thomas.wieberneit@aheadcrm.co.nz
Gartner MQ BI and Analytics Platforms – Lots of Movement

Gartner MQ BI and Analytics Platforms – Lots of Movement

Last week Gartner published the updated version of its Magic Quadrant for Business Intelligence and Analytics Platforms, and I need to say that there has been a lot of movement in both directions, up as well as down. There has been a lot of reshuffling especially in the Visionaries quadrant. This can partly be attributed to a changing market that caused Gartner to combine a few of last year’s assessment criteria as well as adding two more critical criteria as below: Critical Capabilities Dropped or Changed: Combined BI Platform Administration with Security and User Administration Modified Data Source Connectivity to Data Source Connectivity and Ingestion Combined Publish Analytics Content and Collaboration and Social BI to Publish, Share and Collaborate on Analytic Content Added Visual Appeal to Ease of Use Capabilities Added: Smart Data Discovery Platform Capabilities Workflow Integration Smart Data Discovery emphasizes the increasing importance of AI and machine learning as part of analytics systems. Gartner defines it around the automatically “finding, visualizing and narrating of important findings such as correlations, exceptions, clusters, links and predictions in data that are relevant to users without requiring them to build models or write algorithms. Users explore data via visualizations, natural-language-generated narration, search and natural-language query technologies”. Workflow Integration acknowledges that there is no actionable insight if there is a standalone analytics system. It is defined around the number of products “needed to deliver the critical capabilities and the degree of seamless integration and workflow between capabilities/components”. This has been true for a long time, but hey, better late than never. Gartner itself states that the changes have been major and that...
AI and Bots will kill our Future – Or Not

AI and Bots will kill our Future – Or Not

After the Hype 2016 has been the year of bots, AI, and automation the beginning of 2017 seems to be the time of looking at wider implications. There is a lot of discussion going on in academia, politics, and on the web, e.g. the one spurred by Denis Pombriant with a very readable article, and two follow-ups here and here, in November and December 2016. Denis, supported by Vinnie Mirchandani, took a very optimistic stance – something that is highly important in times of simplification and pessimism. There is no doubt in my mind that technologies that are driven by artificial intelligence can have a tremendous benefit for both, companies and organizations, as well as consumers. Consumer technology like Amazon’s Alexa, Google Assistant, Siri, generally intelligent home automation, self driving cars, etc., can simplify peoples’ lives tremendously by taking away routine activities or making it just easier to execute them. Organizations can create improved customer and employee experiences via automating existing processes, and they could create entirely new experiences using technology – doing things more effectively. Opportunities to do so can be found within the complete value chain. Automation also serves the aspect of doing the same, or more, at less cost, i.e. more efficiently. And in the last point lies a catch. This means that less people are needed to deliver on an amount of work. This means less employed people and, on a first view, more unemployment. This means less disposable income. Because advances in technology have the tendency to benefit only a few, which are those who deliver the automation systems and those who are able...
Ocean Medallion – Which Customer Problem Does it Solve?

Ocean Medallion – Which Customer Problem Does it Solve?

A few years ago Disney embarked on a massive customer experience journey that included the introduction of a ‘Magic Band’. Disney at that time followed (and likely still does) an idea that can be paraphrased as looking at everything through the eyes of the customer and pay attention to all details. During his 2016 CRM Evolution opening keynote Dennis Snow explained this concept and implementation in depth (see also my earlier CRM Evolution post). Dennis talked about the Disney way of creating great customer experiences, which basically follows three simple rules Design your processes with the customer in mind, not with internal/operational priorities; look through the lens of the customer Pay attention to details Create little “Wow Moments”. These add up to a lasting great experience and are easier to achieve than single “big” experiences. To me the most important message that Dennis conveyed is that the simple things and consistency are what matters. Consistently provide little experiences throughout the customer life cycle. He underpinned this with some examples from the ‘ordeal’ of getting out of the park and back into the hotel. Everybody is exhausted, kids may be edgy, riding the bus is usually not fun. What about the bus driver singing some songs or doing a little trivia? The rooms showing some little surprise, like specially folded towels? Another of his core messages was that a company gets loyalty and advocacy only by creating those “wow” moments mentioned above. For this to be effective, however, it must not fail at base priorities. Customer expectations can get mapped to a pyramid. Every customer expects accuracy and availability. These...
AI and Machinelearning in 2017 – What to Expect

AI and Machinelearning in 2017 – What to Expect

2016 has been the year of Artificial Intelligence and machinelearning. With the year being almost at an end, let me chime in to the gang of pundits who venture into prediction land and pronounce what we get out of our glass balls. So here are my 5 plus 2 bonus ones. AI gets mainstream in Consumer Environments Alexa paved the way, the Google Assistant is on its heels, Microsoft Cortana wants to get there, too – and Apple, amazingly, is a late starter in this environment. Amazon started with a pretty smart strategy by not overselling the capabilities of its underlying AI, as Apple did with Siri, which caused some grief for Apple and some laughs for many people around. More and more helpful Alexa skills are developed and implemented that improve its usefulness. Similarly Google; they started late but are in the game now, too – following a different strategy of adding new functionality by just making it available in contrast to Amazon, who opt to have users individually enable ‘skills’. Identification of what these systems can do will be an interesting question. Facebook’s Mark Zuckerberg created a butler for his house, who he calls Jarvis, like the one of Tony Stark in the Ironman movies. Google recently based its translation engine on machinelearning and AI, seeing vastly improved translations. Facebook’s translations base on an AI, too – although this one still seems to have a lot to learn. Not to mention all the countless other consumer services Google has, that utilize machinelearning and AIs in the background. Two of the main developments to look at here are...
Why the Phone is Dead – And How to Accommodate for It

Why the Phone is Dead – And How to Accommodate for It

As our (digital) lives circle more and more around mobility, and consequently the mobile phone, the questions around communication-, and in particular around service- and support channels become more interesting by the day. Facebook triggered what can be dubbed a little revolution when opening its messaging platform for chatbots in 2016; meanwhile even Skype offers chatbot support. It is safe to say that chatbots have been one of the main technology trends in 2016. Slack, originally released only mid of 2013, has become one of the main collaboration- and communications platforms. Artificial Intelligence and machine learning in various flavors and strengths have become part of many business applications throughout business’s value chains. And the combination of conversational user interfaces and AI/machine learning has the potential of changing the way people interact with businesses (and data, for what it is worth in this context). Facebook, Google, Amazon, Apple, Microsoft, to name only the big players, offer voice driven digital assistants, which already now provide a hint of new engagement models between customers and companies. Intelligent, conversational systems are what we are about to see, first predominantly using chat-like user interfaces, then also merging voice into the mix, first to cover isolated situations, then increasingly for more complicated ones. Some Data Points Business Insider reported in September that the usage of chat apps has surpassed the usage of social media, measured in monthly active users. Additionally, Google found already in 2014 that 59 per cent of smartphone owners globally install games within a week of getting the phones, which is a higher percentage than any other type of app. On the...