‘Data is the new oil.‘

It’s been said so many times that it is now a cliché, but unlike oil, data is not a diminishing resource. In fact, total data volume has been growing exponentially for years, increasing from an estimated 2 Zettabytes in 2010 and to a staggering 181 Zettabytes by 2025.

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Telcos at the heart of the data explosion

The evolution of telecom networks from 2G to 4G has had a significant role to play in this data explosion. With the introduction of 4G, cellular and wireless networks became the dominant medium of buying, selling, browsing, streaming and socializing, creating rich consumption patterns and generating countless transactions and data points.

The global coronavirus pandemic has accelerated the adoption of these digital behaviors, bending the data growth curve even further—a trend which will undoubtedly continue as the global rollout of 5G increases bandwidth and throughput exponentially.

The convergence of these two megatrends is disrupting industries and creating new business models, use cases, applications and revenue streams in real time. Most importantly, telcos— especially CSPs—will be at the very heart of the digital revolution, as massive volumes of network and operational data courses through their infrastructure.

Five barriers Telcos face to true data optimization

But several barriers are stopping most telcos from extracting the maximum value from this data they’re capturing. These include:

  1. Data Redundancy and Segmentation: Having access to volumes of data is not enough. It needs to be in the right form to generate insights. Volumes of redundant data lying in multiple heterogenous systems and formats do not help analytics or machine learning.
  2. Lack of system integration: Many Telcos lack the tight integration needed to ensure a frictionless flow of data across the enterprise, creating data islands and silos. For example, network performance may not be able to fully leverage other operations data from OSS, business processes data from BSS, APIs, databases and the like.
  3. Legacy Data Stack: Though many Telcos have operated for years relying on-prem legacy Data Warehouses, they are often riddled with heavy technical debt built up over the years, acting as a bottleneck and preventing the flow of high volumes of data at high velocity.
  4. Lack of right partner or right inhouse skills: Extract meaningful insights from vast volumes of data is a complex and specialized job. Telcos excel at their core business processes but data analytics is a fairly recent and fast-moving area of expertise that can be difficult to staff easily or well.
  5. Regulations: One of the most significant recent roadblocks has been the proliferation of data privacy and protection laws around the world, which adds an additional layer of complexity related to understanding what data can be stored and monetized while still remaining in full compliance.
Five ways to clear the data optimization barriers

While the challenges are daunting, Telcos can overcome them by following these five steps:

  1. Begin with the right data strategy: Telcos need a carefully crafted enterprise data strategy designed around enterprise business needs and goals. Clearly defined policies, guidelines and data governance is the first step towards success. A coherent data strategy also helps with regulatory compliance, ensuring the use of data aligns with changing local and regional privacy regulations. A partner with data in their DNA can use their experience and best practices to help you accelerate this process and produce a more robust result.
  2. Unify all data with a focus on quality: Once you have a solid data strategy and have identified what data is useful for your business goals, the next step is to have proper enterprise data warehousing management. Heterogenous data needs to be unified, de-duped and cleansed before it is able to generate insights or run any Machine Learning algorithms.

    If you have a legacy data warehouse, it likely needs to be modernized to extract the full benefits of a cloud native architecture. The quality of data at this stage will determine how accurate your analytics are at later stages.

    If you’re considering a partner, make sure they able to not only build the data pipelines but also ensure the highest quality data, including building ongoing data quality checks into your automated CI/CD framework. Like oil, data is only useful when it’s refined.

  1. Handle your Big Data right: The massive amounts of data coming in the 5G world will require enormous storage and management capabilities. The right partner can help build a cloud-based data lake that streamlines structured and unstructured data ingestion, enabling the creation of actionable data visualizations and fueling the machine learning engine.
  2. Create an effective Master Data Management (MDM) system: As data explodes in size and diversity, it becomes a challenge to connect and make sense of many data points. Petabytes of data can be meaningfully mined only if Telcos build MDM systems for their customers, products, services and more.

    MDM systems will rise to a whole new level of importance in the big data and machine learning world, since they can create a 360-degree customer view while keeping track of the expanding portfolio of products and services modern Telcos offer.
  1. Analytics, AI and ML: If a Telco follows all the steps above, they’ll be in a position to generate insights and drive ROI from their data-related investments. This includes standard descriptive analytics delivered through dashboards and reports—which look backward—but they’ll be able to take advantage of forward-looking predictive and prescriptive analytics as well.

    Here again, unlocking the full potential of a Telco’s data analytics investment requires a partner with a history of exctacting insighs and value from all types of data forms and analytics needs, with a track record of success to prove it.

Five Telco data optimization success use cases

Telcos who are positioned to take full advantage of their data optimization investments can gain a durable competitive advantage over their competition in any number of ways, including:

  1. Analyzing changing customer behavior patterns to proactively create new products and services, delivering optimum product-market fit. This opens up the opportunity to deliver a superior customer experience along with identifying new paths to profitable growth.
  2. Using hypercustomerization to deliver unique, individualized experience for every customer, including product suggestions, communication preferences or special services and offers. This differentiated experience cultivates loyal users and created higher cross-selling and up-selling opportunities, resulting in higher ARPU.
  3. Predicting customer dissatisfaction before customers take any action, preventing customer churn.
  4. Improving 5G reliability and service assurance, using AI/ML algorithms to sift through huge volumes of network events and operations data flowing out of OSS to identify network performance issues, predict outages and create preventive maintenance plans with the help of growing IoT-based solutions.

    Finding these bottlenecks and process inefficiencies can drive more automation, increasing efficiency and reducing Opex, as demonstrated in this case study.

  5. Improving the maturity, fluency and accuracy of AI chatbots deployed across the enterprise. With more customer interaction data to work with and improving algorithms, AI-infused chatbots can create customer delight by reducing the wait times and solving many mundane problems without human intervention. In the event a human agent must be called upon, the system can summarize the issues for the agent without the customer having to reiterate everything.

The benefits of data optimization intiaitives in telecommunications are incredibly compelling, given telco’s place at the heart of the digital world today. But as data volume, velocity and variety grow, build and maintain  data management and analytics solutions will only increase in complexity. An experienced partner with a decades-long legacy of handling data operations for large enterprises can help simplify the process.

At Persistent, we deliver solutions that drive agility and responsiveness by helping Telco organizations develop new products faster, manage costs in business operations and derive insights from performance data. Learn more about Persistent’s services focused on Telecom and Media for companies struggling to redefine the customer experience, capitalize on digital convergence and launch new business models.