November 13, 2023
5 minutes read
Information Insight

Why Data Governance Matters in Telecommunications

As the Technology, Media, and Telecommunications (TMT) industry quickly grows in the face of remote working, 5G networks, the expansion of AI, and other innovations, the data in telecommunications grows every second yet are rarely used in an optimal way to help an organization reach its goals. 

There are missed opportunities when data in telecommunications is not used to strategically make data-driven decisions—especially at the enterprise level. Accurate, easily-accessible data can help your organization reduce operational costs, increase sales, and get faster reporting to make informed decisions. 

In a survey conducted by TM Forum, when employees were asked to rate how effectively their companies use data on a scale of one to 100, only 22.5 percent gave their company a score of 70 or higher. Forty-three percent gave their company a 50 or lower. 

One of the core reasons for the low data effectiveness survey scores is a lack of Data Governance. Lack of data governance—internal rules that standardize the use, access, and management of data—undermine your ability to improve data quality and implement advanced analytics. This is why data governance matters.

Let’s say you ask your data analyst to pull reporting for your next board meeting on customer engagement. The analyst must go to three different platforms, contact several different departments, and then learn how each one of them processes their data before discerning any actionable insight. It’s a time-consuming, inefficient process that may not lead to accurate, meaningful information. Those missed customer insights can cost you real dollars and churn in the long run. 

Telecommunications industry data analysis says that telecom operators are rich in data but need more governance to analyze and capitalize on it. The volume of telecommunication data collected and managed by these TMT companies shows no signs of slowing down, indicating an increased demand for network optimization, data security, and personalized customer experience

Deploying a strategic data governance action plan is vital to the success of your telecommunications organization. In this blog, we’ll dive into why data governance matters and how data governance strategies enable telecommunications providers to use data to solve current challenges and prepare for the future. 

Data Governance in Telecommunications

Data governance, at its core, is about making decisions at the appropriate enterprise level and the internal standards or policies that keep data clean, effective, and efficient for an organization to achieve its goals. It can lead to increased trust within and outside of the organization, minimize data maintenance costs, and avoid redundancies. A company’s data governance strategy informs its data management practices. 

A successful data governance framework truly touches every part of your organization. For example, standardizing incoming customer data (where to store, analyze, and enhance it) can quickly help data analysts create forecasts, giving you better visibility into your customers and how to improve their level of satisfaction. 

There are three pillars for establishing a data governance framework: 

1. Policies and Standards 

Policies and standards enable organizations to use data in consolidated reporting and analytics platforms and ensure that data is fit for purpose in whichever capacity the organization needs it. Effective policies around company data will help efficiently structure the data, avoiding data cleanup in the future. Establish who can use it, how they can use and view it, and who manages it. 

2. Processes 

The next step is implementing those policies and standards through processes. The new processes should not only address training and promote the adoption of the new data governance strategy but create owners of each step in the adoption timeline to move everything forward. It’s important to incorporate leadership, managers, and early adopters as evangelists to spread the value of this change to the rest of the organization.

3. Roles and Responsibilities 

Designating roles early will increase the success of the data governance implementation. These leaders can be set up in committees, working groups, or any other collective that fits your company’s culture. These roles will have pre-determined responsibilities to keep everyone accountable along the way to establish the framework and help others adhere to policies, standards, and processes.

Once your approach is set, you can use it to help build consensus among leadership. Data governance programs require a cultural shift and need company-wide buy-in, especially from leadership, to be successful. Implementing a data governance strategy may also require external expertise, which will require budget approval from leadership to be able to recognize the true value of a successful data governance deployment.

If the Technology and Data Analytics teams are the only departments engaged in data governance, they will undoubtedly fall short. It’s essential to show the value of this approach clearly throughout the entire organization.

Why Data Governance Is Essential to Leveraging Big Data in Telecom

Technology is quickly evolving—from streaming services to fiber internet—everything is moving faster. Big data in telecom is vital to understanding and acting on new technologies, adapting business strategies, and how to harness it all for both you and your customers. 

With so many business opportunities, having a data governance strategy to ensure quality information for your data analysts to create real-time forecasts can positively impact your business. With clean, centralized data, you can increase visibility into your customers to create more business opportunities, increase sales, and make better informed decisions to grow your organization.

Why Data Governance Matters

Create better customer experiences. Only one-third of customers believe their telecom service provider understands them. You need reliable data to create a 360-degree profile of your customers and leverage tools like artificial intelligence to streamline their experience and anticipate their needs. By understanding them, you’re creating a customizable experience for them, increasing referrals and overall satisfaction. 

