To achieve effective digital transformation, companies need to select appropriate technology, have strong leadership, maintain a customer focus and ensure that the culture within the enterprise is sufficiently committed to achieving the digital transformation goals. In effect, the best business models focus on more customer and worker-centric approaches, seeking better ways of organizing and minimizing disruption. As our first article pointed out, identifying suitable examples is not straightforward (see: “DX success: Xylem simplified its business platform”).
Sprint, a digital transformation success story
With our second example of best digital transformation practice we turn to a telecoms provider. The company is Sprint. The Sprint Corporation is a U.S. telecommunications company providing wireless and Internet services. The company is currently the fourth-largest mobile network operator in the U.S., with 54 million customers.
While Sprint has desires to become bigger, it faces stiff competition from other major players like Verizon and AT&T. Hampered by cost pressures, Sprint decided to undergo digital transformation in order to boost competitiveness. Part of this drive is connected to a possible merger with T-Mobile.
Reinvesting in technology
Central to the digital transformation journey is a reinvestment in technology. Much of this technology will be geared towards collecting and analyzing data on customers. This data is being used to improve the customer experience.
By collecting data in a new way, the telecoms company will be able to use real-time 360-degree data on individual customers. This will enable it to personalize promotions, campaigns and service interventions along the entire customer journey.
Big gains from data analytics
In conversation with CIO, the CEO of Sprint, Scott Rice explains an additional focus in terms of data analytics, for the company’s 3 billion records that are processed each day. This is by analyzing hiccups in the services delivered and delays that occur which affect the customer experience. This type of information aids Sprint in understanding when and why a customer abandon a transaction. Before the use of automation, this task required human input which was slow and sometimes unreliable. Moreover, there were pockets of data that could not be accessed.
The new approach has enabled Sprint to redesigned the customer journey based on data. This was achieved by using Elastic Stack open-source software, which was powerful enough to plough through 50 terabytes of data, which was related to logs, databases, emails and electronic information. The data logs were linked to customer transactions, website browsing, and specific purchases.
To aid this process Sprint developed a Hadoop-based data lake (a method of storing data within a system or repository) to further analyze customer data. This was to improve the way the company recommends products to consumers.
These developments, while successful, do not represent the end of Sprint’s digital transformation path. Data review and analysis continue to remain central, and the company is working on its internal culture in terms of becoming more agile, by developing smaller, project based teams.