Big Data

Data-Driven Organizations: A collaborative approach to the business model of our era

Data-Driven Organizations

As organizations and businesses look to outsmart their competitors and enable better results, they need to look no further than to their data. Proper data management goes far beyond simple analytics used to create informed decisions. Instead, data-centric organizations can take this value a step further, using data to drive actual processes and make changes that improve people’s experiences on a daily basis. 

From modern companies to more storied institutions, data-centric architectures are already at the heart of much of our daily lives and simple pleasures. 

Consider UPS. Twenty years ago, mail operations were simply a delivery service, but now, each package that arrives at one’s doorstep is the product of a powerful, automated data-driven operation. From scheduling drivers to route optimization and prioritizing which packages are the highest priority, nearly all of UPS’s operations rely on data. 

The same is true for more modern companies that have become a deeply embedded part of day-to-day life. Netflix, for example, is heavily reliant on metadata that tags and classifies every television show, documentary and movie to then correlate those items to what the system knows specific users will enjoy. 

These companies understand that data is an enterprise asset, and business operations looking to maintain a competitive edge must acknowledge that a data-driven architecture is the business model of our era. 

What does a data-driven culture look like? 

At the forefront of any data-centric company is the idea that functions are temporal and data is permanent. As such, functions should be brought to the data, rather than the other way around. 

Most companies have already begun to make their operations more data-centric. In order to do so, they’ve recognized the institutional value of collaboration, meaning data cannot be isolated nor can it be used on an as-needed basis. 

This concept is enabled by collaborative databases, or a consolidated platform that applications can read and write into with built-in security functions as well as the ability to run analytic processes. This essentially means that data can be used for a variety of functions at a massive scale without ever needing to be copied. 

This both enables secure consumption of information from internal and external sources while also simplifying the data sharing process and eliminating silos created from past function-first operations.

Data-centric organizations acknowledge that employees of a given company should have free access to data across departments, within legal and privacy constraints, instead of needing to make copy after copy of different datasets to manipulate it to their liking, an error-prone practice that has proven to be a hurdle on the path to becoming data-driven. 

Resistance to a business transformation 

These prolific copies of datasets and a need for control are often what stands in the way of this utopian, collaborative data-driven management style. 

While a data-centric organization should aim to maintain one “golden” record of data, doing so often requires a cultural reboot, especially for more mature companies weighed down by their historical, outdated management techniques. 

For years, companies and individuals have copied datasets so that they maintain autonomy over their use of it. As a result, chief data officers, who have long preached ownership for a given dataset, have struggled to introduce this new, collaborative counter culture. 

But professionals within an enterprise must share their data unless there is a valid and meaningful reason to restrict access. Certain divisions can certainly own portions of datasets, but ultimately, that data should be governed in a cohesive manner that is accessible to other departments. 

Consider this from a national security standpoint. The U.S. Department of Defense reaps no benefit from one department hoarding and protecting its data from another. This data is certainly confidential and private, but the overall institution can recognize the need to share it across departments in order to remain competitive on an international level. This type of collaboration is imperative and cannot be understated. 

Why be data-driven? 

The next generation of modern data-driven management veers away from control and ownership – a change that is almost sacrilege from some data professionals – and instead enables stewardship and access to one master record. Data-centric organizations treat data as the primary asset of a given enterprise and main driver for company growth. 

While new tech-savvy companies and longstanding institutions have clearly acknowledged the value of a data driven model, why should more organizations take this approach? The answer is simple: competitive advantage. 

From life-changing matters of national security to daily mail deliveries and streaming preferences, machine learning algorithms are always improved with more data.

Collaboration and reliance on business and technology processes centered on data will certainly be a default business strategy for organizations that desire to maintain their competitive edge.

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