Reader Forum: The dilemma of the broken cell phone

Editor’s Note: Welcome to our weekly Reader Forum section. In an attempt to broaden our interaction with our readers we have created this forum for those with something meaningful to say to the wireless industry. We want to keep this as open as possible, but maintain some editorial control so as to keep it free of commercials or attacks. Please send along submissions for this section to our editors at: [email protected] or [email protected].
A customer returns a broken cell phone to the wireless counter at a big retail store. What happens next?
Sounds simple, but this situation actually describes an extremely complex, multidimensional problem influencing everything from customer satisfaction and brand value to supply chain effectiveness and revenue generation.
Why so complicated? For starters, even a broken cell phone is worth something – you don’t just toss it. In this scenario, there are a number of potential options available to the sales rep, who can offer to fix or replace the phone. Furthermore, if the first option is chosen, then the customer might (or might not) be offered a loaner phone during the repair period.
Arriving at the optimal choice means answering a number of other key questions. For example, how valuable is the customer? Maybe valuable enough that you want to offer them a new phone on the spot. In that case, what kind of phone? And what do you do with the broken phone? Do you refurbish it and sell it to someone else? Or, do you break it down to its components and sell them on the spot market for those items?
As you can see, figuring out what to do with the broken cell phone isn’t so simple after all. It quickly evolves into a really difficult analytical problem that, at least partially, must be solved in real time while the customer is at the counter.
Fortunately, the past several years have witnessed a big leap forward in the ability of companies to address this type of situation. Businesses have begun to integrate their vast and widely-scattered stores of data, in turn enabling analytics systems to transform that raw information into actionable intelligence.
The development of analytics systems have similarly progressed to a level of sophistication unimaginable just a few years ago. The Watson computing system that competed and won on the “Jeopardy!” quiz program is a great example. Watson represents a leap forward in artificial intelligence that can analyze human language and answer complex questions extremely fast. On “Jeopardy!”, Watson correctly responded to the kind of complex clues that the show is famous for. An example, from a “Jeopardy!” category called Literary Character APB:
Host Alex Trebek: Wanted for a 12-year crime spree of eating King Hrothgar’s warriors; Officer Beowulf has been assigned to the case.
Watson: Who is Grendel? [the correct answer]
Watson evaluates the equivalent of hundreds of millions of pages of material – books, reports, articles, and so on – in three seconds or less. It is not stymied by intricate wordplay. In the above example, modern crime lingo was used to pose a question about a literary classic (Beowulf) from 1,000 years ago. Watson was unfazed.
Imagine how Watson technology could handle the dilemma of the broken cell phone. Integrated into a company’s core systems – including databases, CRM, analytics systems, inventory and order management, market data, plus all points of interaction with customers – Watson’s prowess could give managers the insight to make far better strategic decisions.
It could enable the cellular provider to ask relevant questions — instantaneously — about the customer, such as: “Should we repair or replace the cell phone?”
Watson could then easily and immediately analyze the type of cellular plan and model phone the customer has, the market segment the customer belongs to, any relevant customer preferences, the phone’s repair history, whether the loss of that customer would likely result in other customers cancelling their service, and so on.
Watson could integrate that data with additional information – such as today’s market price of the broken cell phone’s components versus the profit likely to result from selling a refurbished phone. In a few seconds, Watson could arrive at the right answer: Offer the customer a new 4G smartphone with 500 bonus minutes; disassemble the broken cellphone down into its components and sell them on the spot market. This is an informed business decision derived from instantaneously analyzing a wealth of disparate data.
As the economy recovers, the companies that will emerge as leaders will be the ones that take a holistic view of their operations, using sophisticated analytics technologies to find the optimum solutions to supremely difficult challenges. These successful companies will consistently make decisions that earn the highest levels of customer satisfaction, while at the same time driving increased revenues and profits. They will have a huge advantage over competitors that are still doing business the old way.