Drowning in Data? How To Ensure Your Data Strategy Isn’t Hurting Your Brand?
Data is coming in from different channels, mobile devices, IoT devices, to the point where it is often overwhelming. With so much data being produced and accumulated every minute, brands can begin to drown in data. That said, not all data is valuable or actionable, so brands need to be able to discern which is which.
“Enterprises are not drowning in data because of its depths, they are drowning because they don’t know how to swim. Too often organizations approach their analytics blindly, sifting through mountains of data hoping to find gems,” explained George Kobakhidze, enterprise solutions atZL Tech, an information governance platform provider.
The amount of data that is produced in one day by people across the globe is staggering. According to Raconteur’s A Day In Data, on each day of 2019, 400 million tweets and 294 billion emails were sent, 4 petabytes of data were created on Facebook, and by 2025, it’s estimated that 463 exabytes of data, (463,000,000,000,000,000,000 bytes), will be created each day.
For brands that need to sift through all the data that is created through their various channels, including social media, email, websites, apps, sales inquiries, customer service tickets, surveys, and brick-and-mortar storefronts, a data strategy is required to separate good data from useless data. An effective data strategy allows brands to collect and analyze data, obtain actionable insights from the data, and store the data for future use. Often, this is where the problem lies — the lack of an adequate strategy. “The issue lies in that information is frequently stored without a strategy for future use, leaving data in the dark — unused and unknown. With upwards of 80% of enterprise data being considered dark, it is no wonder that analysts feel like they are drowning as they are unable to access relevant information, rendering the entire data collection process moot,” said Kobakhidze.
It’s also important to recognize that data has an expiration date — that is, data that was collected before the COVID-19 pandemic, for instance, is largely not useful for making actionable insights today. George Corugedo, co-founder and chief technology officer at Redpoint Global, a CDP platform provider, told CMSWire that brands need to remember that the overall principle is that data spoils. “So if you want to take the greatest advantage of the enormous volumes of available data (which everyone should try to because it is valuable) then all processes need to be performed under a ticking clock, reminding them that the data they are working on is dying a little bit every second.”
According to Walter McAdams, VP of solutions of Rhode Island-based SQA Group, a software quality assurance solution provider, brands need to structure a foundation in which their data strategy is business driven. In this way, it can provide insights and strategic guidance to the brand. The data must be trustworthy, reliable, accessible, and digestible to the software with which it will be used. “When creating a data-centric culture, you need to establish fundamental pieces: a data governance structure, clear understanding of ownership, unified data definitions, a mechanism for ensuring data quality, and methods for reporting, accessing and querying data that puts actionable information in the hands of stakeholders,” McAdams explained.
“If your foundational data structure is solid, you can’t overuse data and it reduces the possibility that you will misuse your data,” he said. “Instead, you can shift to turning data into actionable insights. Data serves as our compass: indicating what to do and where to head next.”
McAdams said that above all, brands should keep two things in mind: keep their data definitions up to date, and recognize that data quality never ends —i t goes on forever. “To get good data is essentially to get good data definitions that are endorsed by the stakeholders,” he said.
