Krishna Subramanian, COO at Komprise, discusses the benefits disruptive technology can bring to a business as more and more companies adapt to Digital Transformation. She also talks about the transformative effects of AI and ML in data management and how this will allow businesses to become more agile, adaptable and efficient.
In the wake of the success of companies like Netflix, Uber and Airbnb, the superficial attraction of ‘disruptive technology’ can seem extremely alluring for many businesses. But what is disruptive technology? And how disruptive should it be?
This type of business is clearly effective at deploying technology to disrupt settled markets, but that doesn’t mean the technology in itself is disruptive. Many businesses with well-established IT infrastructures and architectures do not have the flexibility and agility that newer companies like Netflix have in deploying this technology. However, that doesn’t mean that these more traditional organisations cannot adapt. If anything, the success of startup businesses like Uber and Airbnb reinforce the message that businesses need to adapt and transform to new architectures and swiftly, if they are remain competitive – but this needs to be balanced with the cost of business disruption.
The vast majority of organisations need technology that is transformational without causing business disruption. Disruptive technology cannot be adopted wholly for its own sake, or because an organisation believes it can reinvent itself and become an Uber overnight – it can’t. The best disruptive technology is transformational, but not destructive, to adopt. It enables a business to transform to a newer, simpler, better way of doing things, without requiring the company to disrupt users and take a hit on productivity, service and sales.
There are technologies that enable organisations to create new and more efficient ways to work, but without interrupting the overall business. For example; Amazon, Facebook, Google and Apple are all a testament to the power of successfully innovating, without invasive IT projects.
Transforming data management
Organisations that want to strike a practical balance need to begin at the data management level. Data is the lifeblood of most organisations and being able to transform how this information is managed, stored and collected will allow the organisation to innovate. Many businesses struggle with storage costs, the sheer volume of data being generated and data silos. Using technology to transform the approach to data management and overcome these obstacles will leave businesses in a far better position to successfully evolve. Two technologies that have the capability to deliver massive disruptive change in this area and across the whole organisation, are Artificial Intelligence (AI) and Machine Learning (ML).
AI and ML are disruptive enablers because they have the potential to transform technology that is essentially low-level automation today, into intelligent learning systems. Therefore, the big benefits of AI and ML are higher levels of automation, simplicity and efficiency. AI’s reliance on data is expected to lead to significant transformation in the data management industry. Adaptive automation and Machine Learning will enable data management software to perform in smarter ways by observing and leveraging patterns. AI-based data management will start to be able to think outside the box, offering more intelligent ways to manage business needs.
AI will also allow organisations to use intelligent software to move away from cumbersome, tedious, error-prone and time-consuming rule-based policies to setting goal-based policies. Rule-based data management policies typically rely on a human to predict every single eventuality and program a rule for it. Moving to goal-based policies where intelligent software works out the appropriate way to achieve them would ensure IT is in control of the outcome without the manual heavy-lifting and errors associated with the rule-based approach.
In addition, organisations can benefit from the improved search and discovery that AI can deliver. A significant roadblock to adoption of Big Data has been the difficulty in finding the right datasets to analyse, with data strewn across billions of files and different storage silos, both on premises and in the cloud. AI can drive efficient search and discovery of data to help extract value from it more efficiently, even when considering today’s massive scale of data. With AI, intelligent software can pull information from a much wider data lake, no matter where it is stored.
It’s true that not every company can be an Uber or Airbnb, but every business can be transformed. So perhaps it’s time to evolve the way we see disruption because disruptive technology, when applied through transformation, can help to elevate organisations. The transformative effects of AI and ML in data management will allow businesses to become more agile, adaptable and efficient. Data can drive business decisions and being able to leverage the benefits of an innovative data management platform will help to give organisations a competitive edge.
