Customer Story

‘Jam sessions’ democratize data-driven thinking

Telefónica’s creative decision-making culture is driving major innovation and better business

Telefonica

Telefónica

ChallengeAs the explosion of big data continues to transform business, marketers must think creatively about what they can do with data to both monetize information and add value for the consumer.
SolutionUse JMP to extract actionable insight from any given dataset – whether that be external data like weather reports or price information, or internal data like service usage patterns – to narrow the gap between data and decision across the organization.
ResultsTelefónica Germany’s Digital Command Center has adopted a transformative new system, based in JMP. Known as the JAM Sessions Methodology, it allows professionals from different sectors and backgrounds to collaborate on data insight generation.

“Jam musicians are masters of communication; every aspect of their music hinges on real-time collaboration,” says Alfredo López Navarro, Knowledge Manager at Telefónica Germany’s Digital Command Center. “A quartet is a musical metaphor for conversation; each group has its own rhythm, style and way of coming together as a whole, developing specific patterns of interaction that directly influence their music.” This metaphor is at the core of Navarro’s brainchild; what he calls the JAM Sessions Methodology. It’s a guideline for working fluidly with data that aims to promote creativity and bridge the gap between available data and organizational knowledge.

When Telefónica, one of the world’s largest multinational telecommunications providers, was recently recognized by Fortune magazine for its innovation, Navarro says, the JAM Methodology exemplified that spirit of evolution. “JAM is a fruit of that tree,” he says. “It’s capable of incorporating different levels of skills and a wide range of profiles into our data-driven decision-making culture.”

Telefónica has implemented the JAM method across a wide swath of the organization, from product development and R&D to market research and marketing. And as a JAM champion and proponent, Navarro’s remit is to explore data – and help others to do the same. “I’m very lucky!” he says. “I get to play with data; exploring it from multiple sources and shifting through all incoming data with the goal of discovering insights and turning them into competitive advantages that improve business decisions and sustain operational and financial efficiency.”

Telefonica logo

Data as a driver of growth and communication

Over the past two decades Telefónica has evolved from its foundations as a traditional telephone company, providing landlines and mobile phone services, to a fully-fledged internet giant, upon whose services millions across the world rely to navigate the interconnectivity of modern life. As the company prepares to launch mobile 5G networks, the scale of its operations has never been bigger, and equally so are its challenges.

Today being a telecommunications company is about much more than providing the physical infrastructure and devices for internet browsing, but encompasses navigation, self-driving vehicles, smart city developments and much more. As ever more of daily life comes to rely on ‘smart technology’, companies like Telefónica, which provides consumers with access to that technology, are at the forefront of the new data revolution. And Navarro’s efforts help Telefónica capitalize.

“Communication will explode, because everything is going to be connected to everything else,” he says. “In some cases, there are technical barriers as with reliable and low-latency communications which will power brand new industries and services. Sometimes, as in Internet of Things applications, the ceiling is cultural; for smart cities or smart grids to be fully incorporated into our daily lives, society must change accordingly. Cultural transformation is, by the way, one of the biggest challenges for Industry 4.0. And the JAM Methodology pays special attention to it.”

Alfredo López Navarro

“There is a magic effect in ‘touching the data’. Sometimes visualization is enough, but storytelling with data is key. JMP Graph Builder is king here.”

– Alfredo López Navarro, Knowledge Manager, Digital Command Center

JAM Sessions provide structural guidance for ‘outside the box’ thinking

For Navarro and his team, JAM Sessions are all about experimenting with data to generate insights into these new growth opportunities. “These days, as well as in the heads of the experts and professionals, knowledge comes in the form of data,” Navarro says. “The ‘data cyborg’, if you allow the simile, incorporates the best of human creativity and feelings together with the cold, fast, algorithmic logic of bots.”

The JAM Sessions Methodology is a process Navarro has devised to stimulate collaboration between professionals with the explicit aim of creating ‘outside the box’ thinking, which will lead to strategic marketing and business insights. Like the jam bands he admires, it’s about experimenting with a range of tools to find solutions that work; taking creative, collaborative thinking to drive commercial success. The JAM Sessions Methodology motivates interdisciplinary collaboration and facilitates communications between individuals at different statistical skill levels.

To ensure JAM would catch on, Navarro says he had to find a way to democratize data science so that people from different backgrounds could adopt the methodology in a meaningful way. “Data is said to be the “new oil” in our age,” he says. “But I think that we are in a transition period where some of the new possibilities are still constrained by old ways of thinking.”

Real-time data exploration in JMP makes for fruitful collaboration

Though most at Telefónica were already avid users of Excel, Navarro realized that in order to drive a real cultural shift within the organization, they required a new tool; a software package with a more sophisticated analytics backend than Excel, Tableau or SPSS, and also a more user-friendly, interactive interface that wouldn’t be daunting for statistics naïve employees.

“I'm always in the scanning mode,” Navarro says. “I'm very curious and always want to try new tools and see how they perform.” When he first encountered JMP, Navarro recalls, the impression was immediate. “JMP can do everything that SPSS can, and plenty more things too. It's so interactive, so visual.” JMP is now fundamental in bringing the insights that drive behavioral change – and with it, better business across Telefónica.

JAM Flow

“You can be an open-source minded data scientist and still be in love with JMP.”

At the moment, Navarro and his team are working with pricing, looking at market data as well as external figures – including things like weather and macro-economic data sets – to produce insights about internet usage and costs. For Navarro data visualization is the most important part of the process; “There is a magic effect in ‘touching the data’,” he explains. “Sometimes visualization is enough, but storytelling with data is key. JMP Graph Builder is king here. We do a lot of modelling and multivariate analysis and the new Project feature in JMP 14 makes it very easy to document complex processes.”

For those with less statistical training, features like JMP Projects help facilitate JAM Session conversations that would not have been previously possible. “The Project feature is a real game-changer… People are excited,” Navarro says. “We can now use JMP like a PowerPoint.”

Even the more experienced data scientists in Telefónica’s ranks see significant advantages in JMP, Navarro adds. Though statisticians or developers at Telefónica may regularly write scripts or contribute to an increasingly vast open-source library, they still benefit considerably from the graphical interactivity of JMP. The JMP Graph Builder is a cornerstone of data exploration, even when data scientists may choose to run their own scripts in R or Python with the output.

“Sometimes our data comes from a process that originated in R or in Python, but then we feed it into JMP... connect through the query builder to a data set and then do the exploration and gain insights,” Navarro says. “You can be an open-source minded data scientist and still be in love with JMP.”

JAM Flow

JMP bridges the gap between creative experimentation and useful application

Applying a collaborative, creative approach to statistical analysis is at the very heart of Navarro’s work and his JAM Sessions Methodology; he is passionate about demystifying the world of data both within Telefónica and beyond.

“As far as Telefónica Germany’s Digital Command Centre is concerned, conducting JAM Sessions is an open exercise of insight generation where business knowledge comes across statistics with visual interfaces facilitating team-ups between non-statistical experts and data scientists,” explains Navarro. “Ideas flow spontaneously and unexpectedly. Nevertheless, the same way an impromptu concerto is possible only after years of practice and study, a systematic methodology is needed for this serendipity to be achieved in a useful way: insights and theories ought to be grounded.”

The JAM Sessions Methodology: an overview

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The results illustrated in this article are specific to the particular situations, business models, data input and computing environments described herein. Each SAS customer’s experience is unique, based on business and technical variables, and all statements must be considered nontypical. Actual savings, results and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software.

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