Choice of proper data operating model: A study in telecom industry

ABSTRACT

In the telecom sector the competition is always very high barring few occasions. Each of the service providers wants to stay top in the game and the role of data analytics is gaining more and more momentum to unearth the insights from all the data captured. The events of Covid-19 outbroken in early 2020 have turned the world completely upside down. Considering the exceptional economic & health crisis, organizations scrambled to adjust their ways of working to run their daily operations. They could no longer rely on previous assumptions about their customers, including their buying patterns e.g.;when the selling curve will go up, what are the seasonal patterns, what product mix make them buy etc. In no days, brick & mortar stores closed due to panic, e-commerce sales gradient rising, and customer center interactions exploded. Meanwhile, the new normal defines the new consumption pattern of media as more people started working from home, spending more time online and watching TV, and virtual interaction is all time high rather than contacting in person. Rapid change is obvious in this crisis period, and more than ever, organizations need to make decisions quickly that are however anchored in data. Yet, even as organizations bury themselves in data, they are getting an incomplete picture of performance and their customers and almost all the time this is data related [10]. This creates the classic dichotomy;you rely on data to make the decision and you are not sure whether data has the proper quality or not. Data is an important factor, for any strategy the leadership team of any organization is willing to take. In Telecom industry, managing data effectively and efficiently is one of the toughest challenges. Often, different functional departments and sub-functional departments create their own version of data and applications which can help their day to day activities. This kind of fit-for-application and their own set of data elements create the silos within the organization, duplicate the effort and make it nearly impossible to manage the data democratically. Different departments having different versions of the truth leads to plentiful issues including poor operational, predictive & regulatory reporting. In a big telecom organization, it is common that the same enterprise, network and product data gets replicated, processed and managed multiple times throughout the company. Transitioning a telecom organization to a truly data driven organization where data is 'managed' is not only difficult but need to overcome numerous common challenges. A successful data-operating model across the organization is the answer to that [1]. A successful data operating model helps to disrupt the technical silos existing in an organization. It builds upon the business model clearly indicates the value created out of it with a long-term goal alignment and addresses the way, data is going to be handled across the newly defined organizational processes;all the way from upstream data collection, cleansing and enrichment to the referencing and the downstream use of raw or transformed data [11]. © 2021 CEUR-WS. All rights reserved.