SAP HANA 2 – Revolution or Evolution?
Yesterday SAP announced SAP HANA 2, an updated and improved version of its flagship product SAP HANA, and new SAP HANA microservices through SAP Hybris as a Service. SAP HANA 2 will be available for first customers on November 30 and an express edition shortly after its general availability. Note: if SAP talks about RTC this usually differs from General Availability, which is only after a successful ramp-up period of about 3 months to validate a product with early adopter customers. So the Express Edition will probably be released around end of Q1/2017. In usual bold marketing words SAP HANA 2 is poised to be a “new foundation for digital transformation” and is according to Bernd Leukert, member of the executive board, Products and Innovation at SAP SE, the continuation of “breakthrough innovation on a highly stable core data platform for our customers”. SAP HANA 2 shall deliver enhancements in the areas of database management, data management, analytical intelligence and application management as well as well as two more services for cloud customers: Text Analysis and Earth Observation Analysis. The latter in a beta status only. These latter two new HANA functionalities are likely to be the reason of tying the two announcements. The update cycle of HANA 2 shall be 6 months. Some Observations It is interesting that SAP refers to the new HANA services as microservices. This suggests that these services are built on top of the HANA 2 core – or else HANA itself has been rearchitected to be built on a microservice architecture. I rather think the former, also as the delivery is via YaaS....
Omnichannel – Myth, Reality or Utopia?
Omnichannel – is it a Myth, Reality or Utopia? Over the past 20 or so years the way products and services get sold and customer service as well as marketing get delivered changed dramatically. Gone are the times where a potential customer was addressed via a radio- or TV-spot or an ad printed in a newspaper, advertising mail in the mailbox … – well, it still happens, but the focus shifted dramatically. We started off from one single ‘channel’ – customer goes to the store and interacts with a person – and added an ever increasing number of additional ones, like the ones mentioned, plus many more. For retail businesses the store will not go away. Generally spoken, human interaction will stay important, probably increase in importance; human customer service will not vanish – but is likely to change … please hold this thought. In today’s omnichannel world we also have telephone, e-mail, web-delivered ads, mobile apps, branded and white-label communities, social media like Facebook, Instagram, Twitter, etc., knowledge bases in combination with self-service, chat, messenger applications like WhatsApp, FB Messenger, Snapchat, iMessage; chat supported by ‘machine intelligence’, exposed via so called chatbots, and what not. The list could virtually go on and on. This is all supported by and implemented on a platform that leverages integrated applications, which work on a joint, or at least consistent data model – with clean data – utilizing strong real-time analytics capabilities that powers both, customer segmentation and knowledge categorization for efficient search. And it delivers a great customer experience. In Real Life Uhhm, I am just awaking from my dream …...
Customer Experience – It is all in the Data. Really?
A while after my earlier discussion with Abinash Tripathy from Helpshift about the value for customer experience of bots in customer support he contacted me with some exciting news about what he and his team are doing now. Believe me, it is interesting – but read for yourself. Our conversation, of course, led on to another vivid discussion about things to come and things that in our opinions should come. The bottom line is that we live in a data driven, always on, real-time world, where prediction of events or the ability to suggest an action is becoming increasingly a differentiator … be it in a B2B- or a B2C world. Think of Rolls-Royce selling uptime of their engines, entire airplanes nearly continuously sending telemetry data “home”, or the massive amount of data that a Formula 1 car continually sends in order for the team to take proper real-time decisions. Any car already collects a lot of data – it just needs to get connected to allow for prediction of maintenance to prevent failures. Or think of entire power grids that are already instrumented in a way that allows the operator to predict a failure several days in advance, so that the affected element can get fixed before it fails. It is all in the data? The secret is in having the data. And in the algorithms, be they event- and rule based, or more sophisticated and using machine- or deep learning. Neither data nor algorithms alone are the goal. Because what is needed is actionable insight. Actionable insight emerges only if the right algorithms are applied to the...