Data Visualization

Breaking the Reactive Cycle

Image showing a person looking at graphs while working

In a recent blog, we wrote about the value of big data and that it should be treated as currency. Organizations that understand the value of their data have two things in common:

  1. They know their data is complex and must pull out the most valuable pieces to their stakeholders, employees, and customers and present it.
  2. They know that the hours required by resources to manually handle such a task especially when there is a real-time demand is wasted time and diminishes the value of the data.

Many of these organizations have invested in data visualization dashboards and tools to pull real-time data that is accessible by stakeholders at any time, any place. This investment pays off and adds value to the data while keeping their resources focused on profitable tasks.

Unfortunately, there are still too many organizations that still use their resources, such as data analysts, to build dashboards and reports in PowerPoint. These organizations may see the benefits of a customized real-time dashboard and they have the budget to invest, but slowly that budget diminishes as they continue to use resources to meet immediate demands, such as building manual reports. Why is that? Why do organizations continue in this spiral that starts with good intentions to invest in a better solution but ends up doing the same thing over and over. Isn’t that the definition of insanity – doing the same thing over and over again and expecting different results?

Why is that?

We believe organizations that operate in a reactive vs. proactive mode finds themselves in this predicament more often than not. A reactive company makes spur of the moment decisions based on an immediate demand instead of allowing the time to look at the big picture and what needs to be done to get there in the long run. They end up only seeing tomorrow, quickly reacting to that demand and using resources ineffectively to deliver. In the case of providing data to their stakeholders, managers pull whichever resource is available off of billable work to prepare a report. This process often involves finding and sifting through the data, manually building charts to make some kind of point, then piece those charts and points together in a PowerPoint, and answer endless questions. The end result is time wasted, inconsistent outputs, and a higher risk for data error.

The proactive organization sees the big picture and does not make hasty decisions. They understand that investing all their time and resources into the immediate issue will only shelve the long-term solution and prolong the immediate issue. They understand that reaching a more efficient and profitable solution to visualize their big data involves planning and strategy. Once the data visualization solution is implemented, the data becomes much more valuable because it is more accurate and customizable.

So, how long does it take to build a data visualization solution?

At Boost Labs, we do not cookie-cutter anything, so the time for strategy and implementation varies based on your data and goals. We help you determine the best type of data visualization to effectively present your data. With that in mind, we anticipate up to 3 months to customize a data visualization dashboard for you. We help you lay out the plan and strategy so that you can share it with your stakeholders, which helps keep them focused on what is ahead vs the immediate. If you are operating in a reactive mode, let’s talk and see what we can do to break that reactive cycle.

Let’s break the reactive cycle by starting a conversation today!

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