Reporting In Companies: 7 Keys to Implement It Successfully


Despite huge investments in data, most executives don’t trust their data. According to a KPMG and Forrester Consulting survey To more than 2,000 data and analytics decision-makers, only 38% of them have a high level of confidence in their customer information and only a third trust the analytics they generate from their business operations.

That is why it is important to have accurate data that nourishes the reporting of your company, since the objective of any company must be the integrity of the data, which refers to the quality and reliability of your business data, including how accurate, consistent, timely and well preserved that data is.

With high data integrity, your business can also benefit from the increased opportunities that big data provides.

So why is reporting so important to business?

Why it is important to have a reliable reporting process

Untrustworthy data has an impact on the entire organization – Marketing and sales lose up to 550 hours and $ 32,000 per agent when using low-quality data. Therefore, if you are going to have data as the axis of actions in your company, they will have to be of quality, accurate and efficient.

Having a reliable reporting process is essential because this way you will have a broader panorama of the direction of your company, you will be able to better integrate the areas and you will create solid bases for decision making.

If you have a reliable reporting process, your company will have advantages such as:

  • Manage appropriately reports and dashboards
  • Have more focused strategies with better results
  • Have a clear and real vision of the performance of your company and the return on investment
  • Provide better customer experiences
  • Increase your team’s job satisfaction
  • Share important information with the whole team

To have reliable data you need to optimize organizational processes, approaches and skills.

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

In this article you can read some key tips to have a reliable reporting of your business.

1. Go back to basics

To make your data more reliable, let’s go back to the beginning. Imagine that you are starting your database completely from scratch with a clean slate. Now answer these questions:

  • What data do you need to collect?
  • In what format do you need to collect them?
  • What data do you not need?
  • What is the clutter or noise that you would like to avoid?
  • How do you need to integrate your applications?

You can use these valuable approaches:

  • Implement new data collection, management and integration processes
  • Know what to clean and prune from your database
  • Identify how to educate your team and increase data literacy in your organization

Once you are clear on what needs to happen, start creating an action plan to implement it and make your data more reliable.

2. Follow the data trail to its source

Whenever you are faced with unreliable data it is advisable to trace it back to the source. Where did the inaccurate data originate?

This includes analyzing your forms and verifying that the data collection is consistent and standardized. It also means making sure your Google Analytics tags are set up correctly or that your SQL scripts for your business intelligence platform are flawless.

If you require a higher level of technological knowledge, perhaps because the person who implemented your systems has left the company, consider hiring a data specialist to help you. You can also enlist their support to simplify your data processes, with the goal of making them more internally manageable in the future.

3. Generate good data practices

Regardless of the industry or the size of the company, there are some best practices that every organization should follow to obtain reliable data. These include:

  • Coherence– You must maintain the same format across all systems by using uniform and standardized collection processes and fields. When integrating apps, do custom settings to make sure the right data is synced in the right places.
  • Integrity: for each piece of data, you need a complete overview. Some examples are the source of your marketing leads, the sales history of your customers, or the conversion path for new offers. Is your data complete?
  • Centralized and enriched dataInstead of having fragmented and incomplete data spread across multiple systems, maintain a centralized database with the most up-to-date and reliable information. This can be your CRM for your customers’ data and a system like HubSpot Analytics for your company’s performance data. Create two-way integrations between your centralized database and connected applications to enrich your data everywhere.
  • Access control– Set permissions and policies that ensure that only the right people see certain data. It’s about balancing accessibility and transparency with security.
  • Validation– 28% of customer and prospect data is suspected to be inaccurate in some way, according to Experian. To get accurate data, you need a method to verify and validate it. This can include automated processes to detect 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. Look for real-time updates when choosing a business intelligence system and data integration solution.
  • Quality sources– Make sure you know where all your data comes from and that you can guarantee its integrity. Maintaining an orderly database that you know you can trust is better than having very advanced data sets that you have a hard time understanding or controlling.
  • Cleaning: if you consider that B2B data deteriorates at a rate of 70% per year, your database needs frequent cleaning. It is important to update your data by eliminating duplicates, inaccuracies and other data that have become a mess.
  • Protection and security– Maintaining high security is crucial for data protection regulations like the General Data Regulation Regulation in Europe, but it is also a basic principle to become a trusted brand. It is also absolutely decisive if you want valuable data at your fingertips.
  • Integrations: according to a study, more than 80% of business leaders Respondents agreed that problems arise because they have different internal systems and applications that do not “talk” to each other. Always seek to have integrations, that is, applications that are compatible with each other that add up instead of generating conflicts.
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4. Document your processes

A common trap organizations fall into is relying on one person to set up and manage their data processes. When that person leaves the organization, chaos often breaks out.

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

5. Simplify everything

Complexity is often the root of bad data that cannot be trusted. For complex data analytics to work properly, you need the time, resources, and knowledge to support it.

For most organizations it is more efficient to keep data and reports as simple as possible.

Simplifying your data means:

  • Collect only the data you need
  • Organize data consistently and in standardized formats
  • Avoid complicated systems and workflows
  • Shrink your reporting dashboards
  • Avoid multiple systems for the same job
  • Create clear and easy to understand documentation
  • Modify processes so anyone can quickly understand them

To make your data the most reliable, ask yourself: Where can I simplify the data collection, management and integration processes?

6. Be aware of the sunk cost fallacy

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

The sunk cost fallacy or the sunk cost trap is “a cognitive bias that consists of giving value to a relevant personal investment from the past, and clearly irrecoverable, to keep afloat a project whose expectations are very daunting.”

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This is all too common when it comes to business data and analytics. If you keep building on faulty foundations, you will come back to the same thing.

It starts with understanding exactly what you are dealing with and the problems at hand. Get a second opinion if you need one. Then, make as unbiased a decision as possible about what to do to increase data integrity.

In the long run, it might be easier to start from scratch, create a much simpler and more precise strategy, and ditch what you had before.

7. Communicate with stakeholders

While concerns about untrustworthy data are often valid, sometimes you or your organization’s stakeholders still don’t trust the data when everything is correct.

If this is the case, clear communication is the way to go. Explain why your business analytics data is reliable and how it is configured to ensure reliability. Answer questions to help stakeholders understand how data is collected, managed, and integrated between the applications you use. In addition, it encourages expressing concerns so that you can explore their validity or irrelevance together.

Jerry Gordon

About Jerry Gordon

Webmaster, nature and tech lover. Jerry manages the day-to-day operations at DigiToolsadvisor. He loves enjoying his free time, but most of all, trying new tools to master.