Identifying who owns this data and how it should be processed, stored and accessed according to the organization’s business requirements and to legislation such as GDPR is fundamental to data governance. Enterprises are struggling to achieve this and are abandoning their data as a result.
Over the past twelve months, we have all been churning out data, which has sent data volumes stratospheric. However, it might surprise you to learn that less than 2% of this new data was saved and retained to use in 2021.
What happened to the other 98% of data created? According to analyst firm IDC, it was typically used for instant consumption or temporarily cached and overwritten with newer data.
The data mountain is getting bigger
The analyst firm forecasts the amount of digital data produced over the next five years will be greater than twice the amount of data created since the advent of digital storage. This is a mind-bending statistic.
IDC has identified three key reasons we should store far more of the data we create: firstly, as a catalyst for innovation and new revenue streams, and secondly, to monitor the pulse of an enterprise’s staff, partners and customers. For example, data insight helps to maintain trust and empathy that underscores customer satisfaction and loyalty. Finally, we should store more data for digital resilience, both to restore business operations following disruption and to capitalize on changing business situations.
Getting to grips with data
Managing business-critical data is crucial to success. Enterprises need to use data for smart decision making and gaining a competitive edge. If they can’t efficiently manage their data, it doesn’t matter how much information they have stored, they will struggle to create value from it.
Although there may be many likely use cases for data, they must deliver on business value and be achievable for the data team. An effective governance strategy is paramount throughout the data analytics effort to ensure data is usable, accessible and secure. This will help ensure that data is consistent and meets necessary policies and standards. In fact, effective data governance is a prerequisite of data analytics, ensuring data is clean, well-organized and trusted.
Don’t become a data hoarder
When you are advised to keep more data, the temptation is to hoard absolutely everything, regardless of understanding it or knowing where it will be helpful. This, as our digital data report points out, can lead to significant issues for data teams swamped by purposeless, inaccurate, or even data that falls foul of regulations, such as GDPR. It can also make compliance and security much more complicated and resource hungry.
The difference between companies with robust data governance and those without is plain to see. McKinsey has found that the gap between the leaders and laggards in data is growing. It notes that high-performing organizations are three times more likely than others to say their data and analytics projects have contributed at least 20% to earnings before interest and taxes (EBIT) over the past few years.
How are they doing it? McKinsey found that high performers have leaders that put data and analytics strategies at the center of business plans for the long haul. They are integrating data into employees’ workflows and establishing a clear vision for a data-centric culture.
Data-centric in practice
Progressive-thinking construction firm McConnell Dowell, for example, wanted to digitize the process to enable construction sites to better manage construction schedules and objectives. The company’s goal was to create a way of collecting and reporting real-time data to support informed, iterative, collaborative and transparent, agile decision making. This would have the potential to accelerate construction schedules.
Following extensive innovation briefings with McConnell Dowell, Orange created a flexible, scalable IoT platform designed to collect, report and virtualize data sent across a private network. This digital approach erases paper-centric processes from project management reporting.
At the other end of the solution spectrum, Intis, an engineering and automation company headquartered in Croatia, is utilizing an IoT platform and devices to send alerts when its connected vending machines need re-stocking, to carry out dynamic pricing and to flag predictive maintenance via a central management portal. These devices, combined with a comprehensive, cutting-edge software solution, also provide cash and cashless payments and smart routing to ensure drivers take the most economic route when refilling machines and only visit machines that need to be visited.
Data management is vital to data-centric
Businesses must become data-centric if they are to survive and thrive moving forward. Successful digital transformation is dependent on how well enterprises can collect, store and manage their data. The big challenge is in deciding what data to keep, and this is where a well-thought-out data governance approach comes in.
Yes, enterprises will inevitably end up keeping more data from which to draw value. But it is imperative they have a quality data retention process to harvest what is valuable and jettison the sub-standard and inferior.
Contact Orange to find out how we can help you become more data-centric. If you want to read more, download our whitepaper to find out how to build a data strategy and unlock new and eclectic use cases across business, customer and IT operations.
Axel Hinze is Managing Director of Germany. He has a wealth of experience in the ICT industry and a strong focus on collaboration and co-innovation with large multinational customers. In his free time, Axel enjoys time with his family and friends, cycling, skiing and listening to classical music.