Driven by new thinking, new technology capabilities and the drive toward digital business, the usage of data is changing radically. Here are seven data-driven differences between the digital and pre-digital world:
Training machines with data is starting to become a mainstream way to solve complex business problems. Gartner describes the promise of AI-driven analytics as “to amplify the speed and scope of human expertise in a wide range of business decision making.”1 Whilst establishing Big Data is an important foundational step, solving complex business problems is closely linked to the development of Machine Learning, a branch of Artificial Intelligence.
Machine Learning has historically been restricted to those use cases that could bear the high costs incurred by a computationally intensive, somewhat hit and miss (‘iterative’) process that also required both relatively expensive software and the skills of a data scientist. This is changing rapidly, however, due to three factors: the rapid expansion of data sources, significantly improved algorithms and substantially more-powerful computing power, all of which is bringing machine learning capabilities to bear on a broader set of business challenges.
The move toward mainstream Machine Learning is a significant departure from previous practice, as we have traditionally solved most business problems by processing data with logic, not learning from the data itself via algorithms.2 Machine Learning is also able to make predictions based on patterns and the other factors it has been trained with, which is extremely valuable to business.
Sensing the physical world in real-time. The Internet of Things (IoT) has become one of the fastest growing and high impact new technologies. IoT provides a connection between ‘things’ (objects) and people, and a much higher level of real-time sensing than has been possible before. This promises transformational capabilities, not just in business but also across society. When applied to a city, for example, it can improve infrastructure and services to citizens based on the real-time data IoT devices transmit. According to IDC, 25 percent of all data will be real-time by 2025, and 95 percent of that real-time data will be driven by IoT.3
The returns on IoT can be significant – according to Vodafone’s annual IoT report4, where organizations reported an increase in revenue from adopting IoT, it averaged 19 percent. Where they reported a reduction in costs, the average was 16 percent. This is driving adoption at scale, with the number of organizations deploying more than 50,000 connected devices doubling since 2016.
Digitizing physical matter. 3D Printing (additive manufacturing) creates a three dimensional physical object from the data contained in either a digital design or a digital scan. Unlike conventional manufacturing where materials are removed to make the finished part (often under computer control), material is added layer by layer.
In the case of a digital scan, it is fair to describe this process as the digitization of physical matter, as the digital scan captures the form of the object and the 3D printing renders this into a physical copy. Whilst initially this technology was limited to rapid prototyping, some industries – such as aerospace – have moved beyond this stage to produce finished parts for mission-critical use.
3D printing has also been embraced by the healthcare industry to produce 3D models that can be used in practice surgery and pre-op preparation.5 It is predicted that by 2021, 40 percent of manufacturing enterprises will have established 3D printing centers of excellence.6
Humans augmented with data. Human beings are gaining new abilities due to digital augmentation. Head-mounted displays, earbuds and smart watches are all examples of wearables that deliver data to the user, whilst microchips can be implanted to capture data or initiate gesture commands. Wearables will contribute to the growth of endpoints (the end of the network), which also include cars, phones and IoT sensors.7 Going beyond data to augment workers with AI is predicted to generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity.8
Reliance on data in daily life. IDC estimates that daily digital interactions will grow by more than a factor of 20 over the next 10 years, driven by more online interactions and interactions with digital homes, appliances, vehicles and wearable and implantable devices. What’s more, these interactions will become more automated over time, creating a life increasingly dependent on data.9
Stronger data rights for individuals. Business and government use of personal data is now so extensive that governments around the world are moving to regulate its use so as to safeguard citizens. GDPR is the most notable regulation in this area and provides data subjects (the individuals the personal data relates to) with a set of rights over how their personal data is used and administrated. Whilst some of these rights existed before GDPR, the regulatory climate is moving from relatively laissez-faire to one of clearly defined individual rights that will be strictly enforced.
IDC recently described an implant use case in a convenience store chain where employees had microchips implanted into their hands. This allowed them to open doors, log on to their computers and use vending machines via gestures.10
Data generated by the individual can also be used with wearables. A team at Aalto University in Finland analyzed how the unique nature of each individuals gaits and can be used to create individual ‘fingerprints’ that could be employed to pair wearable devices.11
Data on the balance sheet. One of the most intriguing analyst predictions about data comes from IDC, which predicts that by 2027 we will be able to value data assets on balance sheets in accordance with GAAP standards.12 Data as a Service (DaaS), defined as “the process of locating, extracting, deriving, aggregating, enriching and curating various types of data from social media, Internet of Things, government, and corporate data for resale in the form of value added content” is a strong contributor to this change in the status of data.
With all the changes described above, it is no surprise that the importance of data as a business priority continues to grow. A recent Commvault-sponsored survey13 shows that IT personnel and executives think that understanding data, from both a management and an analysis perspective, are among the most essential priorities for future businesses’ success.
The same survey showed that IT personnel and executives consider that data management and analysis are more essential to the future of their businesses than quarterly earnings, corporate reputation, or even customer service – indicating to us that important business outcomes will increasingly be based on data and an organization’s ability to make use of it effectively.
1 Gartner, Analytics and BI Strategies Primer for 2017
2 Gartner, Analytics and BI Strategies Primer for 2017
3 IDC: Monetizing data in the Global Datasphere, 2017
4 Vodafone IoT Barometer for 2017/18
5 Gartner, Predicts 2018: 3D Printing and Additive Manufacturing
6 Gartner, Predicts 2018: 3D Printing and Additive Manufacturing
7 IDC: Monetizing data in the Global Datasphere, 2017
8 Gartner: How to Start a Machine-Learning Initiative With Less Anxiety, 2017
9 IDC: Monetizing data in the Global Datasphere, 2017
10 IDC, ICT Market Update, 2017
11 IDC, ICT Market Update, 2017
12 IDC, ICT Market Update, 2017
13 Quadrant Strategies: Poll with IT Executives and IT Personnel, 2017