Telecom data analytics is a game changer for telcos in the digital era
By : Flytxt
Q&A with Mario Nolla, Senior VP – Analytics and Consulting Practice, Flytxt, in VanillaPlus Magazine.
In telecom industry, there seems to be a renewed focus around analytics. As someone who has worked on both sides, how do you look at this trend?
Historically, telcos have used analytics extensively to run their businesses. However, when the environment gets challenging, objectives get harder and resources get constrained, you will always fall back on proper planning and analysis to achieve the desired goals. With telcos now exploring newer means of increasing revenues and optimising margins, analytics has gained center stage again. Though, expectations from analytics function are different now. Analytics is perceived as a game changer for telcos in the digital world. The sudden rise of ‘C-level data executives’ is evidence of how telcos are warming up to the cross-industry trends that are driving a shift in digital business.
Telcos now wish to move beyond traditional descriptive and exploratory analytics, which was mainly used for postmortem of business decisions, to advanced analytics and machine learning driven automated decision making. These new big data analytics technology platforms are improving personalisation at a transformational scale by allowing telcos to manage customer expectations in the very moment of truths.
The other expectation involves breaking down the traditional silo-based decision making. Instead of having fragmented data management and analytics, specific to different business units such as Marketing, Network and so on, big data analytics is allowing the telcos to have a single view of customers and the business. It is allowing them to bind together their operations and customer expectations tightly. Analytics has the caliber to be the nerve-center in the digital economy. This is possible through providing enterprises with consumer insights that enable them to make much more informed decisions that can generate higher incremental business value.
It is important to understand that success in this new digital world not only depends on a telco’s ability to know their customer holistically but also with reference to different contexts. This means going well beyond traditional data sources and integrating other sources such as location, devices and OTT data, as well as acquiring the ability to make sense out of customer actions in real-time. There is also an increasing regulatory pressure on data privacy and security, which again modern analytics systems should cater to.
The competitor landscape of telcos is shifting. How do you see them adapting to this new world of customer experience?
Today digital disruption has brought almost all enterprises on the same footing when it comes to customer ownership. So telcos are going to have new competitors, especially, when they move beyond their core services to offer digital lifestyle services like mobile payment, m-commerce, etc. Every service and process in digital realm demand customer-centric thinking and execution. So a deeper understanding of customer’s persona and his changing needs is a must. However, the real challenge of managing customer experience is not in the analytics part. That is relatively easier part to fix with proper analytics tools and team. The harder part of it is to be able to do all the operational changes that are necessary to bring those insights at the right time to the right person. For example, how do you make the insight available to the agent in front of the customer in the moment of truth? That is the hardest part.
Empowering the last mile brings its own set of challenges to the telcos as they won’t have much control, in the traditional sense. In many of the markets that we work, some divisions of our telco clients are contracted out to franchises, especially Sales & Distribution and Customer Care. Providing that much information and power to the channel executives and touch-point personnel is a sensitive proposition for telcos. However, many telcos are increasingly looking at shifting the focus from indirect channels to direct channels in order to have more control over the customer experience. Here again, if decision making can be automated across touch points, and channels are backed up with a deeper enterprise-wide view of the customer, telcos can nail it down without making drastic changes to their current processes. Analytics needs to be seen as an enabler for better decision making and not as a change agent for overhauling the processes.
What are the skillsets required to get analytics right? How does Flytxt support telcos in creating business value through analytics?
We did talk about how expectations from analytics function is changing for telcos. So traditional analytical tools and practices may not be enough. The focus of telcos has clearly shifted from IT-led reporting to business-led self-service analytics.
Flytxt’s mission is to liberate telcos from worrying on how to get analytics right and allow them to just focus on business strategies. We take it upon ourselves to provide the required technology, business applications and services and help them transform their underlying data asset to significant business value through advanced analytics.
