the demands of a digital economy, in part by focusing its human capital on key tasks that cannot be automated so easily.

But as Kumar Singh, research director at SAPInsider, notes, it’s not like a day will come when an enterprise becomes smart at the flip of a switch. Instead, we’ll see gradual steps in maturity as organizations embrace these new capabilities.

A freshmen enterprise, for example, is still charting out the potential for intelligent operations and data-driven decision-making to alter the business model. Meanwhile, sophomores are starting to implement cultural changes to create new processes and streamline operations, while juniors are taking this to the next level by focusing on the creation of new revenue streams and business models. Finally, senior organizations have converted their operations to rapid, iterative experimentation with an eye toward building customized AI toolchains and developing in-house talent around the new data ecosystem.

The smart (data-driven) plan

None of these milestones will be achieved without a plan, however. Salesforce recently posted four key pillars that organizations should strive for to become a data-driven organization. The first key step is to develop adequate data management, focusing not just on markets or customers but employees, operations, and virtually everything else. Secondly, organizations should choose their data analytics technology carefully. While it may be tempting to deploy out-of-the-box solutions, a more effective strategy is to focus on lower-level tools and programming languages to preserve high levels of flexibility.

From there, you’ll need to upskill your workforce in the use of AI and then embed these new talents directly into business units rather than spin them off into their own department. This provides the fastest, most accurate turnaround for data-driven decisions. Finally, the smart enterprise requires a cultural shift that embraces change. This can only come about through proper leadership and a clear strategic roadmap that incorporates all aspects of the company.

To become truly smart, however, tools like AI must integrate seamlessly into the operational model, says BMC’s Ali Siddiqui. This is why AIOps has become a key strategic imperative for enterprises making this transition. Like with DevOps, AIOps strives to create a more proactive and predictive IT environment in which machines can resolve their own issues using Big Data and advanced analytics. By putting IT at the forefront of digital transformation, it can then accelerate the deployment of smart capabilities across the rest of the enterprise.

As with people, however, smart is a relative term. More than likely, organizations will become very smart at some things and not so smart at others. And no matter how smart you become, there are always ways to become smarter.

Ultimately, the smartest enterprises will be those that recognize how much they have to learn.

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