What to Do When You Can’t Trust Your Business Reporting Data

Despite investing heavily in data, you might be surprised to find that most executives don’t trust their company’s data. They may be skeptical of the data they are using, or they may simply not know how to interpret the information at hand.

In fact, Havard Business Review reports that 90% of executives believe data literacy is critical to business success. However, only 25% of employees feel safe working with their company’s data.

The statistics scream loud and clear that if you have trouble trusting your business data, you are absolutely not alone. However, this doesn’t make it any less important to fix.

Untrustworthy data affects your entire company. You run the risk of:

• Pivoting strategies based on false assumptions
• There is a lack of a clear picture of business performance and ROI
• Delivering bad customer experiences
• Decreasing job satisfaction for your team due to manual tasks and frustrations
• Reluctance to share important insights across the team

Instead, the goal of every company should be data integrity. Data integrity refers to the quality and reliability of your business data, including the accuracy, consistency, timeliness, and preservation of that data.

With high data integrity, your company can also benefit from the enormous possibilities that big data brings with it.

Here’s our guide to what to do when you can’t trust your report data. Learn how you can change things over the long term so that leaky processes and frameworks don’t affect your data outputs.

This is how you can make your data more trustworthy

It may sound obvious, but if your company has been grappling with unreliable data for a while, you will have to do things differently to get a different result.

Correcting untrustworthy data requires changes to the following data in your company:

• Processes
• Way of thinking
• Skills

Let’s explore the best ways to make your data more trustworthy so you can benefit from accurate, timely analysis that paves the way for informed decisions.

1. Go back to the basics.

To make your data more trustworthy, let’s go back to the beginning. Imagine restarting your database from scratch. Now answer these questions:

• What data do you need to collect?
• In what format do you need to collect it?
• Which data do you not need?
• What clutter or noise do you want to avoid?
• How do you have to integrate your apps?

You can use these valuable insights to inform:

• New processes for data collection, management and integration
• What to clean and remove in your database
• This is how you train your team and increase data literacy in your company

Once you know what needs to happen, create a plan of action to implement it and make your data more trustworthy.

2. Follow the data path back to the source.

When faced with unreliable data, follow the path back to the source. Where did the inaccurate data come from?

This includes looking at form fields and checking for consistent and standardized data collection. It also means making sure that the Google Analytics tags are set up correctly or that your SQL scripts for your business intelligence platform are free of errors.

If this adds to your technical knowledge, perhaps because the person who implemented your systems has left the company, consider getting a data specialist to help. You could also get their help in simplifying your data processes so that they can be better managed internally in the future.

3. Check the boxes for data best practices

Regardless of the industry or company size, there are some best practices that every company should follow for trusted data. These include:

• consistency – Maintain the same format across systems by using uniform and standardized fields and data entry processes. When integrating your apps, use customizable field mappings to ensure the right data is synced in the right places.

• completeness – For each data element, you need to know the big picture. Some examples are the source of your marketing leads, the sales history of your customers, or the conversion path for new deals. Are your data complete?

• Centralized and enriched data – Instead of spreading fragmented and incomplete data across multiple systems, you maintain a central database with the most up-to-date and trustworthy information. This can be your CRM for your customer data and a system like Chartio or Supermetrics for your company performance data. Create bidirectional integrations between your centralized database and connected apps to enrich your data anywhere.

• Access control – Set permissions and policies to ensure that only the right people see certain data. The point here is to reconcile accessibility and transparency with security.

• Validation – According to Experian, 28% of customer and prospect data is suspected to be inaccurate in some way. To get accurate data, you need a method of checking and validating it. This may include automated processes to check for anomalies and missing fields, supported by some manual checks.

• Real-time updates – To get the best results from your data, it must be up to date. When choosing a business intelligence system and data integration solution, look for real-time updates.

• Quality sources – Make sure you know where all your data comes from and that you can guarantee its integrity. Maintaining a clean and tidy database that you know you can trust beats with sophisticated data sets that are difficult to understand or control.

• cleanliness – Given that B2B data expires at a rate of 2% per year, your database needs to be cleaned up frequently. It’s important to refresh your data by removing duplicates, inaccuracies, and other data that has been turned from value to clutter.

• Security and Protection – Maintaining a high level of security is vital for data protection regulations like GDPR in Europe, but it’s just a basic principle to be a trustworthy brand. It’s also absolutely crucial if you want valuable data to hand (and only yours).

• Integrations – Over 80% of business leaders say data integrations are important to day-to-day operations in their company. Data integrations reduce data silos and make data more accessible to everyone in your company so that employees don’t have to search for other colleagues to find specific information stored in their department’s database.

4. Document processes.

A common trap companies fall into is relying on someone to set up and manage their data processes. Often times, when that person leaves the organization, chaos is unleashed.

You can avoid this by creating clearly documented processes that are stored in your company wiki, Google Drive, or a tool like Notion. And remember: processes that are too complicated can do you more harm than good. The simpler your processes, the better.

5. Simplify everything.

Complexity is often at the root of bad data that you cannot trust. For complex data analytics to work successfully, you need the time, resources, and knowledge to back it up.

For most businesses, keeping your data and reporting as simple as possible is more effective.

Simplifying your data means:

• Collect only the data you need
• Organize data consistently and in standardized formats
• Avoidance of complicated work processes and systems
• Reduce your reporting dashboards
• Avoiding multiple systems for the same job
• Create clear and easy-to-understand documentation
• Change processes so that everyone can understand them quickly

To make your data so trustworthy, ask yourself: Where can you simplify your data collection, management and integration processes?

6. Keep the sunk cost fallacy in mind.

You have invested a lot of money, have complex systems in use … and you don’t want to throw that away. So instead of starting over, you build on what you have – and hope that it covers up what lies underneath.

Investopedia describes the sunk cost fallacy or sunk cost trap as “A tendency for people to irrationally engage in an activity that does not meet their expectations. This is due to the time and / or money they have already invested.”

This is all too common when it comes to business data and analysis.

If you keep building on shaky foundations, it will bite you again. Start by understanding exactly what you are dealing with and what are the problems. If necessary, bring a second opinion here. Then make the most unbiased decision possible about what to do to improve data integrity.

In the long run, it may be easiest to go back to the drawing board, come up with a much simpler and more accurate strategy, and ditch what you had before.

7. Communicate with stakeholders.

Concerns about untrustworthy data are often legitimate, but sometimes you or your company’s stakeholders are quiet Don’t trust your data if everything is fine.

If so, clear communication is your way forward. Explain why your business analytics data can be trusted and how it is set up to ensure reliability. Answer questions to help stakeholders understand how data is collected, managed, and integrated between your apps. Also, encourage raising concerns so that you can explore their validity or insignificance together.