Customer data should be protected by a firewall, and if properly protected, can still be used to perform valuable analytics
In 2006, British mathematician Clive Hamby declared that data is the new oil and could therefore fuel a new data-driven industrial revolution.
Since he and his wife helped Tesco receives £90 million From his first attempt to get a Clubcard, he should know. It seems that the “cranes” there are already pumping information black gold to the surface: what is expected to be the global market for big data analytics More than $745 billion by 2030– And while it may not be the most reliable measure, big tech companies are Throwing billions at artificial intelligence At a rate described as “one of the largest cash infusions into a given technology in the history of Silicon Valley.”
This is what we are told happens. But is this really so? Are organizations honestly and consistently monetizing all the data they have, and thus using it for competitive advantage and innovation?
Even more troubling is whether the safeguards we have put in place, such as the GDPR and other global restrictions on data privacy, are being deployed in ways that make them unnecessarily restrictive of the full flood of AI-driven innovation?
We were keen to understand where organizations really stood with this exploit, and whether data monetization and a defined, repeatable workflow already existed.
Specifically, we wanted to investigate whether organizations were truly leveraging the full potential of their data and operating with appropriate levels of protection for that data, and whether that data could be accessed in a time frame that was meaningful to the business.
So, we researched and spoke to 600 CIOs, CTOs, CTOs, CDOs and CDOs at organizations in everything from aviation to retail and telecom.
It was interesting to hear first-hand what they told us about the real state of data handling there.
Innovation through data, yes. But enough of it? no
What these practitioners told us is that although they fully see the potential for innovation and profit opportunity in their data, they struggle to leverage it cost-effectively.
For example, 56% of all respondents said they had already achieved significant improvements in both customer and employee experience (customer and employee experience); 44% of respondents confirmed that access to data directly led to a profit advantage of between 6 and 10% – 20% put this number at 11 to 20%. In 2023, more than half (57%) of the organizations we spoke to introduced new products and services based on insights they got directly from mining their data.
But 32% admitted it could take 3 to 6 months to access the data they need to run the apps to do so. 37% said the process could take between one and two full months, and only a small percentage, just 2%, said they could access data in “less than a week” or immediately.
To clarify what we mean by “data”: we’re not talking about transactional data like EPOS data – we mean potentially good data, about customers, their behaviors and attitudes.
When we say that, CISOs and data protection officers will immediately put a “sensitive and classified data” tag on this – putting this data in the cold and closing many doors around it.
Which is as it should be – I don't mind other people knowing what kind of sandwich I bought at the petrol station for example, but I don't mind if I link that purchase to my National Insurance number.
If the data firewall is set too high, does it mean missing out on millions in potential profits through data exploitation (and potentially billions for a public UK company) in a missed opportunity?
Could putting all your effort into the Internet be a big mistake?
Yes and no. We need that Protect our dataThese laws exist because of shocking bad behavior by some technology vendors.
But there is worrying confusion about what we are really protecting here. IT has somehow become obsessed with cybersecurity, but has not yet thought about data security.
Consequently, we spend $180 billion annually on cybersecurity, while data security strategies are less understood and adequately resourced. Ultimately, all of this cybersecurity is there to protect your networks, your infrastructure, and your endpoint… but 99 times out of 100, bad agents don't care about any of that — they're after one thing, your data.
What happens then is that IT managers turn all their attention to cybersecurity, GDPR, and other data privacy laws, thinking that solves the data problem. But if you secure your data in ways that make it essentially “dark” for the type of AI analysis you want to run on it, you're sitting on your oil, not moving it around. The good news is that there is a solution that satisfies all stakeholders in saving and using customer data.
Use the right technology to protect all that sensitive information
The way out of this is for you to understand that there are tried and trusted ways to let your data scientists and machine learning platforms access data in ways that preserve my 100% NI number from that visit to the petrol station, but still allow you to do something in the transaction ( Or sell it to third parties).
It introduces privacy-enhancing technologies (PETs) such as encryption and anonymization, which can be used to protect sensitive information in ways that prevent anything an IT manager would worry about, as that “sensitive and classified” personal data is replaced with a value that prevents individual consumer data from being directly identified.
What IT managers in this survey tell us is that most organizations are investing heavily in PET through encryption, with pseudonymization and encryption being used or less understood.
Personally, we think this is a mistake – pseudonymization in particular is a very effective way to make customer and partner data privacy-secure but open to quick analysis.
However, we were very encouraged by how our analysis showed the need to look again at data security, with almost all respondents (96%) saying they plan to invest part of their IT budget on this issue this year – with 49% considering that they should It ranges between 11-15% of their entire IT budget.
In short, these numbers show that business owners know that data is their biggest asset, but they also demand a secure way to use it so they can analyze it all for gain in ways that don't expose anyone in the company or its employees. Suppliers.
Shortly after that famous comparison between data and oil, Australian economist Michael Palmer pointed out that although oil in its raw state has value, “if it is not refined it cannot really be used.” Could thinking about data more than infrastructure security be the improvement step we're missing?
Written by Paul Mountford, CEO of Protegrity