About the author Bill Schmarzo is CTO for IoT and Analytics at Hitachi Vantara. Data is a unique resource. It never runs out and never wears out, gains value over time, can be used indefinitely, and is abundantly available. In the age of "digital Darwinism," when rapid innovation means that digital transformation will separate the winners from the losers, data is a company's most valuable asset. TechRadar Pro spoke with Bill Schmarzo, Hitachi Vantara CTO for IoT and Analysis and Data Guru, to find out how organizations can survive and thrive in challenging times by exploiting the information contained in their data.
Many companies still struggle to capture the true value of their data. Of course, we've all heard the maxim "Data is the new oil", it just means that data is really valuable, right? Yes, but the value of oil is not the product itself: crude oil must undergo a refining process to become something valuable, useful. And the same goes for data. Raw data is not valuable, it is prepared data that will become your source of income. Companies have a lot of data that doesn't pay them anything. Finding the best of all this data is one of the biggest challenges for today's leaders to stay up at night.
How should companies use your data? Where to start?
Companies need to think differently. Businesses are survival of the fittest and are the organizations that have adapted to technological change and have used new technologies to their advantage, which have continued while others have disappeared. We live in one of the most exciting periods of innovation in human history. Advances in 5G, IoT and AI will revolutionize every industry, from healthcare to manufacturing. The deployment of new technologies to replace traditionally human-centric processes may have slowed it down during the Industrial Revolution, but it is not digital transformation. Companies need to think about how these technologies, along with the vast amounts of data they will generate, can be harnessed to create new sources of value for customers, products, and operations. Every company should aspire to become the best in its industry in exploiting the economic value of its data. The most important question business leaders need to ask now is: how effective is your organization in leveraging data and analytics to drive your business model? But if you ask an IOC or a CEO this question today, many of them won't know how to answer it.
What about data protection? If new technologies create even more data sources, how can companies manage all this data, turn it into useful information, and ensure regulatory compliance?
The data landscape is becoming more complex. The amount of unstructured data is growing rapidly, which is bad news when it is estimated that only about 1% of unstructured data is being analyzed. And now, we're also starting to collect different types of data: sensors that can capture vibration data or even sound data. Therefore, it is not surprising that today, approximately 80% of the work of a data expert is dedicated solely to the preparation, collection, cleaning and organization of this data, instead of high-level analytical work that will lead to efficiencies and positive changes. So yes, it's a problem that will only get worse. DataOps is one of the answers: it is the missing piece of the puzzle. It is a data collection, management, and retention methodology that automates many of these time- and labor-intensive processes. And of course, with automation, you can expect fewer human errors, making for a more reliable and efficient practice that ensures data is in the right place, at the right time, and accessible. to the right people.
Who is responsible for ensuring that an organization's data is actually used?
The digital transformation, the monetization of the data -- these are not attempts with data scientists in the organization or just in the IT department, because it's not just about technology, it's a conversation. economic. It starts with a basic understanding of the company and its main business objectives. "Data specialists" who have their heads in algorithms all day are probably not in the best position to answer questions like: What does our organization want to achieve in the next 12 months? And that's not what they're hired for. It is the stakeholders who make the decisions who need to be able to think like data scientists: understand where and how the insights from their data can be applied across the enterprise. For example, many clients have complained that I have standalone analytics projects that never go anywhere because they are developed in isolation, never being operationalized or reused across the company. This is the curse of "orphan analysis". It is not a technological problem, it is an organizational problem. In the end, digital transformation is a group project. In other words, to be successful, you need collaboration within the company.
What does success look like?
In the end, it is the organizations that turn their raw data into meaningful information, that truly exploit the economic value of their data to reinvigorate their business model, who will be the winners. Is there a blueprint or five-step plan for instant digital transformation? No, of course not! Because digital transformation is not a fad diet. This may not be the most satisfying answer, but it will require a mindset shift and organizational change, and it doesn't happen overnight. Bill Schmarzo is CTO for IoT and Analytics at Hitachi Vantara.