March 1, 2023

Why you’re data-rich and insights-poor

In today’s data-driven business landscape, organizations increasingly rely on internal reporting to make informed decisions. Companies that fail to use analytics productively will fall behind. 

It’s likely you already have many data tracking and reporting tools in place at your organization. CRM systems, website analytics, marketing automation platforms, business intelligence tools, customer feedback and more all provide valuable information. But ask yourself: Does your data actually help you to make insights-driven business decisions?

Companies that prioritize data-driven decision-making are more likely to achieve their goals and see greater success. A study from Forrester found that businesses that use data to make decisions are 58% more likely to beat their revenue goals. The same study found that data-savvy businesses are also 16x more likely to significantly surpass their revenue goals when compared to their passive counterparts.

Data-savvy businesses are 16x more likely to significantly surpass their revenue goals. (Source: Forrester)

Despite the proven benefits of data, many companies struggle to effectively manage and use it to guide their decision-making. This insights-poor approach leads to ineffective targeting, misguided strategies, lost revenue opportunities—and competitive disadvantage. 

So, why is data-driven decision-making not yet a reality for most organizations? Let’s take a look at three root causes. 

Your data is inaccessible 

Inaccessible data refers to data that is difficult (or impossible) to access, use or analyze. This may be due to technical limitations, restrictions on access or sharing, lack of appropriate tools and skills, or overwhelming volumes and complexity.

Many organizations respond to the need for data by increasing the amount of it. For most, this means a focus on raw data, charts and extensive tables. But high volumes of complex data leave sales, marketing and enablement professionals feeling overwhelmed—and it creates more questions than answers. 

  • Two-thirds of CMOs (67%) say the amount of data has become overwhelming; and 33% note that the biggest external factor is the rising numbers of data-rich channels and platforms.
  • A recent study from Gartner found sales reps have the lowest data proficiency (43%) in the organization, and sales leaders list “data complexity” as the number one barrier. 

Think about the data at your organization. Do you know what types of data are available to you? How and where to access it? And, most importantly, how to interpret it? If not, data inaccessibility is holding you back from advanced insights-driven decision-making.

Your data lacks quality 

Gartner estimates that every year, poor data quality costs organizations an average of $12.9 million. Poor data quality refers to reports that are inaccurate, incomplete, inconsistent, duplicative or outdated. In other words, the data is not to be trusted. Human error, system limitations, integration issues and lack of governance can all contribute to poor data quality. 

If there’s one thing marketers and sellers agree on it’s that there’s nothing more frustrating than bad data. 

  • Poor data quality is one of the toughest challenges for marketers; 63% of respondents reported poor data quality and unclear analysis as top reasons why they don’t use analytics to inform their decisions. 
  • Nearly half of sellers (45%) say their biggest data challenge is incomplete data. 

63% of marketers say that poor data quality and unclear analysis are top reasons why analytics doesn’t inform their decisions. Source: Gartner

How much do you trust your organization’s data? How often do you find reports that are insufficient, conflicting or outdated? These are all red flags that you need to improve your data quality, or risk faulty decisions and actions. 

Your data is stuck in silos

When data is stored in separate, disconnected systems it’s difficult to share or access information across the organization. Valuable insights are stuck in isolated pockets that prevent revenue teams from building a complete and accurate view of their customers and operations, and leaves earnings unrealized.

Data silos are most often caused by multiple different software systems and a lack of standardized data structures. Nearly half (47%) of sales leaders list inconsistent definitions of metrics and key performance indicators as a roadblock to data proficiency. 

47% of sales leaders list inconsistent definitions of metrics as a roadblock. Source: Gartner

Siloed data can exist within the same department too. Integrating and making sense of this data can be challenging and unsustainable, especially for data-rich companies with a growing number of sources. 

  • For example, marketing professionals often have to work with data from multiple sources, including web analytics, social media, CRM systems, and customer feedback.
  • More than half (52%) of CMOs say they’re already using 14 data sources or more.

How many data sources do you use? Do you know what data exists outside of your department and how to access it? How do you consolidate information from multiple sources? Siloed data is why you can’t see the bigger picture and results in misguided decision-making. 

Diagnose your data dilemma 

If your data isn’t doing enough for you, investigate the cause. Whether it be inaccessible data, poor data quality, siloed data (or a combination of the three), understanding what’s making you insights-poor is the first step to fixing it. Then, you can unlock the full potential of your data to make informed decisions that drive growth for your business. 

Ready to learn more? Check out this article to discover how you can use data to support sales enablement and drive sales performance.