We’re all fans of Apple and the products that come out of Infinity Loop. But i’m willing to wager my iBucks that there’s exactly once in a year during the WWDC, when Tim Cook goes on stage (used to Steve Jobs, may he rest in iPeace) and unviels the latest shiny upgrade to the iPhone, we’re all wondering whether that device which looks so suspiciouly much like what we bought some months back is indeed the latest evolutionary step in the technology ladder. Now, juxtapose your situation with that of a CIO of a large company who’s just been through a gruelling enterprise upgrade. Before he/she can uncork the bubbly and celebrate a job well done, a cursory glance on the www will tell them that they’re alreay lagging behind on the curve, because technology has already gotten the better of their upgrade timeline.
For the sake of discussion , let us take an example of a clothing retailer which seeks to understand the behavioral and purchasing patterns of the consumers across different geographies that it operates in. For this, it would need sales data from their PoS terminals, which are then aggregated based on seasons, collections, price, social indicators etc, and then this data is then mined to develop insights into planning for the next season. In the classical sense, this would mean that the retailer implements a bulky OLAP system onto which the data needs to be replicated from the OLTP system, extractors and infocubes are to be created and complex technical requirements are to implemented before they can productively start arriving at insights into consumer buying patterns. Even if we discount the effort that it takes to set up such a landscape, the very fact that this would still not provide us real time insights seems like a whole lot of work for what can at best be just-in-time or slightly delayed actions on the part of the company. Now, with industry leading Real TIme Analytics solutions running on in-memory platforms can do the same for ou in Real Time. Not only will your decision making be faster and more in sync with the reality on ground at-the-moment, you can also make use of different predictive analytics alorithms made available to arrive at decisions that can have a positive impact on future sales.
Channels are no longer contrained by brick and mortar and this is old news. The e-commerce boom, so far sustained by conventional browser applications on desktop computing devices have already made a splash on mobile devices, with native apps providing a wonderful user experience. Almost every analyst who’s willing to put his money where his mouth is in agreement that there will be more and more people who would embrace newer channels for doing their shopping, as long it provides them ease of access and use, at the same time not compromising on the entire ‘shopping’ experience. With companies like Apple/Samsung hogging the newsreels for their foray into wearable computing (well, Google is already there with it’s Glass, but much on that later), there’s no doubt that we’re on the cusp of many more interesting shopping experiences.
To cut the long story short, it is now as clear as daylight that the quicker you are on the uptake of new technologies, the more nimble you are, to reach to different scenarios that may arise during the course of business. This leads to huge expectations from the Technology Companies. You’re looking at catering to a application hungry market that wants to hit the ground running, without having to run large complex projects just to get started with using the ‘silver bullet’.
But is this really how it plays out really out there in the real world? To go back to the question asked right at the beginning, how many of us religiously change our phone every year, to stay ‘up-to-date’?
More to follow…