Opportunity Costs and Data

Direct and indirect costs are easily calculated, recorded and audited but another kind of cost is often overlooked — the cost of a lost opportunity. This is noteworthy because opportunity cost has great strategic importance for the top management — especially when the business landscape is facing big changes due to competition or technological advancements or market considerations. Opportunity cost rightfully should come under the Risk Assurance function, along with revenue assurance.

In general, opportunity cost doesn’t get reported in the financial statements and is not covered under standard revenue assurance controls and hence little attention has been paid to this topic. Opportunity cost is understood as the benefits missed out when a decision is made to invest in one activity instead of another. In other words, opportunity cost is the benefit a business could have gained, but did not, had a different decision been taken.

The telecom business landscape is dynamic and telcos have been rapidly adapting newer technologies. Telecoms is considered as a gold standard for adaptation to newer technologies and we have witnessed the evolution and rapid adaptation from 1G in 1980s to 2G, 3G, 4G and very soon we will have 5G rolled out. Each new generation of technology brings a new set of use cases that need to be supported — this includes the hardware and software as well as business models, operational policies, and new metrics. The emerging use cases for IoT and streaming mobile content will add new elements to the telecoms ecosystem.

Telco revenue assurance systems and policies have been successful in detecting revenue leakage and ensuring maximum revenue realization for services provided and consumed through data recorded and generated by operational and business systems. However, opportunity costs remain hidden and are not considered or discussed.

To get an insider view of the problem of opportunity cost, I had a few discussions with telecom operators in India, Africa and Americas. The operator’s dip in revenues from voice and SMS is not being compensated by growth in revenue from data (GPRS, 3G, 4G LTE). Also, the cost of upgrading to 4G is not as marginal as one would assume because of existing towers, fiber setup with last mile connectivity etc. Fiber for 4G is about 10 to 20 times faster than 3G, and there are specific 4G voice support requirements that must be met. Therefore, the cost of the upgrade is similar to setting up a greenfield network. 4G enables end to end IP networks and delivers broadband speeds of up to 100Mbps — with up to 20Mbps being used by a basic subscriber. Without 4G telcos cannot stay in the business, and very soon they must upgrade to 5G. Incumbent telcos are compelled to use higher operating leverage to support aging technologies like 2G/3G; despite all these upgrades to newer technologies, telcos margins and revenues are not seeing the growth they enjoyed during the 2G era. Are telcos missing out opportunities that can be monetized? Can big data analytics help telcos with this problem?

When demonstrating our telecom analytics products I am often asked how to increase revenue or growth in today’s challenging situation. Considering opportunity costs and big data analytics is a way to start addressing that question. It is interesting to see that the focus of standard revenue assurance is expanding from leakage within the revenue chain, to issues outside that chain. This shows the severity of the downward revenue trends.

We are living in an information age and it’s important to understand the business of information from social media companies to update telco business models. Social media providers such as Facebook and Twitter are effectively monetizing data, and this is an important case study for telcos to look at. Facebook is the fourth largest company in the world in terms of market capitalization. They have successfully monetized data. Without support from the telecom sector, social media businesses could not have reached this level of success. Also, telcos have subscriber data that the internet giants do not have. In fact, telecom generates more data than social media platforms. Data available with telecom is very valuable for machine learning and artificial intelligence. Operators must capture this lost opportunity in data monetization.

The revenue and margin issues that telcos face can be addressed by providing secured access to anonymized subscriber data and by provide ancillary services that complement existing services. Telcos should also join hands with their competitors and come up with a framework like interconnect or roaming agreements for data processing, aggregation and sharing.

Daniel Peter
Daniel Peter
Daniel Peter is Vice President of Analytics at Gamma Analytics. He heads Gamma’s Data Science group working with customers in advanced predictive model development, business data analytics, data science, and product strategy. He also has significant expertise working with Fortune 500 companies for Connectiva Systems and Hewlett Packard.

Daniel has a Business Analytics degree from IIM Calcutta, Masters in International Business from Kedge Business School, France, and MBA from Loyola Institute of Business Administration, India. He is the author of: “Corporate Response to Recession (2008-09)”. He speaks and writes on telecom topics and can be reached at daniel@gammanalytics.com