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21 September, 2021
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HomeAcademyAutobotXManaging Data To Drive Competitive Advantage

Managing Data To Drive Competitive Advantage

One of the most important lessons we’ve learned from the pandemic is just how important technology is to building robust and thriving businesses. Organizations that have prospered in the last nine months have done so by leveraging cloud computing, high-speed networks, artificial intelligence (AI), and the internet of things (IoT) to push forward their digital transformation agendas.

All of this has been fuelled by data, as we’ve found new and innovative ways to measure, record, understand, and react to the changing world around us. This is true for everyone, from those responsible for tracking and attempting to contain coronavirus, to businesses reacting to the changing needs and behaviors of their customers.

Digital Transformation and Data

In the so-called data decade, when data is expected to hit 175ZB worldwide by 2025, less than 0.5% of the world’s data is actually being analyzed,  our lives become increasingly digital and virtual. Harnessing it and using it to generate competitive advantages is the number one challenge facing business leaders and strategists today. To put it starkly, if you don’t become the leader in data-driven business activity in your industry, someone else will.

This topic – and particularly questions around how data can be leveraged in the real world to generate real business growth – was the subject of an event I took part in recently, hosted by Dell Technologies. Along with experts such as Florian Baumann of Dell Technologies, Michael Cote at VMWare, and Roger Benson of AMD, we discussed how to turn data into useful insights, how to overcome challenges inherent in working with data, and how it is affecting different industries, during a series of panel discussions and question-and-answer sessions.

The Data Challenges

And there are certainly many challenges. One of the first common mistakes we identified in our discussion is the danger of putting technology before business. There’s sometimes a propensity to think, “This is an amazing new technology, what can I do with it?” – when in reality, the correct approach is “This is the problem I have, what technology should I use to solve it?”

In one panel discussion, we focused on how these issues are affecting the fields of mobility and automotive. Today’s generation of connected, smart vehicles routinely gathers and transmits up to 10 TB of information per day, from sensors around the vehicle monitoring every aspect of its performance. As we move towards even more autonomous, self-driving vehicles, the volume of that data will explore further, taking in-camera and lidar data. The challenge for vehicle manufacturers is to take that data and use it to make sure they are meeting their customers’ needs and expectations better than their competitors are.

As Baumann puts it, “The vehicle will be a data center on wheels … vehicle data is the most important asset we have in the industry. But very often, we have to deal with a lot of challenges … how do we collect this data and what kind of data needs to be collected, and how to identify valuable training data. Because we are collecting up to 100 TB of information per vehicle, per day – we have to identify what’s important.”

How Telsa Is Harnessing Data

A fantastic example of data being harnessed to provide new business opportunities is Tesla’s Autobidder project. While Tesla is best known for its electric vehicles, a knock-on effect of the data it has collected over the years is a huge amount of information gathered on the way energy is used. As a result of owning this data, it has been able to develop a solution for trading and distributing energy assets in real-time. It allows energy producers to sell excess power they generate to business or residential users, driving down energy costs by creating competition with existing suppliers. The platform makes use of AI to predict demand across different regions and to set prices, as well as Tesla’s cloud computing infrastructure for data storage and processing.

What we see here is a company that was able to create an entirely new revenue stream by leveraging its existing capabilities in order to solve a problem common to its customers – expensive energy.

This also illustrates another key point covered in the conversation, which is that these key tech trends behind today’s smartest breakthroughs and innovations don’t exist in isolation. AI, cloud, edge computing, and IoT – all underwritten by big data – are trends that feed and supplement each other. So often, an understanding of all of them, as well as the ways they intersect each other, is very useful when it comes to deploying them in business.

Three Ways Businesses Can Harness Data

During our discussions, I also cover what I consider to be the three core ways that businesses can benefit from this data boom, as well as the new tools and applications such as AI and IoT that let us harness it.

The first is by using data to make better-informed decisions. Data-driven decision-making succeeds or fails depending on our ability to use data to make predictions. Asking ourselves, based on past experiences and observations, are we more likely to achieve a successful resolution if we take path A or path B? The most advanced applications of this predictive technology operate using real-time data – monitoring and acting on insights as they happen and in-the-moment. As tools for real-time data capture and analytics become more efficient and affordable (for example, through cloud and edge services), companies will increasingly work with newer, faster-moving datasets to provide increasingly accurate predictions and increasingly valuable insights.

Secondly, digital leaders need to consider how they can use data and digital strategies to offer their customers better products and levels of service. Often this means building a better understanding of who the customer is and how they want to use our service. Netflix and Amazon do this by understanding what we are likely to want to watch or buy. Fitness devices leverage cloud computing, edge computing, AI, and IoT to monitor our activities and sell the data back to us as insights that can make us healthier. I even have a toothbrush that uses AI to monitor how well I brush my teeth and point out areas that I might have missed! Vehicle manufacturers that are moving into self-driving cars and delivery vehicles, and even autonomous passenger drones (now operational in Dubai) are all examples of businesses finding new ways to use data to solve customer problems.

Michael Cote, digital transformation specialist at VMWare, highlighted some of the methods software companies are using to create applications that are more in-tune with their users’ needs. This is enhanced when development teams are able to monitor user data and use it to make decisions about enhancing their products.

“If you’re given weekly data, you can start to make very strategic decisions, like stopping a feature no one uses or adding a new feature … a study some time ago found people only use a third or less of the features in any given software. If two-thirds of the app layer are things no one uses or cares about, that’s a tremendous waste, and developers can start paying attention to that third of data we’re using.”

The third way in which companies should be using data and advanced data processing technology is to develop smarter and more efficient internal processes. Multinational manufacturing giant Unilever has automated huge swathes of its recruitment and HR processes, by creating online cloud-based services that use AI to screen initial applications from would-be employees. It also provides HR services to existing employees using chatbot technologies involving natural language processing (NLP) technology to converse in natural human languages. Predictive maintenance is a reality in industrial sites around the world now, where networks of cameras and sensors monitor machinery and learn to predict where and when failures will happen, meaning they can be fixed more swiftly and cost-effectively.

For me, it’s becoming clear that in order to become leaders or maintain their place as leaders, during the 2020s, companies are having to rethink how they use data from the ground up in order to hit all three of these objectives. This means new roles and skillsets will need to be developed or hired in, covering everything from data science to DevOps.

To achieve this, every executive and decision-maker in a company should be thinking and acting as if they are a leader of a tech company. This means putting data at the center of everything they do and working to ensure this is true across their organization.

Source: LinkedIn, January 20, 2021

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