How To Create A Data-Driven Workplace
By Rick Delgado, contributing writer
With the potential offered by the use of Big Data analytics, it only stands to reason organizations will want to utilize Big Data more and more within the workplace. Big Data can not only help a business be more successful with customers, it can improve what happens internally as well.
The benefits to creating a data-driven workplace are many, from being more effective as a leader to improving overall productivity. Employees also come away with a better understanding of what value data brings to the company as a whole. It also helps organizations stay on top of their progress, providing more accurate measurements for desired outcomes. While the benefits are clear, getting to the point where a workplace can be considered data-driven is difficult, especially for those new to the Big Data game. That makes learning how to achieve that goal all the more important.
Big Data can be complex, especially for those who have little experience with it. While the aim of making an entire business data-driven is an admirable one, it’s important for organizations not to bite off more than they can chew. In the case of Big Data analytics, it’s best to start small, learning through tiny steps before implementing an even bigger strategy. Starting with a simplified approach may mean concentrating more on a single metric, measuring how you’re doing with it every step of the way. A company may perhaps adopt a data-driven culture for a specific department or team. Learning the lessons from this type of experimentation can help tremendously in adopting it for the whole company.
Of course, creating a data-driven workplace is almost impossible if employees don’t have the data they need. An organization should take care in every step of the data analysis process, from the collection of data to the implementation of insights discovered. Learning about these steps and knowing the best ways to perform them is essential. For example, in the data collection phase, businesses will need to learn what data is the most valuable to focus on while also knowing which data can be ignored (it’s certainly possible to have too much data). Enterprises also need to know how they’re going to store all that data. They may choose to go with a cloud solution or software defined storage, but however they choose to tackle the challenge, they’ll need to be able to handle a lot of information.
Employees at a data-driven workplace should also know how best to access data. A company could collect as much data as they’re capable of, but if an employee can’t get the required data to do their jobs the best, they’ll be left floundering. At the same time, that doesn’t mean every employee should be able to access every single piece of data. For that reason, businesses should be open about what data access restrictions they have in place. They also need to have a simple to follow process for getting any required information an employee might not have access to at first.
Many people may ask what Big Data can be used to measure to make a workplace more data-driven. The answer is quite simple: as much as possible. If it can be quantified, it should be measured and analyzed. If it can’t be quantified, then the focus should be placed on qualitative measures. If everything is being recorded and analyzed, insights will be more helpful. This is, of course, a tall order for many organizations, which is why data analysis should begin through simple steps, but the goal should be for businesses to progress to the point where every task, operation, and milestone can be measured with the data they collect. When this is achieved, a workplace will be using Big Data for all that they do, making them a truly data-driven workplace.
While it almost goes without saying, none of this is possible if a business doesn’t have the right people in place to make use of the data. That requires hiring people who not only know about data analysis but how to apply it to their specific industry. Without this skill, it can be reasonably assumed that much of the data will go to waste and insights will be missed. To be more effective at being data-driven, having data experts on board is pretty much an essential element.