Optimize networks. Networks account for 40 percent of telecommunication providers’ capital and operational budgets. To optimize networks, you need to be able to analyze complex data sets, ranging from usage to hardware bottlenecks. Before you can begin to implement those analytics, you need to be able to centralize and standardize the data. Only then will you be able to see reliable statistics to make informed decisions with. 

Reduce operational risks and costs. Day-to-day operational data from across the business allows you to home in on inefficiencies and sources of risk. Artificial intelligence and machine learning can process that data and provide potential solutions. However, those tactics will fall short if your data is inaccurate, incomplete, or inaccessible. Better yet, you can quickly find anomalies and fraud attempts and alert security teams to stay agile in emergencies. This type of telecommunications industry data analysis  can discover up to 350 percent more fraud incidents. 

Barriers to Data Governance Maturity

While the telecommunications industry continues to make headway in addressing data governance, it’s not quite enough. Only 17 percent of telecommunication providers say they have a mature data governance program. A mature data governance program can help maintain data quality, employee compliance, and future metrics on company goals. 

The top barriers to better data governance were:

  • Data silos. Siloed data in telecommunications can quickly create problematic friction within your company. Breaking them down should not be done quickly, but by carefully reviewing all systems and learning how different departments manage them. After you have this vital information, implement a strategy to integrate each silo over a long timeline, keeping an eye for any issues. 
  • Legacy systems aren’t integrated after a merger or acquisition. Legacy systems from the new addition have been created over time with different standards than your organization. After the acquisition, not reviewing their data systems and integrating them in a timely manner can quickly create redundancies and a slower, more difficult merger between the companies. This inaction can pose security risks, compliance issues, and higher IT maintenance costs. Having a well-stewarded data catalog and other data artifacts simplify these integrations immensely.
  • Lack of internal skills. Data experts are in short supply, and many TMT companies choose to dedicate their resources to data quality and analytics projects. Unfortunately, the more data they process, the harder it is to create internal standards through a data governance strategy.
  • Lack of leadership engagement. Without leadership buy-in, it’s challenging to promote the cultural shift that data governance maturity requires. Adopting new technology strategies is always difficult when the value of the change is not clear to employees and when they see leadership not encouraging its usage. 
  • Lack of employee engagement. Due to a lack of training and leadership encouragement, employee participation in data governance is lacking. Employees, especially the early adopters, need to feel part of the strategy. It is important to understand that this is done with and for employees rather than to them. Departmental resistance can quickly lead to failed data governance strategy. 

Establish and Improve Your Data Governance Program with Kenway

Here at Kenway, we understand how vital an effective data governance program is to your company. When implemented, a program will enable you to use data to address current challenges, such as managing real-time data and meeting regulatory compliance. With that foundation set, you’ll be prepared to take on future data-centric initiatives like machine learning and artificial intelligence. 

Our telecommunications experts can fill resource gaps and help you overcome common barriers to data governance maturity. Once your data governance strategy is in place, we can improve your telecommunications industry data analysis capabilities, refine processes, and ensure successful technology implementations. 

If you’re ready to take the next step in your data governance journey, connect with one of our consultants to learn more.


What is data governance in telecom?

  • Data governance, at its core, is the internal standards or policies that keep data clean, effective, and efficient for an organization to achieve its goals and make informed decisions. A company’s data governance strategy informs its data management practices. 

How Big Data is used in telecom?

  • You can use Big Data Analytics to provide better customer experiences, implement innovations in AI and machine learning for forecasting, optimize networks, and reduce operating costs. 

What is telecom analytics?

  • Telecom analytics is an intelligent technology process that helps communication service providers (CSP)  gather data and obtain actionable insights about their customers, including their loyalty, experiences, and journey within the company. This data helps the CSP target customers for increased sales, improve risk management, and reduce churn

How data mining is used in the telecommunication industry?

  • The telecommunication industry uses data mining to obtain historical data on a particular customer and predict how they will behave in the future, e.g. if they will leave the company. They will look at past bills, subscription information, features used, customer information, and more. 

What are the types of data in telecom?

  • Telecommunications companies generate mountains of data from many sources. The network produces data about tower performance, traffic on the network, and bandwidth usage. Customer account data includes contact information, billing details, and product lists. Every device on the network creates location data, usage data, and security information. This data can be structured, unstructured, or semi-structured. 

What is the importance of data in telecommunication?

  • Beyond simply knowing who your customers are and when their bill is due, telecommunications data gives providers a window into network performance and service quality. This allows them to monitor traffic, identify congestion, and fix it to improve service. Beyond the network, telecommunication data can support legal and security requirements like fraud detection, regulatory compliance, and network security.

What are the sources of data for telecom industry?

  • Examples of telecommunications data sources are: call details, CRM systems, data usage, security logs, billing systems, network data, and device data.

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