Data has been called many things, from the ‘new oil’ to the ‘new currency’, but fundamentally it has grown to become one of a business’s most valuable assets. However, like any other commodity, even data can depreciate in value. The value of currency constantly changes and evolves as new types appear, such as the emergence of cryptocurrencies. It’s a similar story with data. As the number of channels we utilise increases, the types of data we collect and use has also changed. And inevitably, this means some data has become outdated and needs to be left behind.
This data is not only less valuable, but holds many dangers for the businesses that continue to keep it. As technology continues to advance, old data gets harder to read, becomes less meaningful and even more difficult to use. It loses its value, eventually becoming obsolete, and this is the point at which employees stop managing it properly. We call this dark data. When data reaches this point, the risks can be very real for businesses. This is particularly true for companies that hold personally identifiable data, such as financial services companies. To deal with the challenge of dark data, these organisations must adopt a more strategic, autonomous approach to data management.
A long history of data collection
From the days of the earliest banks, financial services companies have always used data to improve and streamline the customer experience. We have come a long way from personal customer information written on a paper documents, to credit scores, purchase histories and the telematics data used by an increasing number of insurance companies. Yet, this long history of data collection is part of the problem.
As financial services companies evolve, old data loses its strategic and business value – going dark. With today’s limitless cloud storage systems, it is far easier to make use of digital data than it is physical written records. Inevitably, the latter is filed away and eventually lost. Yet dark data never completely goes away.
Financial services companies are particularly vulnerable to the rise of this dark data. Indeed, the industry holds huge backlogs of stale data, 20 per cent of which are made up of old document files. As smart contracts and blockchain transactions grow in popularity, this type of old data is rapidly losing its relevance and value.
The financial services industry’s heavily regulated environment is partly responsible for creating a culture that is cautious to delete anything. The result of this ‘save everything often’ mentality is that old data takes up valuable storage space.
The out of sight, out of mind nature of dark data also means it stops being properly managed, maintained and protected. Over time, this can pose a major security risk to financial services companies and their customers. With data privacy regulations like GDPR now in effect, consumers are more likely to take action against irresponsible financial services firms than any other sector, so dark data represents a ticking time bomb for data security.
What happens when data goes dark
To fight the dark data problem, businesses must stop it at its source. Ultimately, dark data stems directly from a lax data management strategy. This is not a new phenomenon; indeed, it has long been an aspect of development culture in financial services. Historically, mainframe systems were siloed and when a new application was to be built it would be done in a separate environment. Unsurprisingly, the data these companies hold is now spread across many different databases found in the cloud and on-premises.
When data becomes dark, it is not because of negligence but the complexity of keeping it organised in deeply fragmented IT environments. Research shows that employees regularly struggle with an overabundance of data sources and tools, as well as a lack of strategy and backup solutions. According to our research, the majority (81 per cent) of organisations think their visibility and control of data is unsatisfactory and even more (83 per cent) believe it is impacting data security. Not only is this fuelling the rise of dark data, it is hurting the ability of employees to find and utilise valuable data, resulting in missed business opportunities and wasted resources.
The future of data management
Creating a data management strategy
As data becomes more siloed and fragmented, it is harder to find, manage and protect. This is how dark data turns into a risk. To stop this happening in the first place, financial services companies must create data management strategies that accommodate both recent and obsolete data. At the same time, they have to resist the temptation of a ‘save it all’ strategy. Instead they should take advantage of new tools and platforms that can locate, automatically classify and manage data across multiple environments.
Introducing and enforcing data management policies
Data management policies should be put in place and enforced from the bottom to the top. This means everyone knows what the data types and formats are and where they should be saved at all times. But it is equally important that these boundaries are not too restrictive. Data is changing all the time, so standards too will need to adapt. Employees should be allowed some freedom of action as long as they stay within the goal posts.
Using the right technology
Dark data is a consequence of the rapid adoption of new technologies and business models, and the abandonment of the old. So, it is only fitting that new technology should be the key to solving our dark data challenges. A single, unified data management solution can use intelligent automation to help employees locate data far more quickly than before and better understand what data they have at a glance. This has multiple benefits: less data goes dark, efficiency increases, and protection is enhanced. In addition, the organisation gets a superior overview of its data, which it can use to make better decisions faster – giving it a strategic edge.
While dark data might only seem like an issue for older, established organisations burdened with legacy technology, this is not the case. Challengers may have the latest tools and lack databases of redundant historical data, but over time their data will also depreciate in value. But they have the opportunity to mitigate the dangers of dark data by starting off on the right foot, and implementing good policies through a structured, automated approach to data management. Those that truly appreciate the value and power of their data will thrive in our digital economy.
Jasmit Sagoo, senior director, Northern Europe, Veritas Technologies (opens in new tab)
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