Internally, we have evolved an analytics practice cutting across technology, business consulting and operations teams. There is a continuous focus around creating suitable analytical models for telecom business environment, leveraging advanced machine learning algorithms. We call this packaged analytics. The objective is reducing the time taken to create and deploy a model that can help in solving telcos’ specific business problems like churn mitigation, fraud detection, bandwidth utilization, etc. This calls for data scientists and decision scientists working together. However, you may still need some kind of fine-tuning when you deploy the model in live environment. But again, we are talking about 2 to 3 weeks kind of time frame for deploying a model in place compared to months in traditional approach.
Decision scientists leverage Flytxt’s packaged analytics models for self-serve analytics and data discovery. The evolution of Flytxt’s Big Data Analytics platform into a self-service platform for end users like decision scientists, IT operations team and data scientists offers significant benefits to these end users in terms of productivity improvements, faster decision making and optimal realization of economic value. Measurable economic value through faster and efficient decision making is the end goal of Flytxt’s analytics and consulting practice.
What are the barriers telcos face in adopting analytics capabilities?
The major challenge in adoption of analytics is the alignment of overall operational processes with the analytics objectives. Analytics gives actions and recommendations, which still needs to be executed within the window of relevance to realise desired business impact. The exponential growth in the volume, variety and complexity of data, has changed the paradigm of deriving business value from analytics. To meet the time-to-insight demands of today’s competitive business environment, telcos need to democratise analytics with self-service capabilities.
Another aspect is ensuring the quality and reliability of data. Telcos have built the traditional data warehouse in Frankensteinian approach as the business was growing organically or through mergers and acquisitions. And still data analytics teams spend a lot of time reconciling different definitions of KPIs across various analytics systems. It has to give way to a more nimble footed approach, where required data for analytics can be integrated and accessed in a short time. Thanks to the capabilities of new age analytics tools, the barriers of consumer privacy and data security seems to be no more a show-stopper now.
How do you see the analytics landscape evolving in the next few years?
What analytics delivers to the telcos is the ability to make smarter decisions faster. Its scope could extend from in the moment of truth decisions taken on customer touch points, to the strategic decisions made by the CXOs. There are two important sides to the evolutionary landscape. On one side, an increasing emphasis will be laid on the ownership of analytics function and on the other side the usage of insights from analytics will become widespread across department/functions.
As analytics is fast emerging as a core competency and competitive differentiator for telcos, its importance has risen to the executive level. CAO (Chief Analytics Officer) and CDO (Chief Data Officer) are emerging as senior business executives responsible for creating the analytics strategy to drive digital business transformation. In near future, these executives will be seen directly reporting to the CEO with an organization-wide executive authority for data and analytics, having a clear mandate to foster collaboration across departments in making smarter and faster decisions.
On the usage aspect, the analytics progression into the future will be guided by how the analytics practice is adopted by multiple teams for different objectives. The evolution of self-service analytics tools will allow people with very little knowledge of analytics to use advanced analytics and gain benefits from them. However, the need for specialists will not go away, in fact that will rise further to ensure they manage and provide the whole infrastructure and foundation for decision making across the organisation. Use cases will extend beyond telecom business to digital business and connected world, creating new business models and partnerships for telcos.
Can you elaborate on some of those analytics driven monetisation opportunities for telcos?
Telcos have predominantly focused on customer value management (CVM). It has given them measurable revenue uplift as analytics improved their ability to micro-segment the base and to personalise offers and services over touch points across customer lifecycle. We are definitely seeing use cases like contextual marketing and churn detection maturing across the markets. With new customer engagement channels emerging like social media, a set of new use cases like social network analysis and sentiment analysis are showing lot of promise. We also expect the other departments and functions to take a cue from marketing and increase their analytics focus for operational and strategic decision making. It could find applications across optimising network utilization, customer care efficiency as well as sales and distribution network.
Going forward, analytics will transcend the realm of internal business workflows to enable telcos to profitably participate in the digital economy by offering innovative digital services on their own or in partnership with other enterprises.
The economics of data monetisation is changing dramatically with new business models predicated on new data sources and external monetisation use-cases. Some use-cases involve scenarios where consumer data is analysed to extract insights that can be monetized with other verticals, such as advertisers, healthcare industry, transportation players, government and retailers.
This Q&A was originally published in Vanillaplus Magazine