BDBB — Bad Data is Bad for Business
If you run a business, information is your power, one of your most valuable assets, and the key to winning deals, increasing revenue, and cutting costs. How do you expect to beat your competitors if you run your business on alternative facts? You must base your decisions on accurate data; to do that, you must know that you can trust the data.
Earlier this year, I heard of one horrifying perception: C-level executives believe that 33% of their data is inaccurate. Now, this may be true or not, but that’s a lot of mistrust.
Years ago, I worked with a client who was trying to implement a consolidated data warehouse for their firm and bring the data from five different entities into one cohesive data file that would help everyone. After six months of conversation, argument, and infighting, senior management elected not to get involved, which resulted in the project being abandoned.
I explained to them where they would save millions of dollars in the first year. However, the managers in charge of the data labels would not compromise on what each element defined and how precise it needed to be for general use. As a result, the cost of workarounds and band-aids was preferable over building a clean data file.
The C-suite must accept the blame for this problem. If you can’t trust your data, then something needs to change how your business runs. As business leaders, here are two areas that can make a difference.
Always Trust the Data
Data governance projects are designed to address the possibility of data errors. The goal is to set acceptable data quality standards and then automate processes to ensure the data reaches the proper user. Adherence to those standards must be the starting point.
While buying a tool is often seen as solving the problem, agreement among people is critical to any data governance plan. The business must buy into the data governance process so that everyone can trust the data. It can’t just be an IT project accomplished in a vacuum. Governance rules must be based on the needs of the business user.
The only way to know the data is accurate is if it has been carefully governed and the agreements between all the people who will touch it match expectations of what that data represents.
Trust Your People
Data governance and accuracy aren’t technologies. To trust the data, you must trust your people. Even if they’re not like you. Especially if they’re not like you.
The value of teams is critical when it comes to building this trust. Much research tells us what makes the best, most effective teams. Some data points to three factors that seem to contribute most strongly to the problem-solving ability of a team:
• High levels of compassion and understanding
• Equal contributions and trust of all members
• Diversity of members
When it comes to data, allow everyone on your team to contribute equally, and you will find new insights that would not have been possible if you had listened only to people who share your worldview.
Humans have a strong tendency to deny the validity of data that doesn’t fit our mental models of how the world works and to pay attention only to data that confirms our models. In psychology, this is called “confirmation bias.”
This can ultimately sabotage data’s ability to affect positive change. Surrounding yourself with people who think and see the world just like you do or override dissenting opinions that are not like yours will ensure that data has no chance of positively affecting decisions.
“Without transparency, openness, and integrity in the development of data input, data becomes noise, or it just sits there and does nothing.”
Review how the debate was engaged the next time you’re tempted to shut down a discussion on a subject and make the decision yourself. Think about how much more creative and effective teams are when each team member has a chance to contribute. Consider that there may be a better alternative that you hadn’t even thought of. Give your people a chance to surprise you. Trust that they have something helpful to bring to the table.
Takeaways: Data is only as good as the input, and nothing mechanical can improve insufficient data. When you base processes and outcomes on faulty data, those processes and outcomes are questionable. Base the decisions on how your data is collected and how everything is labeled on a collaborative effort among all parties who will use the end date. This will increase the value of your data.
Leadership Questions: How do you encourage clarity and accuracy of data in your business? Why do you tolerate a good enough attitude when entering data? How much stock do you put into your collected data to make decisions? How much could bad data cost you in profit dollars?
Keys: |Application: Leaders and Employees |Status: Stratactical |Duration: DNA Embed |Impact: High