“Next best action” is a hot focus area in customer-facing business processes, especially marketing, sales and service. But it has just as great a potential in back-end business processes, and, in fact, ensures that many companies operate smoothly.
Next best action, in the broadest perspective, is
A bus, train or car to work. A bike to school. A plane for a business trip. And even if you don't leave your home, your life is still influenced by the transportation industry: virtually every tangible good—food, clothing, medicine, vehicles, computers—has been transported into your world from
The sheer thought of the data we create and consume today is mind boggling. IBM research shows we create 2.5 quintillion bytes of data every day, and begs for a response to the question–what are we doing with all this data? A recent global survey by Jaspersoft answered this, revealing that the
"Next best action” is a hot focus area under big data, advanced analytics, digital marketing, smarter commerce and other business imperatives. Enterprises have been doing next best action, in various forms, for years. Many companies continue to scale up and build out their next-best-action
Krishnan Parasuraman, CTO of big data, IBM Digital Media, describes the three contextual factors fueling the questions around big data, including the analytic awakening, commodization of technologies, and data availability.
Recently, I was in Nice for a three-day gathering of 150 European IBM Big Data specialists. Looking around the room at the opening plenary made me think how fast the world of big data is moving and how quickly our community is growing.
One of the topics that got discussed a lot–in the breaks and in
Here are the quick-hit ponderings that I posted on various LinkedIn big data discussion groups this past week. I opened up three new themes–enterprise content warehouse, business process optimization, and big BI–and further developed the established themes of big data's optimal deployment model and
Among healthcare executives interviewed for the 2010 IBM Global CEO study, 90% expect a high or very high level of complexity of data over the next five years, but more than 40% are unprepared to deal with it. The volume, velocity and variety of data are outpacing the ability for healthcare
When you're in a hurry, the next best action for all the drivers ahead of you is simple: pull over to the shoulder so you can zip through to your appointed destination.
That, however, is never going to happen, unless you're an emergency vehicle with lights flashing and siren blaring. Traffic
While healthcare organizations are amassing vast amounts of data, multiple versions of the truth can contribute to errors in patient care and payment processes. Physicians have been on information overload for decades, contributing to the estimated 15% of diagnoses that are inaccurate or incomplete
An analytical problem can be broken down into a number of steps:
Ingest – Integration – Analysis – Interpretation
And yes, I did try to find a synonym for 'analyse' starting with an 'i' so we could have “four 'i's” to complement the “three (or four, or five depending upon your source) 'v's” of big
Customer engagement is a bit of a game, because, deep down, it’s a form of haggling and bargaining. Let’s be blunt: everybody has an ulterior purpose and is manipulating the other party in that direction. The customer is trying to get the best deal from you, and you’re trying to hold onto them and
For the past 2 months, a LinkedIn discussion group has been debating the burning question "Do You Need a PhD to Analyze Big Data?" Always itching for fresh chat, yours truly has stepped into the fray with a humble opinion or two. And I got flamed in no uncertain words. In fact, one PhD who didn't
Below are the top three questions I hear all the time from business partners and customers alike. I will take a moment to address each one. Before I do that, however, I wanted to flash back to 1995. I was responsible for building a channel around our new e-commerce offering called Net.Commerce (
Here are the quick-hit ponderings that I posted on various LinkedIn big data discussion groups this past week. I opened up one new theme–Big Media (which I'd introduced a few weeks back at this IBM big-data-relevant site) –and extended my existing discussions of peta-governance (going beyond what