Data Analytics – It’s a Whole New Ball Game
It’s increasingly clear that business intelligence in the traditional sense is coming up short in the ability to drive an organization towards maximum revenue and efficiency.
The reactive nature of business intelligence practices, matched with knowledge and intuition from those who have spent decades in their industry, isn’t enough anymore.
The management of companies both big and small, should invite big data analysis into the strategy room if they haven’t yet done so, and give it an equal seat at the table, if not veto power and execution responsibilities as well. A discussion on this topic last week reminded me of the movie Moneyball, adapted from the book of the same name. It is the story of how data analytics changed the game of American baseball and the resistance it met within the establishment on the way there. The story holds easy parallels to be drawn to the telecom industry and the difficulty that many within it are having with truly embracing the new era of business analytics.
Telecom companies in developed markets are often critiqued for acting with a lack of urgency to greatly improve the ways in which they do business. One way that many of them remain stubbornly behind is on the increasing importance and complexity of customer relationship management. To address churn and retention, for example, many operators are still, like baseball insiders had been until shortly after the turn of the century, relying on dated statistics and collected wisdom that are being outperformed by newer data analytics. Quite a few operators have stepped into the ring with their big data, intending to use it to improve their business, but the majority have not yet progressed past collecting it and perhaps selling it externally or using it to advise on cost-cutting measures. Not enough operators are realizing the impact that sophisticated data analytics solutions can have and taking advantage of them.
When sabermetrics, the baseball term for data analytics, came along it was seen as a radical new way of predicting the success and performance of players. The metrics it used were actually a more accurate method of assessing value, to guide the decisions of how much a player was worth and who to pursue. In Moneyball, the general manager implemented sabermetrics in order to build a team without much of a budget. Later in that 2002 season, to the surprise of many, the team went on to win 20 consecutive games, setting an American league record, and the legacy practices of the industry slowly began to shift. It took some time, and a shake-up, before the old guard of baseball insiders collectively understood the power of sabermetrics. As in the telecommunications industry, there were new tools and information available that just couldn’t be ignored in the growing competitive landscape.
Operators that have analysts spending hours poring over spreadsheets are not able to most effectively respond in real-time to customer insights. Others, who have recognized the competitive advantage that data analytics tools can bring as well as implemented them, are simply more up-to-speed with the most effective business strategies of the big data era. Telecom companies, much more so than sports team managers, face significant challenges regarding the volume of data to be processed, the variety of such, and the real-time speed it can be handled and automated to affect decision-making and action. Those that haven’t already need to acquire and deploy the necessary tools to internally apply advanced customer care, marketing and operational best practices via the revelations of their big and dynamic data repositories. As a baseball team manager might train their scouts, so an operator should train their line managers in how to understand the output of data analytics and how to integrate it into a decision, based also on their own experience and intuition.
There are some great examples of ‘Moneyball general managers’ among communication service providers (CSPs), who are ahead of the game with data analytics. The resulting demonstrable improvements they have made in customer experience, financial performance, churn and upsell are too significant to ignore. Northstream has studied several companies to detail how these CSPs are applying data analytics and our new white paper, Analytics Beyond the Hype, reviews these case studies in detail.
When it comes to using all the data they have available to them, operators’ hesitance in applying new data analytics methods and tools in favor of the old risks leaving them behind in the continued fight to thrive in the industry. A massive manual analysis in Excel of reasons why customers churn or don’t spend more may win an occasional game, but it will certainly not take you to the championships.