Data, Jill's Thoughts

The Problem With Data

Data has quickly become one of the biggest buzzwords in business. While most (probably all) of us still engage in intuition-based decision making from time to time, the digital age has ushered in an intense focus on data-driven decision-making. There is more data generated now than ever before, more tracking mechanisms for commerce and e-commerce than ever before, and better tools to visualize and interpret data than ever before. Despite all of this, many companies still fail in their efforts to use data to drive business decisions. Why?

Bad Data

One of the biggest issues companies today face is the integrity of their data. Because we can generate so much data from so many sources, it’s sometimes hard to know what data we can trust and what data was collected through biased means. This is especially true when two data sets from different sources present contradicting information. This often discredits the info for the company leading them to place trust in other decision-making methods that lack the substance data-driven decision-making provides. 

Here are some critical steps to improving your data integrity:

  1. Data Cleansing – Just like any asset, data needs to be cleaned and maintained to ensure accuracy, relevancy, and integrity. It is estimated that neglecting data cleansing costs businesses 12-20% of their marketing budget annually. For more information on cleaning and maintaining your data, visit here.
  2. Single Source for Data Insights – You likely have data from your analytics platform, your CRM, your ERP, social media platforms, email campaigns, Excel spreadsheets, and more. The information from these data sources is likely compiled by different departments into different spreadsheets. As a result, asking two different departments the same question will likely lead to two different answers. Even more inconvenient is that often the same person will be unable to produce the same number twice! To simplify your data use, establishing and maintaining a single-sourced data warehouse is critical. You can decide as a company the best formulas and calculations for a unified database, so all departments act with the same information and insights in unison.
  3. Data Ownership – You may have bad data if no one in your organization owns the data being produced. Without specific and documented data set ownership, data often becomes neglected integrity is lost. Make assignments to particular employees and give them the proper training to ensure data sets are trustworthy and accurate. 
  4. Automation – To err is human. No matter how careful you are, eventually everyone makes a mistake. Manually entering and managing data leads to a higher risk of bad data. By using automation in data entry and analytics, data integrity improves. 

The HiPPO Effect

When a company is unable to produce valuable insights to drive decisions, bad data removes confidence from data sets, or when the data needed does not exist, the HiPPO effect takes over. What is the HiPPO effect? Simple. The HiPPO is the Highest Paid Person’s Opinion. When data can’t be used in decision making for whatever reason, the opinion of the highest paid person in the room typically trumps all others, right or wrong. In comparison to accurate data-driven decision making, the HiPPO method results in lower ROI, revenue, and results over time. 


A lack of data or a lack of confidence in existing data sets typically results in intuition-based decision making. While some of the great entrepreneurs have made their careers on their keen intuition, the odds are not on your side if you fail to implement data-driven decision making into your business. For help improving your data integrity, send my team an email at or call us at 1-800-434-1851.

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