In the 2011 film Moneyball, Jonah Hill plays Oakland Athletics Assistant General Manager Peter Brand. He approaches General Manager Billy Beane (played by Brad Pitt) with an idea: the low-budget, low-talent Athletics can compete with the top teams in the league if they harness the power of data and apply it to player selection. To call Major League Baseball “old-school” up to that point would be an understatement. Despite initial resistance, Brand’s approach is eventually embraced, leading to the Athletics’ success. The disruptive power of data changed the game of baseball forever: today, there are entire conferences devoted to sports analytics.
There are other great examples of the power of data. On the consumer side, there’s Nest – a company that understood how something as simple as temperature control could become a technological hub for the home.
Or how about the recently announced Juicero – a $700 Wi-Fi enabled juice press that lets you know when juice expiration dates are approaching. And the list goes on: Wi-Fi enabled children’s toys, driverless cars, or the wildly popular Nike+ with its millions of connected athletes.
This connectivity also extends to our work lives and what we’re calling the ‘digital workplace’ – ironically still not paperless, but connected through the Internet of Things (IoT). The premise is simple: the amount of data, created by both human (unstructured data) and machines (structured data) has exploded. Today, all companies are data-driven companies. Organizations need to prepare for this flood of information with data governance plans.
Data is being collected from more sources than ever and decentralized between cloud and on-premise storage. There’s a lot on the line: organizations who don’t understand how to make use of their internal and external data can impede productivity, put their corporate reputation at risk, miss business opportunities, and suffer data loss and breaches.
When defining and implementing a data governance plan there are several considerations for companies, including how and what to monitor, who has access to information, where it is stored and what they can do with it.
As these things typically go, the first step is admitting you should address this problem even if complex and intimidating. It’s an interesting dilemma: the explosion of data is an issue created by technology that will only be solved by technology. And it requires companies to get smart about their content.
Industry is embracing IoT
The construction industry is a great example. This industry centers their business around the phrase “time is money.” Construction firms operate on razor thin margins and know that project delays lead to cost overruns which cut into profits for a given project.
This is also an industry that hasn’t exactly lived on the cutting edge; an industry that up until recently functioned on paper. It functioned on a lot of paper: architectural files, contracts, and change requests generated an enormous amount of physical files exacerbate by the physical silos between remote job sites and head offices.
Today, the market leaders in this industry are brilliant examples of how businesses should move with the times. They have embraced file-sharing solutions in an effort to collaborate in real-time. While some industries have been slow to embrace the cloud, the construction industry understands its promise: real-time access from anywhere and a single instance of the truth when it comes to the mission critical documents.
Construction equipment manufacturers are also embracing IoT. There are obvious technologies in play: GPS, fuel consumption and idle time tracking all add to the bottom line in terms of fuel savings. A large construction company also experimented with Google glass in an effort to look at blueprints through the glasses and work hands-free.
When the cloud collides with your data
One of the less talked about areas is what happens when all of this data hits the cloud. Whether it’s human-generated or machine-generated, it all gets stored somewhere – these days it’s likely in the cloud even if there are still a lot of legacy data on-premises. There are four key pillars in securing data that revolve around who can access it, how it’s secured, where it’s stored and how long it’s kept.
Access control is about ensuring the right group of people has access to the right information at the right time. Organizations should consider the “least privilege access” security model that grant access to the strict minimum set of users that really require it. Access control also enables organizations to flag content open to all and limit its exposure to prevent data leakage.
Encryption is at the center of conversations that have moved from the server room to the boardroom. Beyond blanket encryption of documents, consider “selective” encryption that enables extra protection through encryption for a sub-set of content (e.g. sensitive data containing personal information) to ensure privacy. This content will stay encrypted no matter how, when and with whom it is shared, and requires a different decryption key only owned by the individual owner to access.
Data residency is an important consideration for organizations. We’re in an era of the need for data sovereignty. All data, whether generated by machines or people, is subject to local regulations. Government requests for access and privacy shield regulations are forcing companies to ensure data residency within certain geographical boundaries.
Data retention is an important bookend to an overall content governance strategy, not the afterthought it’s thought to be. It’s about ensuring compliance in areas like legal hold, financial record keeping or requirements to destroy or delete documents at the conclusion of a project.
As we move more towards a truly digital economy, the amount of data being generated by machine to machine interactions and by people will continue to increase. Companies who harness the power of this data and consider how to safeguard it will thrive.
The author is the chief strategy officer at Egnyte
