BACpress : According to a recent report by IDC, digital transformation spending is expected to surpass $6 trillion dollars within the next four years, and it’s believed that enterprises globally will spend more than $1 trillion on digital transformation before the end of 2019 alone.The report also notes that industries like process and discrete manufacturing and transportation will be some of the biggest spenders. These investments are fueling the growth of machine learning (ML) and the internet of things (IoT) to improve customer experiences and operational efficiency and accuracy. As companies have begun adopting digital transformations, there are a few things I’m looking forward to seeing more of in 2020.
Big Data Grows To Ginormous Data
According to a Network World article, “IDC predicts that the collective sum of the world’s data will grow from 33 zettabytes this year  to 175ZB by 2025, for a compounded annual growth rate of 61%.” (One zettabyte is equal to one trillion gigabytes.) This means that we’ll see not only a massive increase in the amount of IoT-generated and real-time data, but an abundance of new data created and managed by enterprises.
By 2025, nearly 60% of the 175 zettabytes of data will be created and managed by enterprises versus consumers. Driving this growth is IoT edge devices sending waves of information to the cloud.
IoT And ML Are No Longer Future Technologies
The workforce is just not equipped to analyze such large amounts of data, so enterprises will be (and already are) looking for new ways to do so using ML and augmentation. As a consequence of ginormous data, IoT should be viewed as the backbone of today’s data-driven economy. To make sense of this data, the evolution of IoT products and services will become less focused on core technology and more focused on technologies that make better use of the data gathered.
Data As A Service
With all of the data developed day to day — in 2020, every person will create 1.7MB of data per second — it only makes sense to use this data to make more knowledgeable business decisions.
For example, KAR Global has released a platform that gives automotive dealers a wide-angle view of cars currently in demand. The platform also shows the best ROIs and how dealers can move less-desirable vehicles, in addition to inventory segmentation analyses and recommendations for remarketing. All of this uses data available from KAR and its customers in a proprietary way that benefits the auto sales industry as a whole. We should expect other industries to begin using the DaaS model in the same way for decision-making.
The Decline Of Packaged Apps
Instead of downloading apps, soon progressive web apps (PWAs) will be much more commonplace. PWAs are accessed the same way as those downloaded from app stores, but they load faster, they are more secure and they are far smaller in size. Companies such as Lumavate help developers in industries such as motorsports, medical manufacturing, construction, and financial services move from native applications to cost-effective PWAs that ultimately deliver a better user experience and free up space on devices.
Prescriptive analytics goes beyond forecasting possible options and instead suggests a range of actions and the potential outcomes of those actions. As more tools become available, this type of data analyzation is becoming a holy grail.
Autonomous vehicles are fantastic examples. A self-driving car must make millions of calculations based on analyzed data to decide when to turn, change lanes and so on.
Oil and gas industries are also using prescriptive analytics to assess supply, demand, pricing and impacts on the industry when they change. Prescriptive and predictive analytics work together as business intelligence that gives executives insight, as well as foresight, into their company data.
More Jobs Will Actually Be Created From AI Rather Than Lost
AI is predicted to eliminate 1.8 million jobs but also create 2.3 million jobs in 2020. Industries such as healthcare, education and the public sector will see growing job demands. While middle- and low-level positions will take the biggest hits, new roles for these types of workers will open up in sectors such as solar-powered energy, which is now the fastest-growing industry for job creation. Industrial manufacturing is also an industry working to reskill its workforce, marrying the technical and nontechnical know-how of its employees for the digital transformation.
Work Augmentation Through Machine Learning
Machine learning used to mean automating tasks and replacing human work. The focus now is on ML’s ability to augment human work to make us more productive and efficient. In 2020, we’ll see machine learning models engineered to optimize logistics, retail and robotics. Things like recommendation engines, fraud detection, and robotic process automation will become standard and make industry competition fierce.
Robot Process Automation (RPA)
This year, Deloitte saw enterprises double the number of intelligent automation tools (e.g., robot process automation) for day-to-day business tasks such as inventory management. The manufacturing industry, in particular, has been watching RPA for several years and will increase its adoption in 2020. Already, successful RPA solutions in manufacturing include order fulfillment, purchase order processing, inventory reports and transportation management. Executives who have implemented RPA note that employees are more engaged by way of strategic and creative thinking.
No matter the industry, investments in IoT, ML and data analytics will increasingly be required to stay competitive. Most of what we’ll see in technology next year and in the future will center on IoT products and services that enable us to comprehend data acquired by the second. Building and analyzing data now gives enterprises more information than ever before. In 2020, they will use this data to elevate customer, employee and stakeholder experiences.