Disruptive Innovation vs Sustaining Innovation in AIOps

Disruptive Innovation vs Sustaining Innovation in AIOps

AIOps technologies bring together big data and ML tools to support a range of IT operations functions. With a new technological trend, it is always useful to analyze things from a macro level. When it comes to the question of disruptive innovation vs sustaining innovation, what is AIOps? Which kind of innovation does it offer companies in different industries?

What is a Disruptive Innovation?

We have disruptive innovation vs sustaining innovation. What is the first of these?

American scholar Clayton M. Christensen coined the term “disruptive innovation” in a paper for Harvard Business School back in 1995. He explained that for an innovation to be disruptive, it had to:

  1. Transform a product/solution that only a few people with a lot of money and skills had access to;
  2. Create a more simple, low-grade solution which is more affordable and accessible to a greater population;
  3. Originate in low-end (less demanding customers) or new market (where none existed) footholds;
  4. Have a significantly different business model compared to the incumbent, and;
  5. May or may not overthrow established industries and existing market leaders.

Usually, disruptive innovations are underrated and deemed inferior in quality. But with the constant development of technology, coupled with its affordability and greater accessibility, they eventually grow more desirable than their established competitors.

Some famous examples of disruptive innovations are the advent of personal computers vs mainframes; the replacement of cathode ray tube (CRT) TVs and monitors with liquid crystal display (LCD) screens; and Blockbuster’s bankruptcy due to Netflix’s innovation in streaming services.

 

What About Sustaining Innovation?

In the struggle of disruptive innovation vs sustaining innovation, what of the latter kind? 

Sustaining innovations target demanding, high-end customers with better performance than what was previously available. It doesn’t create new markets; it develops existing ones.

“Some sustaining innovations are the incremental year-by-year improvements that all good companies grind out,” Christensen noted. “Other sustaining innovations are breakthrough, leapfrog-beyond-the-competition products.”

This is often the kind of innovation that established companies carry out, and they almost always win the battles of sustaining technology. This strategy warrants making a better product they can sell for higher profit margins, and they have the resources to fund and develop these technologies. 

Market leaders don’t often pursue disruptive innovations upon first emergence because (1) they’re not profitable enough, and (2) they can take resources away from sustaining innovations that are, coincidentally, needed against current competition.

Examples of sustaining innovations are the displacement of carburetors with fuel-injection mechanisms in gasoline engines, and Pfizer’s discovery and development of oxytetracycline, a broad spectrum antibiotic.

So What Is AIOps?

So what of AIOps? In the disruptive innovation vs sustaining innovation dichotomy, where does it land?

AIOps, as defined by Gartner, is the application of machine learning (ML) and data science to IT operations problems, “to enhance and partially replace all primary IT operations functions, including availability and performance monitoring, event correlation and analysis, and IT service management, and automation.”

AIOps is currently solving IT industry problems and providing various benefits:

  • Breaking down data silos, and helping companies manage and process huge chunks of data;
  • Eliminating IT “noise”– operational problems that can cause higher operating costs, performance issues, and risks;
  • Delivering smooth customer experience by making complex automated decisions through data collection and analysis, and;
  • Overcoming monitoring and analytics challenges, like collating and analyzing data from multiple sources, and reducing time and attention spent on mundane, repetitive tasks.

The answer is: AIOps is a bit of both. It has become a disruptive force in IT operations management. However, it still is currently serving as a sustaining innovation, by way of improving IT Operations and making developers’ lives easier averting problems, cutting costs, improving customer experience, and allowing IT personnel to focus on new innovations. 

To see AIOps in action right now, request a demo of OpsaniAI here and see how it’ll help your company save $$$ and time.

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