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The importance of putting your data to work

The importance of putting your data to work
(Image credit: Pixabay)
About the author

Bill Schmarzo is the  CTO for IoT and Analytics at Hitachi Vantara.

Data is a resource unlike any other. It never depletes and never wears out, it increases in value over time, can be used indefinitely and is available in abundance. In the era of “Digital Darwinism” – when rapid innovation means digital transformation will separate the winners from the losers – data is the company’s most valuable asset.   

TechRadar Pro spoke to Bill Schmarzo, Hitachi Vantara CTO for IoT and Analytics and data guru, to find out how organisations can survive and thrive through challenging times by unlocking the insights in their data.  

What are some of the challenges businesses currently face when trying to use data to digitally transform? 

Many organisations still struggle to even grasp the true value of their data. Sure, we’ve all heard the maxim “data is the new oil” – it just means data is really valuable, right?  Well yes, it is. But the value of oil isn’t the product itself – raw oil must undergo a refinement process to be transformed into something valuable, something of use. And the same goes for data. It’s not raw data that holds value – no one actually wants to buy your data – it’s curated data that is going to be your cash cow. 

Businesses have reams of data on their hands that isn’t making them any money. Figuring out how to get value from all that data is one of the biggest challenges keeping today’s business leaders up at night. 

How should companies go about using their data – where can they start? 

Companies have to think differently. Business is survival of the fittest and it’s the organisations that have adapted to technological change, and employed new technologies to their advantage, that have endured while others have gone extinct.

We’re living through one of the most exciting periods of innovation in human history. Advancements in 5G, IoT and AI are going to revolutionize every industry, from healthcare to manufacturing. Deploying new technologies to replace traditionally human-centric processes may have cut it back in the Industrial Revolution – but that’s not digital transformation. 

Businesses need to consider how these technologies – and the vast amount of data they will generate – can be leveraged to create new sources of customer, product and operational value. Every company should aim to become the best in their industry at exploiting the economic value of their data.

The single most important question business leaders need to ask themselves right now is: how effective is your organisation at leveraging data and analytics to power your business model? But if you pose that question to a CIO or CEO today, many won’t know how to answer it. 

What about data protection? If new technologies will create even more sources of data, how can businesses manage all that data, turn it into useful insights and still ensure it’s compliant with regulation? 

The data landscape is getting more and more complex. The amount of unstructured data is rapidly increasing, which is bad news when it’s estimated that only around 1% of unstructured data is actually being analysed. And now we’re starting to collect different types of data too – sensors that can capture vibration data, even sound data. 

So it’s not surprising that around 80% of a data scientist’s job today is just spent in data preparation – collecting all this data, cleansing it and organizing it – rather than doing the high-level analytical work that will actually drive efficiencies and positive change. 

So yes, this is a problem that is only going to get more pressing. 

One answer is DataOps – it’s basically the missing piece of the puzzle. It’s a methodology for data collection, management and curation that can automate many of those labor-intensive processes taking up a data scientist’s time. And, of course, with automation you can expect less human error – making it a more reliable and efficient practice that ensures data is in the right place, at the right time and accessible to the right people. 

Whose job is it to ensure an organisation’s data is actually getting put to work?

Digital transformation, data monetization – these aren’t endeavors that sit with the organisation’s data scientists or just live in the IT department, because this isn’t just about technology – this is an economic conversation. It starts with a fundamental understanding of the company and its key business objectives. 

The “data people” who have their heads in algorithms all day are probably not the best people to answer questions like: What does our organisation want to achieve in the next 12 months? And that’s not what they’re hired for. It’s the stakeholders who make those decisions that need to be able to think like data scientists – understanding where and how insights from their data can be applied across the business. 

For example, so many clients have complained to me about having standalone analytics projects that never really go anywhere because they happen in isolation, without ever being operationalized or reused across the company. It’s the curse of “orphaned analytics.” That’s not a technological problem, it’s an organisational one. So, ultimately, digital transformation is a group project – meaning it requires collaboration across the business to be a success.

What does success look like?

In the end, it’s the organizations that convert their raw data into meaningful insights, that really exploit the economic value of their data to reinvigorate their business model, that will be the winners. 

Is there one set template to follow, or a five-step plan to instant digital transformation? No, of course not! Because digital transformation isn’t a fad diet. It might not be the most satisfactory answer, but it will take a mindset shift, and an organisational shift – and that doesn’t happen overnight.

Bill Schmarzo is the CTO for IoT and Analytics at Hitachi Vantara.