Everyone loves the Big Data promise: creating hyper-efficient means of tackling some of businesses toughest problems. The ability to focus on real time, fact-based decisions over simple assumptions has fueled the growth of new big data tools and platforms.
These recent technological advancements now allow us to ingest and synthesize the often overwhelming amount of data. Businesses that use data correctly are given a clear advantage with unprecedented insight into their customers and total addressable market.
Yet, sadly, the majority are torching dollars because of their data.
The reasoning is that along with the potential for optimal efficiency is the reality that the majority of data is still inaccurate. A recent study by IBM estimated that $3.1 Trillion of America's GDP is lost due to bad data and 1 in 3 business leaders don't trust their own data.
Companies often invest in data without really validating its accuracy. This causes the compounding problem of sales and marketing chasing the wrong customers, finance missing forecasts, and data scientists spending 60% of their time cleaning and organizing data.
To add insult, 76% of data scientists view data preparation as the least enjoyable part of their work. Clearly, this is not a scalable path to success.
It seems easier for many companies to accept false predictions rather than to admit that the source of their conclusions could be wrong. It is important to remember that your math is only as good as the data that supports it. The simple fact remains: If you put garbage in, then you will get garbage out.
For many, the term big data has become more of a buzzword than a technology. Marketers specifically jumped onto the big data bandwagon praising the efficiency of a programmatic and predictive strategy. Focusing on the numbers rather than the customers and the art of storytelling.
One of the biggest marketing culprits for using bad data is Account Based Marketing (ABM). ABM is one of the hottest trends with over 60% of companies planning to invest in ABM in the future.
ABM is the opposite of "spray and pray" and focuses on marketing to the right accounts in a scalable manner. It makes sense that spending money on targeting the right leads would be most efficient, unless your definition of "right" is, in fact, wrong.
In my career, I found this slope incredibly slippery. The beauty of tactics like ABM are quickly erased when the data fueling the strategy is invalid. Relying more and more on the data, yet we were rarely questioning the source. Focusing on only superficial metrics of success and therefore simultaneously and unknowingly voiding our own efforts. The shift I am now starting to see is a move towards aligning Account Based Marketing efforts with verified data that powers it, called Account Based Intelligence.
Data is thought to be the answer to numerous problems, yet trusting anything that has a tendency to be inaccurate leads us to flush money down the drain.
In business, we need to prioritize not only funding for quality data and a single source of truth, but also investing in the right tools to manage that data. Creating a culture that is honest about our data's accuracy and its limitations is essential for success.