Hewlett Packard Enterprises’ CEO, Meg Whitman, keynoted at Infosys’ Confluence 2017 last week and her message was on point…five years on point.
Meg Whitman figured a few things out fast when she became the 4th CEO of Hewlett-Packard within a 13-month span. If she was going to lead the company in a turnaround where qualified predecessors before her had failed, it would take five years; playing to their strengths versus shoring up weaknesses, and a culture shift more difficult than any technological change. And getting those messages out early and often may have just saved her job and the company.
Her key messages to the board, the investors, and the employees came from the first two – time and strengths. And sticking to those key messages gave the company the what, why and how Hewlett-Packard would transform from an outdated behemoth back to the industry-leading innovator she believes will eventually change the way we compute (see HP Labs puts optical connections inside the server).
In her bid for California Governor, Meg learned the power of a story and telling the story again, and again, and, yes, again. The five-year transformation strategy became her corporate stump speech. A speech delivered consistently and without corporate speak, with examples of successes and failures, with a vision for a new future and a plan to reach that desired future.
She knew even when it felt stale to her, it was what the company and its stakeholders needed to hear. Her message drumbeat was so steady and on-message that even the press cajoled her for consistency.
Messages must be backed by action and progress toward outcomes. However, when she placed the 5-year transformation stake in the ground, her messages became her lifeline. When investors wanted to know why the company hadn’t turned around in 12 months, she could point to her consistent message it would take five years, not one to meet their objectives, but she had a plan and they were on track. The company had to get smaller to go faster and one large Hewlett-Packard became four, more nimble entities. She reduced the company’s internal applications from 9500 to 350. She’s also betting, and betting big, on a return to their innovation roots by showcasing their next-generation computing prototype, The Machine, their testbed for memory-centric computing.
But if you’ve been following Hewlett-Packard Enterprise, you already knew their strategic path, because Meg has been saying it for years.
The Internet of Things provides an opportunity for cable and satellite TV companies. The window is closing fast, however, as competition from Amazon and other smart home devices are in place tosupplant the set-top box permanently.
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We've all been there. To that land of customer enchantment and delight where a recording tells us our calls are important. In fact, we’re so important that we're typically put on hold and pushed to a self-serve website to solve our own problems. If we want to talk to a human being, there’s little satisfaction in knowing our calls will be handled in the order they were received.
In today’s hyper-competitive telecommunications, media and entertainment industry–particularly the rapidly developing OTT video content delivery market–customers rightfully have all the power and come and go as they please. So pleasing them is a good idea to avoid losing customers, the revenue associated with their departure, and added expense of acquiring new ones. With free video service promos, package flexibility, predatory pricing and lack of differentiation OTT churn is inevitable. The question then becomes how can service providers better understand and anticipate churn to reduce it? Even market leaders with less than two percent churn have room for significant improvement.
The short answer lies in applying data analytics in an insightful, predictive and more urgent manner. Anybody can crunch numbers, but too few are able to identify and put to good use the most important and relevant data that can minimize customer loss and the cost of marketing to retain them. That’s where implementing and operationalizing an Insights-as-a-Service model can help organizations become smarter and better control churn.
Insights-as-a-Service, in the true sense of the definition, is more than a self-service dashboard; it’s answers by the slice. Such an approach enables significantly improved utilization of marketing dollars through personalized micro-targeting. Here’s an example: two subscribers are nearing the end of a trial period or popular season of content. Subscriber ‘A’ lives in the city with lightning fast signal via newly laid fiber. Subscriber ‘B’ lives in a suburb with known antiquated cable lines. Using a set of internal company and third-party data, the company can move away from its blanket use of service continuation offers and personalize the best offer for each subscriber, which will vary by individual broadband speed (and plans for improving speed), content engagement, credit history and other account data points. The company can spend less money by customizing offers and not over incentivizing happy customers that would continue on with or without an offer.
Generally speaking, building or reinvesting in your own big data and analytics infrastructure makes no sense because it’s incredibly expensive and takes far too long to gain or retain a competitive advantage, especially on pre-pay. Instead, why not buy the answers using your data and a service provider’s pre-existing capabilities including hardware, software, open source and third-party data? These service providers can leverage in-place and maintained assets along with industry-specific data scientists to produce advanced analytics that discerns previously unidentified signals in the vast and diverse data sets. Further, they can provide insights that create real competitive advantage—quickly. With well-informed and executed Insights-as-a-Service, churn model enhancements leading to improved customer experiences and more focused retention treatments can be operationalized for real impact within a few months instead of years.
In a nutshell, that’s how you can learn from churn.